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Linking terrestrial phosphorus inputs to riverine export across the United States

Overview of attention for article published in Water Research, July 2017
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  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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Article details
Title
Linking terrestrial phosphorus inputs to riverine export across the United States
Published in
Water Research, July 2017
DOI 10.1016/j.watres.2017.07.037
Pubmed ID
Authors
Abstract

Humans have greatly accelerated phosphorus (P) flows from land to aquatic ecosystems, causing eutrophication, harmful algal blooms, and hypoxia. A variety of statistical and mechanistic models have been used to explore the relationship between P management on land and P losses to waterways, but our ability to predict P losses from watersheds often relies on small scale catchment studies, where detailed measurements can be made, or global scale models that that are often too coarse-scaled to be used directly in the management decision-making process. Here we constructed spatially explicit datasets of terrestrial P inputs and outputs across the conterminous U.S. (CONUS) for 2012. We use this dataset to improve understanding of P sources and balances at the national scale and to investigate whether well-standardized input data at the continental scale can be used to improve predictions of hydrologic P export from watersheds across the U.S. We estimate that in 2012 agricultural lands received 0.19 Tg more P as fertilizer and confined manure than was harvested in major crops. Approximately 0.06 Tg P was lost to waterways as sewage and detergent nationally based on per capita loads in 2012. We compared two approaches for calculating non-agricultural P waste export to waterways, and found that estimates based on per capita P loads from sewage and detergent were 50% greater than Discharge Monitoring Report Pollutant Loading Tool. This suggests that the tool is likely underestimating P export in waste the CONUS scale. TP and DIP concentrations and TP yields were generally correlated more strongly with runoff than with P inputs or P balances, but even the relationships between runoff and P export were weak. Including P inputs as independent variables increased the predictive capacity of the best-fit models by at least 20%, but together inputs and runoff explained 40% of the variance in P concentration and 46-54% of the variance in P yield. By developing and applying a high-resolution P budget for the CONUS this study confirms that both hydrology and P inputs and sinks play important roles in aquatic P loading across a wide range of environments.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 85 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 15 18%
Student > Ph. D. Student 14 16%
Student > Master 9 11%
Student > Doctoral Student 6 7%
Other 4 5%
Other 12 14%
Unknown 25 29%
Readers by discipline
Readers by discipline Count As %
Environmental Science 25 29%
Agricultural and Biological Sciences 9 11%
Engineering 8 9%
Biochemistry, Genetics and Molecular Biology 4 5%
Earth and Planetary Sciences 4 5%
Other 8 9%
Unknown 27 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 February 2020.
All research outputs
#7,716,445
of 25,382,440 outputs
Outputs from Water Research
#2,751
of 11,877 outputs
Outputs of similar age
#106,888
of 307,458 outputs
Outputs of similar age from Water Research
#52
of 206 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 11,877 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 307,458 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 206 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.