Title |
The modelling cycle for collective animal behaviour
|
---|---|
Published in |
Interface Focus, August 2012
|
DOI | 10.1098/rsfs.2012.0031 |
Pubmed ID | |
Authors |
David J. T. Sumpter, Richard P. Mann, Andrea Perna |
Abstract |
Collective animal behaviour is the study of how interactions between individuals produce group level patterns, and why these interactions have evolved. This study has proved itself uniquely interdisciplinary, involving physicists, mathematicians, engineers as well as biologists. Almost all experimental work in this area is related directly or indirectly to mathematical models, with regular movement back and forth between models, experimental data and statistical fitting. In this paper, we describe how the modelling cycle works in the study of collective animal behaviour. We classify studies as addressing questions at different levels or linking different levels, i.e. as local, local to global, global to local or global. We also describe three distinct approaches-theory-driven, data-driven and model selection-to these questions. We show, with reference to our own research on species across different taxa, how we move between these different levels of description and how these various approaches can be applied to link levels together. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 1 | 25% |
Sweden | 1 | 25% |
United Kingdom | 1 | 25% |
United States | 1 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 50% |
Members of the public | 2 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 2% |
Switzerland | 2 | 1% |
Netherlands | 1 | <1% |
Portugal | 1 | <1% |
Denmark | 1 | <1% |
United Kingdom | 1 | <1% |
Japan | 1 | <1% |
China | 1 | <1% |
Unknown | 177 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 47 | 25% |
Researcher | 27 | 14% |
Student > Master | 24 | 13% |
Student > Bachelor | 23 | 12% |
Professor | 9 | 5% |
Other | 32 | 17% |
Unknown | 27 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 69 | 37% |
Computer Science | 15 | 8% |
Physics and Astronomy | 13 | 7% |
Mathematics | 12 | 6% |
Engineering | 9 | 5% |
Other | 35 | 19% |
Unknown | 36 | 19% |