Search

Search Results

Dryad Logo
Dryad
Vandal, Katherine; Garant, Dany; Bergeron, Patrick; Réale, Denis 2023-11-27 <p><span lang="EN-CA">Individual exploration types are based on the cognitive speed-accuracy trade-off, which suggests that higher speed of information acquisition is done by sacrificing information quality</span><span lang="EN-CA">. In a mating context, fast exploration could thus increase the probability of finding mates at the cost of mating with kin or suboptimal partners. We tested this hypothesis by studying male mate choice patterns in a species with a scramble competition mating system. We used genotyping, localisation by radio-collar, trapping, and repeated exploration measures from a long-term study on wild Eastern chipmunks (<em>Tamias</em> <em>striatus</em>). We predicted that, according to the speed-accuracy trade-off hypothesis, slower-thorough explorers should be choosier than faster-superficial ones, and thus avoid inbreeding. We found that slower males reproduced more often with less related females, but only on one site where variance in relatedness and female density were high. Males showed no preference for their mates’ exploration type. Our results suggest that superficial exploration decreases male choosiness and increases the risk of inbreeding, but only under decreased mate search costs due to high variance in relatedness among mates (at high density). Our findings reveal exploration-related, among-individual variance in inbreeding, highlighting the complexity of mate choice, and showing that many aspects of an individual’s life contribute to animal decision-making.</span></p>

Map search instructions

1.Turn on the map filter by clicking the “Limit by map area” toggle.
2.Move the map to display your area of interest. Holding the shift key and clicking to draw a box allows for zooming in on a specific area. Search results change as the map moves.
3.Access a record by clicking on an item in the search results or by clicking on a location pin and the linked record title.
Note: Clusters are intended to provide a visual preview of data location. Because there is a maximum of 50 records displayed on the map, they may not be a completely accurate reflection of the total number of search results.