2019
DOI: 10.1016/j.marpol.2019.103665
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Public support for conservation may decay with increasing residence time in suboptimal marine protected areas

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Cited by 11 publications
(4 citation statements)
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“…Sighting frequencies increased from 2015 onward, which may be a consequence of increased tourism in the archipelago or the more frequent use of underwater cameras and enhanced awareness of citizen science. In the last decade, the FNA has seen a vast increase in the number of tourist and residents (Afonso et al 2019;Cristiano et al 2020), in conjunction with a large tourism ecological footprint (Feitosa and Gómez 2013;Lopes et al 2017). Potential negative impacts of tourism include harassment of marine animals, eutrophication, marine litter increase, light/sound pollution, introduction of exotic species, erosion and sediment loading on coral reefs (Feitosa and Gómez 2013;Canteiro et al 2018).…”
Section: Discussionmentioning
confidence: 99%
“…Sighting frequencies increased from 2015 onward, which may be a consequence of increased tourism in the archipelago or the more frequent use of underwater cameras and enhanced awareness of citizen science. In the last decade, the FNA has seen a vast increase in the number of tourist and residents (Afonso et al 2019;Cristiano et al 2020), in conjunction with a large tourism ecological footprint (Feitosa and Gómez 2013;Lopes et al 2017). Potential negative impacts of tourism include harassment of marine animals, eutrophication, marine litter increase, light/sound pollution, introduction of exotic species, erosion and sediment loading on coral reefs (Feitosa and Gómez 2013;Canteiro et al 2018).…”
Section: Discussionmentioning
confidence: 99%
“…Following Afonso et al (2019), age data were binned into 3 age classes, i.e., <30, 30-44, and >44 years old for categorical analysis, but age was also interpreted as a continuous variable. Regarding socioenvironmental predictors, responses to multiple choice, non-Likert questions were coded following an ordinal scale, normalized by the number of available choices in each question, and averaged to derive an overall score for each respondent concerning his/her affinity for nature ("High, " "Medium, " and "Low"), feelings/prejudice about sharks ("Positive, " "Neutral, " and "Negative"), and specific knowledge about sharks ("High, " "Medium, " and "Low").…”
Section: Statistical Analysesmentioning
confidence: 99%
“…OLR models incorporated Likert knowledge and perception data as response variables and all the aforementioned descriptors as candidate predictor variables, with knowledge and perception responses being modeled separately. The Likert data were weighted as in Afonso et al (2019) in order to penalize more complex assertions for which respondents would be more likely to reply randomly (Supplementary Table 1). A stepwise forward selection procedure based on the Akaike Information Criterion (AIC) was used for model building.…”
Section: Statistical Analysesmentioning
confidence: 99%
“…Due to the unique characteristic of coastal and marine social-ecological systems (CM-SESs) [21], the shery sector is prone to stakeholder con icts (both institutional and individual) which can hamper conservation efforts at local scales [22,23]. Socioeconomic factors (e.g., per capita income, wealth, alternate livelihoods), culture, and ecology (e.g., foraging behaviour of the target species) shape the perceptions and attitudes of shers towards wildlife conservation [24][25][26].…”
Section: Introductionmentioning
confidence: 99%