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Stream Macroinvertebrate Response Models for Bioassessment Metrics: Addressing the Issue of Spatial Scale

Overview of attention for article published in PLOS ONE, March 2014
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Title
Stream Macroinvertebrate Response Models for Bioassessment Metrics: Addressing the Issue of Spatial Scale
Published in
PLOS ONE, March 2014
DOI 10.1371/journal.pone.0090944
Pubmed ID
Authors

Ian R. Waite, Jonathan G. Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, James L. Orlando

Abstract

We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance. We selected macroinvertebrate sampling sites for model development (n = 591) and validation (n = 467) that met strict screening criteria from four proximal ecoregions in the northeastern U.S.: North Central Appalachians, Ridge and Valley, Northeastern Highlands, and Northern Piedmont. Models were developed using boosted regression tree (BRT) techniques for four macroinvertebrate metrics; results were compared among ecoregions and metrics. Comparing within a region but across the four macroinvertebrate metrics, the average richness of tolerant taxa (RichTOL) had the highest R(2) for BRT models. Across the four metrics, final BRT models had between four and seven explanatory variables and always included a variable related to urbanization (e.g., population density, percent urban, or percent manmade channels), and either a measure of hydrologic runoff (e.g., minimum April, average December, or maximum monthly runoff) and(or) a natural landscape factor (e.g., riparian slope, precipitation, and elevation), or a measure of riparian disturbance. Contrary to our expectations, Full Region models explained nearly as much variance in the macroinvertebrate data as Individual Ecoregion models, and taking into account watershed size or elevation did not appear to improve model performance. As a result, it may be advantageous for bioassessment programs to develop large regional models as a preliminary assessment of overall disturbance conditions as long as the range in natural landscape variability is not excessive.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
Brazil 1 2%
Unknown 60 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 23%
Student > Master 12 19%
Student > Ph. D. Student 11 17%
Student > Bachelor 5 8%
Other 4 6%
Other 6 9%
Unknown 11 17%
Readers by discipline Count As %
Environmental Science 21 33%
Agricultural and Biological Sciences 20 31%
Earth and Planetary Sciences 2 3%
Engineering 2 3%
Psychology 1 2%
Other 3 5%
Unknown 15 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 01 April 2014.
All research outputs
#18,369,403
of 22,751,628 outputs
Outputs from PLOS ONE
#154,398
of 194,172 outputs
Outputs of similar age
#162,545
of 224,543 outputs
Outputs of similar age from PLOS ONE
#4,113
of 5,394 outputs
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