Cookies Policy

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

Optimistic and Pessimistic Fruit Flies: Evaluating Fitness Consequences of Estimation Errors

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
You must be logged in to use this functionality

image of Behaviour

I began with an observation that there exists consistent variation among fruit-parasitic female flies (Rhagoletis pomonella) with regard to search time allocation. In essence, populations appear to be composed of flies that are "optimistic" and "pessimistic" about their chances of locating other higher quality patches. I posed the question "how can such variation be maintaned over time?". To answer this question I developed stochastic, dynamic, state-variable model that considered patch emigration decisions by individuals as a function of: (1) current patch quality, (2) average patch quality, (3) density of patches, (4) time of day, and, (5) egg load. The model was then altered to allow for optimistic and pessimistic estimates of patch availability. The optimal behaviour for such flies was then solved. Results obtained showed that optimists move more often within trees and pessimists move more frequently among trees. Further, calculation of daily reproductive output showed that both optimists and pessimists performed nearly as well as flies with errorless estimates of patch availability so long as over and under-estimates were moderate. This is because of the interaction between egg limitation, host availability and time limitation. When patch estimate errors were large (e.g. 90%), however, pessimists performed less well than optimists. These results allowed me to derive fitness curves for optimists and pessimists. These curves were then used to predict the distribution of search allocation by flies in the field. Predictions as to the shape of the distribution were consistent with field data (i.e. optimists are over-represented in samples).

Affiliations: 1: (Behavioural Ecology Research Group, Department of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada, V5A 1S6


Full text loading...


Data & Media loading...

Article metrics loading...



Can't access your account?
  • Tools

  • Add to Favorites
  • Printable version
  • Email this page
  • Subscribe to ToC alert
  • Get permissions
  • Recommend to your library

    You must fill out fields marked with: *

    Librarian details
    Your details
    Why are you recommending this title?
    Select reason:
    Behaviour — Recommend this title to your library
  • Export citations
  • Key

  • Full access
  • Open Access
  • Partial/No accessInformation