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Interactions among resource partitioning, sampling effect, and facilitation on the biodiversity effect: a modeling approach

Overview of attention for article published in Oecologia, September 2013
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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1 X user
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1 Wikipedia page

Citations

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11 Dimensions

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80 Mendeley
Title
Interactions among resource partitioning, sampling effect, and facilitation on the biodiversity effect: a modeling approach
Published in
Oecologia, September 2013
DOI 10.1007/s00442-013-2775-8
Pubmed ID
Authors

Pedro Flombaum, Osvaldo E. Sala, Edward B. Rastetter

Abstract

Resource partitioning, facilitation, and sampling effect are the three mechanisms behind the biodiversity effect, which is depicted usually as the effect of plant-species richness on aboveground net primary production. These mechanisms operate simultaneously but their relative importance and interactions are difficult to unravel experimentally. Thus, niche differentiation and facilitation have been lumped together and separated from the sampling effect. Here, we propose three hypotheses about interactions among the three mechanisms and test them using a simulation model. The model simulated water movement through soil and vegetation, and net primary production mimicking the Patagonian steppe. Using the model, we created grass and shrub monocultures and mixtures, controlled root overlap and grass water-use efficiency (WUE) to simulate gradients of biodiversity, resource partitioning and facilitation. The presence of shrubs facilitated grass growth by increasing its WUE and in turn increased the sampling effect, whereas root overlap (resource partitioning) had, on average, no effect on sampling effect. Interestingly, resource partitioning and facilitation interacted so the effect of facilitation on sampling effect decreased as resource partitioning increased. Sampling effect was enhanced by the difference between the two functional groups in their efficiency in using resources. Morphological and physiological differences make one group outperform the other; once these differences were established further differences did not enhance the sampling effect. In addition, grass WUE and root overlap positively influence the biodiversity effect but showed no interactions.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 3%
Argentina 2 3%
South Africa 1 1%
Mexico 1 1%
Romania 1 1%
United States 1 1%
Unknown 72 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 23%
Researcher 18 23%
Student > Master 10 13%
Student > Bachelor 7 9%
Student > Doctoral Student 5 6%
Other 12 15%
Unknown 10 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 46%
Environmental Science 18 23%
Earth and Planetary Sciences 3 4%
Computer Science 1 1%
Psychology 1 1%
Other 5 6%
Unknown 15 19%
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 24 February 2023.
All research outputs
#7,956,818
of 25,369,304 outputs
Outputs from Oecologia
#1,621
of 4,475 outputs
Outputs of similar age
#66,568
of 215,425 outputs
Outputs of similar age from Oecologia
#9
of 44 outputs
Altmetric has tracked 25,369,304 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 4,475 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has gotten more attention than average, scoring higher than 62% 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 215,425 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 67% of its contemporaries.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.