Title |
Which of Our Modeling Predictions Are Robust?
|
---|---|
Published in |
PLoS Computational Biology, July 2012
|
DOI | 10.1371/journal.pcbi.1002593 |
Pubmed ID | |
Authors |
Rob J. De Boer |
Abstract |
In theoretical ecology it is well known that the steady state expressions of the variables in a food chain crucially depend on the parity of the length of the chain. This poses a major problem for modeling real food webs because it is difficult to establish their true number of trophic levels, with sometimes rare predators and often rampant pathogens. Similar problems arise in the modeling of chronic viral infections. We review examples where seemingly general interpretations strongly depend on the number of levels in a model, and on its specific equations. This Perspective aims to open the discussion on this problem. |
X Demographics
The data shown below were collected from the profiles of 5 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 | 1 | 20% |
United Kingdom | 1 | 20% |
Unknown | 3 | 60% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 60% |
Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 13 | 13% |
Netherlands | 2 | 2% |
Portugal | 2 | 2% |
Spain | 2 | 2% |
Switzerland | 1 | 1% |
France | 1 | 1% |
Brazil | 1 | 1% |
India | 1 | 1% |
United Kingdom | 1 | 1% |
Other | 5 | 5% |
Unknown | 70 | 71% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 35 | 35% |
Student > Ph. D. Student | 30 | 30% |
Student > Doctoral Student | 6 | 6% |
Professor > Associate Professor | 6 | 6% |
Student > Master | 4 | 4% |
Other | 12 | 12% |
Unknown | 6 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 41 | 41% |
Biochemistry, Genetics and Molecular Biology | 11 | 11% |
Mathematics | 10 | 10% |
Computer Science | 7 | 7% |
Physics and Astronomy | 5 | 5% |
Other | 17 | 17% |
Unknown | 8 | 8% |