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Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub‐continental scales

Overview of attention for article published in Ecological Applications, June 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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Title
Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub‐continental scales
Published in
Ecological Applications, June 2017
DOI 10.1002/eap.1545
Pubmed ID
Authors

Sarah M. Collins, Samantha K. Oliver, Jean‐Francois Lapierre, Emily H. Stanley, John R. Jones, Tyler Wagner, Patricia A. Soranno

Abstract

Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern US region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern US region, leading to weak relationships between drivers and stoichiometry. Our results suggest ecological context mediates controls on lake nutrients and stoichiometry. Predicting stoichiometry was generally more difficult than predicting nutrient concentrations, but human activity may decouple N and P, leading to better prediction of N:P stoichiometry in regions with high anthropogenic activity. This article is protected by copyright. All rights reserved.

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The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 31%
Student > Ph. D. Student 17 29%
Student > Doctoral Student 6 10%
Student > Master 6 10%
Student > Bachelor 2 3%
Other 2 3%
Unknown 8 14%
Readers by discipline Count As %
Environmental Science 22 37%
Agricultural and Biological Sciences 12 20%
Earth and Planetary Sciences 7 12%
Medicine and Dentistry 2 3%
Economics, Econometrics and Finance 1 2%
Other 3 5%
Unknown 12 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 05 July 2017.
All research outputs
#4,188,245
of 23,577,654 outputs
Outputs from Ecological Applications
#1,032
of 3,230 outputs
Outputs of similar age
#72,739
of 318,172 outputs
Outputs of similar age from Ecological Applications
#16
of 42 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,230 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.5. This one has gotten more attention than average, scoring higher than 67% 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 318,172 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 42 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 61% of its contemporaries.