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Learning and robustness to catch-andrelease fishing in a shark social network
Abstract : Individuals can play different roles in maintaining connectivity and social
cohesion in animal populations and thereby influence population robustness
to perturbations.We performed a social network analysis in a reef shark population
to assess the vulnerability of the global network to node removal under
different scenarios. We found that the network was generally robust to the
removal of nodes with high centrality. The network appeared also highly
robust to experimental fishing. Individual shark catchability decreased as a
function of experience, as revealed by comparing capture frequency and site
presence. Altogether, these features suggest that individuals learnt to avoid
capture, which ultimately increased network robustness to experimental
catch-and-release. Our results also suggest that some caution must be taken
when using capture–recapture models often used to assess population size
as assumptions (such as equal probabilities of capture and recapture) may
be violated by individual learning to escape recapture.
https://hal-univ-perp.archives-ouvertes.fr/hal-01561754
Contributor : Dorian Miler <>
Submitted on : Thursday, July 13, 2017 - 11:50:00 AM
Last modification on : Thursday, March 19, 2020 - 3:02:04 PM
Contributor : Dorian Miler <>
Submitted on : Thursday, July 13, 2017 - 11:50:00 AM
Last modification on : Thursday, March 19, 2020 - 3:02:04 PM
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