Is the grass greener on the other side? A comparison of management preferences between stalked barnacle harvesters across Europe: Survey data

Description

Survey data used in a perception study of stalked barnacle harvesters on the effectiveness of fisheries management practices in Spain, Portugal and France. Harvesters from the following six regions along the Atlantic Arc participated: Morbihan in Brittany (France), Asturias-East, Asturias-West and Galicia (Spain), the Reserva Natural das Berlengas (RNB; Portugal) and the Parque Natural do Sudoeste Alentejano e Costa Vicentina (PNSACV; Portugal). We administered 184 surveys from October 2019 to September 2020 and each region was treated as an independent population. The data includes: general demographic data (Region, Age, Gender, Level of Education, Main income source, Years of Experience); data of the perceived knowledge regarding management strategies (coded: k_name_of_strategy – using 0 = No; 1 = Yes: NA = No Answer); perception data of the effectiveness of the currently implemented management strategies in each region (coded: e_name_of_strategy – using Likert Scale with scores ranging from 1 = completely ineffective to 5 = very effective); data of the willingness for change of the currently implemented management (Yes, No, NA); and data of harvesters’ perceptions regarding the most important strategy to achieve sustainability in the fishery. Because the surveys were conducted both before and during the Covid-19 pandemic (the column Covid indicates whether the data was collected before or during the pandemic), we had to make adjustments in our data collection methods. We provided the following options for survey completion (see the Recollection_of_data column): by hand in a written format, online, or via an oral interview conducted with the assistance of a scientist per telephone. Results: In general, harvesters indicated a good understanding of the implemented strategies, however, some gaps were identified. Our results indicate that the majority of harvesters in the regions in Portugal and France were willing to make changes to current management strategies, reflecting their awareness of the need for improvement. In the fisheries with higher levels of governance and management success (Galicia and Asturias-West), this willingness was considerably smaller. Based on the AIC model selection analysis results, the model with the single variable region explained 83% of the cumulative model weight. The variable region was the best predictor of the trends in management strategy preferences, and presented a highly significant goodness-of-fit result (p<0.001), suggesting that regional differences play a significant role in shaping these preferences. No clear trend emerged regarding a single "optimal" management strategy preferred by harvesters across regions. Our findings emphasise the importance of tailoring management strategies to each region's specific practices, needs, and characteristics.

Steps to reproduce

For our analysis, we used the R computing software (R version 4.2.2). To examine whether changes in data collection due to lockdowns biased the data, we performed Kruskal-Wallis tests on data from the two regions in Asturias where surveys were conducted before and during the COVID-19 pandemic. To represent harvesters' knowledge of management strategies, we created a bar plot showing the percentage of answers per region, distinguishing between implemented and non-implemented strategies. The perceptions of the effectiveness of regionally implemented management strategies were presented in a graph using mean Likert scale values with their standard deviations. The strategies that did not exist in a certain region were left in blank (marked in grey in the data set). The willingness to make changes to current management was visualized using a relative frequency (%) plot. We developed multinomial logistic models to identify patterns influencing harvesters' perceptions of the most important management strategy for sustainable fisheries. To simplify the interpretation, we grouped the dependent variable (most important management strategy) into four categories: co-management, spatial restrictions, temporal restrictions, and output restrictions. For statistical accuracy, we only used data from surveys with complete information for the models. We assessed multi-collinearity using a Kendall rank correlation test and excluded gender due to high correlation with region. To determine the model that best described the association between the independent variables (region, age, main income source, educational level), with the dependent variable (most important management strategy), we employed the Akaike Information Criterion adjusted for small sample sizes (AICc; Cavanaugh and Neath, 2019). Subsequently, we conducted a Pearson's Chi-square goodness-of-fit test to assess the reliability of the chosen model. The most important management strategies to obtain a sustainable fishery were presented in form of a table with the percentage of responses indicating the importance of the strategies in each region.

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