Dataset Information

Learning and robustness to catch-and-release 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.

SUBMITTER: Mourier J

PROVIDER: S-EPMC5377029 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Learning and robustness to catch-and-release fishing in a shark social network.

Mourier Johann J Brown Culum C Planes Serge S

Biology letters 20170301 3

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 sha ...[more]

PMID: 28298593

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Project description:Despite threats to human wellbeing from ecological degradation, public engagement with this issue remains at low levels. However, studies have shown that crafting messages to resonate with people's personal experiences can enhance engagement. Recreational fishing is one of the principal ways in which people interact with aquatic environments, but long-term data from this perspective are considered rare. We uncovered 852 popular media records of recreational fishing for an Australian estuary across a 140-year period. Using information contained in these articles we analysed the species composition of recreational catches over time and constructed two distinct time series of catch and effort (n fish fisher-1 trip-1; kg fish fisher-1 trip-1) for recreational fishing trips and fishing club competitions (mean n and kg fish caught across all competitors, and n and kg fish caught by the competition winner). Reported species composition remained similar over time. Catch rates reported from recreational fishing trips (1900-1998) displayed a significant decline, averaging 32.5 fish fisher-1 trip-1 prior to 1960, and 18.8 fish fisher-1 trip-1 post-1960. Mean n fish fisher-1 competition-1 (1913-1983) also significantly declined, but best n fish fisher-1 competition-1 (1925-1980) displayed no significant change, averaging 31.2 fish fisher-1 competition-1 over the time series. Mean and best kg fish fisher-1 competition-1 trends also displayed no significant change, averaging 4.2 and 9.9 kg fisher-1 competition-1, respectively. These variable trends suggest that while some fishers experienced diminishing returns in this region over the last few decades, the most skilled inshore fishers were able to maintain their catch rates, highlighting the difficulties inherent in crafting conservation messages that will resonate with all sections of a community. Despite these challenges, this research demonstrates that popular media sources can provide multiple long-term trends at spatial scales, in units and via a recreational experience that many people can relate to.

Project description:BackgroundLittle is known about the social learning of students within community-based clinical placements and ways in which it can be supported. In an allied health service-learning program, we analysed students' learning relationships to quantify what, and from whom students learnt.MethodsWe conducted a social learning network survey in four domains of learning (clinical knowledge, procedural skills, professional development, and complex determinants of health) to explore learning relationships (ties) with other people (alters) that students (egos) formed during their placement. We quantified how different roles (supervisors, health professionals, administrators, peers, schoolteachers, and clients) contributed to the students' learning in each of the four domains. We used exponential random graph models (ERGMs) to test which relational processes contributed to the structure of the observed learning networks.ResultsData was available from a complete cohort of 10 students on placement in a network of 69 members, thus providing information on 680 potential learning relations. Students engaged in similar ways in the domains of clinical knowledge, procedural skills, and professional development. Learning relations with academic supervisors were significantly more likely. Also students reported reciprocal learning relations with peers - i.e. they formed learning pairs. This effect was absent in learning networks about complex determinants of health (including socio-economic and cultural factors). Instead, local administrative staff were significantly more often the source of learning about the local contextual factors.ConclusionsUnderstanding the structure of student learning networks through social network analysis helps identify targeted strategies to enhance learning in community-based service-learning programs. Our findings suggest students recognised important learning from each other and from administrative personnel that is unrelated to the content of their placement. Based on this insight clinical educators could prepare students to become agentic learners, learning with each other and from sources outside their program.

Dataset Information

Learning and robustness to catch-and-release fishing in a shark social network.

Publications

Learning and robustness to catch-and-release fishing in a shark social network.

Similar Datasets

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