| Title |
Networks of plants: how to measure similarity in vegetable species
|
|---|---|
| Published in |
Scientific Reports, June 2016
|
| DOI | 10.1038/srep27077 |
| Pubmed ID | |
| Authors |
Gianna Vivaldo, Elisa Masi, Camilla Pandolfi, Stefano Mancuso, Guido Caldarelli |
| Abstract |
Despite the common misconception of nearly static organisms, plants do interact continuously with the environment and with each other. It is fair to assume that during their evolution they developed particular features to overcome similar problems and to exploit possibilities from environment. In this paper we introduce various quantitative measures based on recent advancements in complex network theory that allow to measure the effective similarities of various species. By using this approach on the similarity in fruit-typology ecological traits we obtain a clear plant classification in a way similar to traditional taxonomic classification. This result is not trivial, since a similar analysis done on the basis of diaspore morphological properties do not provide any clear parameter to classify plants species. Complex network theory can then be used in order to determine which feature amongst many can be used to distinguish scope and possibly evolution of plants. Future uses of this approach range from functional classification to quantitative determination of plant communities in nature. |
X Demographics
The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 15% |
| Italy | 3 | 11% |
| Spain | 2 | 7% |
| Ecuador | 1 | 4% |
| France | 1 | 4% |
| Japan | 1 | 4% |
| Indonesia | 1 | 4% |
| Argentina | 1 | 4% |
| United Kingdom | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 11 | 41% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 15 | 56% |
| Scientists | 11 | 41% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Indonesia | 1 | 2% |
| Italy | 1 | 2% |
| Estonia | 1 | 2% |
| Japan | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 38 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 21% |
| Student > Master | 6 | 14% |
| Researcher | 6 | 14% |
| Student > Bachelor | 5 | 12% |
| Student > Doctoral Student | 4 | 9% |
| Other | 4 | 9% |
| Unknown | 9 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 28% |
| Environmental Science | 4 | 9% |
| Biochemistry, Genetics and Molecular Biology | 3 | 7% |
| Medicine and Dentistry | 2 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 5% |
| Other | 10 | 23% |
| Unknown | 10 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 10 October 2017.
All research outputs
#2,167,353
of 23,577,761 outputs
Outputs from Scientific Reports
#19,330
of 127,567 outputs
Outputs of similar age
#39,740
of 343,068 outputs
Outputs of similar age from Scientific Reports
#553
of 3,563 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 127,567 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.4. This one has done well, scoring higher than 84% 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 343,068 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 88% of its contemporaries.
We're also able to compare this research output to 3,563 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.