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Integrative modelling reveals mechanisms linking productivity and plant species richness

Overview of attention for article published in Nature, January 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)


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809 Mendeley
1 CiteULike
Integrative modelling reveals mechanisms linking productivity and plant species richness
Published in
Nature, January 2016
DOI 10.1038/nature16524
Pubmed ID

James B. Grace, T. Michael Anderson, Eric W. Seabloom, Elizabeth T. Borer, Peter B. Adler, W. Stanley Harpole, Yann Hautier, Helmut Hillebrand, Eric M. Lind, Meelis Pärtel, Jonathan D. Bakker, Yvonne M. Buckley, Michael J. Crawley, Ellen I. Damschen, Kendi F. Davies, Philip A. Fay, Jennifer Firn, Daniel S. Gruner, Andy Hector, Johannes M. H. Knops, Andrew S. MacDougall, Brett A. Melbourne, John W. Morgan, John L. Orrock, Suzanne M. Prober, Melinda D. Smith


How ecosystem productivity and species richness are interrelated is one of the most debated subjects in the history of ecology. Decades of intensive study have yet to discern the actual mechanisms behind observed global patterns. Here, by integrating the predictions from multiple theories into a single model and using data from 1,126 grassland plots spanning five continents, we detect the clear signals of numerous underlying mechanisms linking productivity and richness. We find that an integrative model has substantially higher explanatory power than traditional bivariate analyses. In addition, the specific results unveil several surprising findings that conflict with classical models. These include the isolation of a strong and consistent enhancement of productivity by richness, an effect in striking contrast with superficial data patterns. Also revealed is a consistent importance of competition across the full range of productivity values, in direct conflict with some (but not all) proposed models. The promotion of local richness by macroecological gradients in climatic favourability, generally seen as a competing hypothesis, is also found to be important in our analysis. The results demonstrate that an integrative modelling approach leads to a major advance in our ability to discern the underlying processes operating in ecological systems.

Twitter Demographics

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Geographical breakdown

Country Count As %
United States 13 2%
Switzerland 4 <1%
Spain 3 <1%
Brazil 3 <1%
Austria 2 <1%
Germany 2 <1%
France 2 <1%
Argentina 2 <1%
Canada 2 <1%
Other 11 1%
Unknown 765 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 206 25%
Researcher 186 23%
Student > Master 123 15%
Student > Bachelor 61 8%
Student > Doctoral Student 40 5%
Other 116 14%
Unknown 77 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 362 45%
Environmental Science 255 32%
Earth and Planetary Sciences 24 3%
Biochemistry, Genetics and Molecular Biology 10 1%
Medicine and Dentistry 4 <1%
Other 36 4%
Unknown 118 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 171. 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 07 March 2020.
All research outputs
of 16,016,874 outputs
Outputs from Nature
of 76,134 outputs
Outputs of similar age
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Outputs of similar age from Nature
of 925 outputs
Altmetric has tracked 16,016,874 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 76,134 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 86.5. This one has done well, scoring higher than 87% 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 372,691 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 925 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 67% of its contemporaries.