↓ Skip to main content

How much variance is explained by ecologists? Additional perspectives

Overview of attention for article published in Oecologia, June 2003
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
278 Mendeley
Title
How much variance is explained by ecologists? Additional perspectives
Published in
Oecologia, June 2003
DOI 10.1007/s00442-003-1328-y
Pubmed ID
Authors

Michael S. Peek, A. Joshua Leffler, Stephan D. Flint, Ronald J. Ryel

Abstract

A recent meta-analysis of meta-analyses by Møller and Jennions suggested that ecologists using statistical models are explaining between 2.5% and 5.42% of the variability in ecological studies. Although we agree that there is considerable variability in ecological systems that is not explained, we disagree with the approach and general conclusions of Møller and Jennions. As an alternate perspective, we explored the question: "How much ecological variation in relationships is not explained?" We did this by examining published studies in five different journals representative of the numerous sub-disciplines of ecology. We quantified the proportion of variance not explained in statistical models as the residual or random error compared to the total variation in the data set. Our results indicate that statistical models explain roughly half of the variation in variables of interest, vastly different from the 2.5%-5.42% reported by Møller and Jennions. This difference resulted largely from a different level of analysis: we considered the original study to be the appropriate level for quantifying variability while Møller and Jennions combined studies at different temporal and spatial scales and attempted to find universal single-factor relationships between ecological variables across study organisms or locations. Therefore, we believe that Møller and Jennions actually measured the universality of single factor effects across multiple ecological systems, not the amount of variability in ecological studies explained by ecologists. This study, combined with Møller and Jennions', illustrates importance of applying statistical models appropriately to assess ecological relationships.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 278 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 13 5%
Spain 5 2%
Germany 4 1%
United States 4 1%
Mexico 4 1%
Canada 3 1%
United Kingdom 3 1%
Switzerland 2 <1%
Australia 2 <1%
Other 10 4%
Unknown 228 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 78 28%
Student > Ph. D. Student 38 14%
Professor 30 11%
Student > Master 24 9%
Professor > Associate Professor 23 8%
Other 64 23%
Unknown 21 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 157 56%
Environmental Science 73 26%
Earth and Planetary Sciences 8 3%
Biochemistry, Genetics and Molecular Biology 1 <1%
Business, Management and Accounting 1 <1%
Other 5 2%
Unknown 33 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 25 August 2015.
All research outputs
#6,237,603
of 25,371,288 outputs
Outputs from Oecologia
#1,153
of 4,477 outputs
Outputs of similar age
#15,634
of 52,667 outputs
Outputs of similar age from Oecologia
#5
of 22 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,477 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 74% 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 52,667 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 70% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.