Figure 1.
Map of the littoral of Recife, northeastern Brazil, depicting the locations of a shallow alongshore reef (stripped blue ellipse off Boa Viagem) and both bottom longline (solid gray ellipses located seaward) and drumline (blank striped ellipses located shoreward) deployments in two nearshore fishing sites.
Table 1.
Selected predictive variables.
Table 2.
Summary of shark species.
Figure 2.
Size-structure of abundant sharks.
Absolute frequencies of 10-cm total length-classes, divided in male (gray) and female (blank) components, for a) blacknose sharks, b) nurse sharks, and c) tiger sharks caught off Recife, Brazil, between 2004 and 2011.
Figure 3.
Temporal variability in shark size.
Distribution of total lengths per quarter and per year for a) blacknose shark, b) nurse shark, and c) tiger shark. In each plot, box width is proportional to the square root of the number of individuals measured.
Figure 4.
Dynamics in blacknose shark length-frequency distribution.
Absolute frequencies of blacknose shark total lengths in 25-cm size classes across a) years, and b) quarters.
Figure 5.
Dynamics in nurse shark length-frequency distribution.
Absolute frequencies of nurse shark total lengths in 25-cm size classes across a) years, and b) quarters.
Figure 6.
Dynamics in tiger shark length-frequency distribution.
Absolute frequencies of tiger shark total lengths in 25-cm size classes across a) years, and b) quarters.
Figure 7.
Variation of the relative frequency of male (solid bars) and female (blank bars) a) blacknose sharks, b) nurse sharks, and c) tiger sharks, between quarters (left panels) and years (right panels). Numbers above bars correspond to the number of sharks caught in the respective period. Note that nurse sharks were not sexed before 2007.
Table 3.
Model-type comparisons.
Table 4.
Summary of correlation analyses to assess variable interdependencies.
Figure 8.
The SPT model for the blacknose shark.
Spatiotemporal zero-inflated generalized additive models (ZIGAM) of blacknose shark abundance off Recife, comprising the SPT1 model of the additive effects of a) year and b) month fitted with independent smooth functions, c) the SPT2 model of the interacting effects of year and month fitted with the same smooth function, and d) the spatial effects of the three sampling sites, namely Boa Viagem (BV) and Paiva (PA), both nearshore, and the middle continental shelf (CS). The horizontal lines, the nonlinear lines and the shaded area in a) and b) depict null effects, smooth functions and 95% confidence intervals, respectively. The solid and dashed lines in c) depict isolines of standardized partial residuals and 95% confidence intervals, respectively. The solid and dashed horizontal lines in d) depict effect coefficients and 95% confidence intervals, respectively.
Figure 9.
The ENV model for the blacknose shark.
Environmental ZIGAM of blacknose shark, Carcharhinus acronotus, abundance off Recife, depicting the smooth functions that measure the effects of sea surface temperature (top) and wind direction (bottom) on catch rates.
Table 5.
Summary of SPT models of shark abundance.
Table 6.
Summary of ENV models of shark abundance.
Figure 10.
The SPT model for the nurse shark.
Spatiotemporal ZIGAMs of nurse shark, Ginglymostoma cirratum, abundance off Recife, comprising the SPT1 model of the additive effects of a) year and b) month fitted with independent smooth functions, c) the SPT2 model of the interacting effects of year and month fitted with the same smooth function, and d) the spatial effects of the three sampling sites, namely Boa Viagem (BV) and Paiva (PA), both nearshore, and the middle continental shelf (CS).
Figure 11.
The ENV model for the nurse shark.
Environmental ZIGAM of nurse shark, Ginglymostoma cirratum, abundance off Recife, depicting the smooth function that measure the effect of visibility on catch rates.
Figure 12.
The SPT model for the tiger shark.
Spatiotemporal ZIGAMs of tiger shark, Galeocerdo cuvier, abundance off Recife, comprising the SPT1 model of the additive effects of a) year and b) month fitted with independent smooth functions, c) the SPT2 model of the interacting effects of year and month fitted with the same smooth function, and d) the spatial effects of the three sampling sites, namely Boa Viagem (BV) and Paiva (PA), both nearshore, and the middle continental shelf (CS).
Figure 13.
The ENV model for the tiger shark.
Environmental ZIGAM of tiger shark, Galeocerdo cuvier, abundance off Recife, depicting the smooth functions that measure the effects of tidal amplitude (top) and pluviosity (bottom) on catch rates.