Results of the PERMANOVA Analyses.

<p>Permutational multivariate analyses of variance based on the Euclidean dissimilarity measure for presence-absence data. The tests were done using 9999 permutations under the reduced model.</p><p>Results of the PERMANOVA Analyses.</p

Generalized additive mixed model (GAMM) derived effects of engine power (kW), fishing depth, Period, and Country on the catch rates reported by fishers.

<p>Gray shaded area and dashed lines of upper and lower brackets indicate 2 standard errors above and below the estimates shown in solid lines. The relative density of data points is shown by the ‘rug’ on the x-axis.</p

Non-metric Multi Dimensional Scaling (nMDS) ordination comparing species abundance trends responses outputs across the different locations (Country).

<p>The position of each dot is defined by the assemblage of species recorded in each interview.</p

Map showing the ports where the interviews with the fishermen were carried out.

<p>SPAIN (GSA 6): 1: Port de la Selva; 2: Roses; 3: Palamos; 4: Blanes; 5: Arenys de Mar; 6: Mataro; 7: Barcelona; 8: Vilanova i la Geltrù; 9: Tarragona; 10: Cambrils; 11: L’Ametlla de Mar; 12: San Carles de la Rapita; ITALY (GSA 9 & 17): 13: Viareggio; 14: Livorno; 15: Elba Island; 16: Castiglione della Pescaia; 17: Porto Santo Stefano; 18: Porto Ercole; 19: Civitavecchia; 20: Fiumicino; 21: Ponza Island; 22: Civitanova Marche; GREECE (GSA 20 & 22) 23: Nea Michaniona; 24: Chalkis; 25: Peireas; 26: Patra. Country maps source: ©OpenStreetMap contributors. <a href="http://www.openstreetmap.org/copyright" target="_blank">http://www.openstreetmap.org/copyright</a></p

Median overall engine power (in kW) and fishing depth (in meters) of the vessels used by the fishermen interviewed over time.

<p>Upper and lower whiskers indicate 25–75% percentiles around the median.</p

The set of candidate models.

<p>GSA = Geographical Sub-Areas</p><p>s() is a smooth function represented using penalized regression splines [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119330#pone.0119330.ref025" target="_blank">25</a>].</p><p>Covariate “Fisherman” was estimated through penalized random effects (bs = “re”).</p><p>The set of candidate models.</p

Results of the Generalized Linear Mixed Models on ordinal outcomes in each study area.

<p>The null hypothesis tested is the absence of a time effect in the responses to questions on catches or sightings of large marine fauna in each Mediterranean case study. The full model (including time effect) was significant when the log-likelihood value was smaller than in the null model, and the coefficient of the time effect was significant at the 5% level (Z-test).</p

Results of the Generalized Linear Mixed Models on ordinal outcomes combining all cases studies.

<p>The null hypothesis tested is that the responses to questions on catches or sightings of large marine fauna in the combined Mediterranean case studies do not change over time. The full model (including time effect) was significant when the log-likelihood value was smaller than in the null model, and the coefficient of the time effect was significant at the 5% level (Z-test).</p

Survey interview data showing the number of fishers interviewed in each area, their age and their experience in the fishery.

<p>We show the age of the fishers at the time of the interview (2009) and the time when they started in the activity for each study area in terms of range and mean. Small-scale and trawl fishers of the Ligurian and Tyrrhenian Seas were combined for the statistical analysis.</p

Trends in catches of cartilaginous fish.

<p>Frequencies in the responses to questions on catches of cartilaginous fish (sharks and rays) in each Mediterranean case study, by time period.</p