Cookies Policy
X

This site uses cookies. By continuing to browse the site you are agreeing to our use of cookies.

I accept this policy

Find out more here

A maximum likelihood approach for identifying dive bouts improves accuracy, precision and objectivity

No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.

Brill’s MyBook program is exclusively available on BrillOnline Books and Journals. Students and scholars affiliated with an institution that has purchased a Brill E-Book on the BrillOnline platform automatically have access to the MyBook option for the title(s) acquired by the Library. Brill MyBook is a print-on-demand paperback copy which is sold at a favorably uniform low price.

Access this article

+ Tax (if applicable)
Add to Favorites

image of Behaviour

Foraging behaviour frequently occurs in bouts, and considerable efforts to properly define those bouts have been made because they partly reflect different scales of environmental variation. Methods traditionally used to identify such bouts are diverse, include some level of subjectivity, and their accuracy and precision is rarely compared. Therefore, the applicability of a maximum likelihood estimation method (MLM) for identifying dive bouts was investigated and compared with a recently proposed sequential differences analysis (SDA). Using real data on interdive durations from Antarctic fur seals (Arctocephalus gazella Peters, 1875), the MLM-based model produced briefer bout ending criterion (BEC) and more precise parameter estimates than the SDA approach. The MLM-based model was also in better agreement with real data, as it predicted the cumulative frequency of differences in interdive duration more accurately. Using both methods on simulated data showed that the MLM-based approach produced less biased estimates of the given model parameters than the SDA approach. Different choices of histogram bin widths involved in SDA had a systematic effect on the estimated BEC, such that larger bin widths resulted in longer BECs. These results suggest that using the MLM-based procedure with the sequential differences in interdive durations, and possibly other dive characteristics, may be an accurate, precise, and objective tool for identifying dive bouts.

Affiliations: 1: Department of Biology, Memorial University of Newfoundland, St. John's, NL A1B 3X9, Canada; Centre d'Etudes Biologiques de Chizé, CNRS, 79 360 Villiers en Bois, France; 2: Centre d'Etudes Biologiques de Chizé, CNRS, 79 360 Villiers en Bois, France

10.1163/156853907782418213
/content/journals/10.1163/156853907782418213
dcterms_title,pub_keyword,dcterms_description,pub_author
6
3
Loading
Loading

Full text loading...

/content/journals/10.1163/156853907782418213
Loading

Data & Media loading...

http://brill.metastore.ingenta.com/content/journals/10.1163/156853907782418213
Loading

Article metrics loading...

/content/journals/10.1163/156853907782418213
2007-11-01
2016-09-27

Sign-in

Can't access your account?
  • Key

  • Full access
  • Open Access
  • Partial/No accessInformation