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Visually mediated neighbour recognition in the fiddler crab Uca capricornis

Mating signals are often directed at numerous senses, and provide information about species identity, gender, receptiveness, individual identity and mate quality. Given the diversity of colourful body patterns in invertebrates, surprisingly few studies have examined the role of these visual signals in mate recognition. This experiment demonstrates that distinct carapace colour patterns in the fiddler crab, Uca capricornis, enable males to discriminate between their female neighbours and unfamiliar females.

The experiment was conducted in the East Point Reserve, Darwin, NT from September to January 2003 and 2004.

The methodology involved identifying male and female U.capricornis neighbours living 10-30cm apart. The female was caught and randomly assigned to one of seven treatments, including replacement with a similar sized female, and various manipulations to alter her appearance. The female was then tethered close to the males burrow and the interaction monitored. The males behaviour was classified as either 'approach' or 'ignore.' The results show that males tended to approach unfamiliar females tethered nearby, whereas they were more likely to ignore their unaltered neighbours tethered in the same position.

Data and Resources

Additional Info

Field Value
Title Visually mediated neighbour recognition in the fiddler crab Uca capricornis
Type Dataset
Language English
Licence Creative Commons Attribution 2.5 Australia
Data Status inactive
Update Frequency never
Landing Page https://data.gov.au/data/dataset/d36b86e2-c0a2-4b52-acc0-9ae61eb38e0e
Date Published 2017-06-24
Date Updated 2023-08-11
Contact Point
Australian National University
Tanya.Detto@hotmail.com
Temporal Coverage 2017-06-24 20:01:47
Geospatial Coverage {"type": "Polygon", "coordinates": [[[130.5, -13.0], [131.0, -13.0], [131.0, -12.0], [130.5, -12.0], [130.5, -13.0]]]}
Jurisdiction Commonwealth of Australia
Data Portal data.gov.au
Publisher/Agency Australian National University