Future research directions on the "elusive" white shark

White sharks, Carcharodon carcharias, are often described as elusive, with little information available due to the logistical difficulties of studying large marine predators that make long-distance migrations across ocean basins. Increased understanding of aggregation patterns, combined with recent advances in technology have, however, facilitated a new breadth of studies revealing fresh insights into the biology and ecology of white sharks. Although we may no longer be able to refer to the white shark as a little-known, elusive species, there remain numerous key questions that warrant investigation and research focus. Although white sharks have separate populations, they seemingly share similar biological and ecological traits across their global distribution. Yet, white shark’s behavior and migratory patterns can widely differ, which makes formalizing similarities across its distribution challenging. Prioritization of research questions is important to maximize limited resources because white sharks are naturally low in abundance and play important regulatory roles in the ecosystem. Here, we consulted 43 white shark experts to identify these issues. The questions listed and developed here provide a global road map for future research on white sharks to advance progress toward key goals that are informed by the needs of the research community and resource managers

Global Spatial Risk Assessment of Sharks Under the Footprint of Fisheries

Effective ocean management and conservation of highly migratory species depends on resolving overlap between animal movements and distributions and fishing effort. Yet, this information is lacking at a global scale. Here we show, using a big-data approach combining satellite-tracked movements of pelagic sharks and global fishing fleets, that 24% of the mean monthly space used by sharks falls under the footprint of pelagic longline fisheries. Space use hotspots of commercially valuable sharks and of internationally protected species had the highest overlap with longlines (up to 76% and 64%, respectively) and were also associated with significant increases in fishing effort. We conclude that pelagic sharks have limited spatial refuge from current levels of high-seas fishing effort. Results demonstrate an urgent need for conservation and management measures at high-seas shark hotspots and highlight the potential of simultaneous satellite surveillance of megafauna and fishers as a tool for near-real time, dynamic management

The relationship between TP and increasing body size of <i>G</i>. <i>cuvier</i>.

<p>Stomach content calculated trophic position (TP_SCA) for each size class is indicated by the white box. The solid black line in each box represents the median, outliers are indicated by open circles. TP estimated using a scaled δ¹⁵N framework (TP_scaled) is indicated by blue circles and TP estimated using a standard additive trophic framework (TP_additive) is indicated by black circles. Vertical dashed black lines indicate the predetermined size classes of <i>G</i>. <i>cuvier</i> used in the stomach content analysis (<150 cm), medium (150–220 cm) and large (>220 cm).</p

Variance component analysis from linear mixed-model analysis for <i>G</i>. <i>cuvier</i> δ¹³C and δ¹⁵N for two tissue (muscle and liver) and three tissue (muscle, liver and skin) models.

<p>The between-individual component (BIC) represents the total intercept variance and the within-individual component (WIC) represents the residual variance. Total niche width (TNW) is the sum of the intercept and residual variances for δ¹³C and δ¹⁵N. Total BIC and total WIC are calculated by combining the intercept variances for δ¹³C and δ¹⁵N and then dividing by TNW. Proportion of WIC and BIC that explained TNW is in parentheses.</p

Stomach content composition of <i>G</i>. <i>cuvier</i> caught in the KwaZulu-Natal shark nets and drumlines, 1983–2014.

<p>Results are summarized for eight functional prey groups and presented by frequency of occurrence (%F), by mass (%M), by number (N%) and index of relative importance (%IRI). Totals represent number of non-empty stomachs (F), mass prey items (M, kg) and number of unique prey items recorded (N).</p

Metric multidimensional scaling (<i>m</i>MDS) ordinations of dietary samples with approximate 95% region estimates fitted to bootstrap averages for small (< 150 cm), medium (150–220 cm) and large (> 220 cm) <i>G</i>. <i>cuvier</i>.

<p>(a) Percentage frequency of occurrence (%F), (b) Percentage mass (%M), (c) Percentage number (%N) and (d) Percentage index of relative importance (%IRI). <i>R</i>, ANOSIM global <i>R</i> statistic and associated <i>p</i> value. Significant pairwise tests (with <i>p</i> value in brackets) are detailed in each figure.</p

Metric multidimensional scaling (<i>m</i>MDS) ordinations of size class 2 (medium) <i>G</i>. <i>cuvier</i> dietary samples with approximate 95% region estimates fitted to bootstrap averages for decades 1 (1983–1992), 2 (1993–2003) and 3 (2004–2014).

<p>(a) Percentage frequency of occurrence (%F), (b) Percentage mass (%M), (c) Percentage number (%N) and d) Percentage index of relative importance (%IRI). <i>R</i>, ANOSIM global <i>R</i> statistic and associated <i>p</i> value. Significant pairwise tests (with <i>p</i> value in brackets) are detailed in each figure.</p

Diet and trophic ecology of the tiger shark (<i>Galeocerdo cuvier</i>) from South African waters - Fig 7

<p>δ^<b>15</b><b>N (a and b) and</b> δ^<b>13</b><b>C (c and d) ontogenetic profiles for <i>G</i>. <i>cuvier</i> by sex (black circles represent males, grey circles represent females).</b> Linear and polynomial regression models (where appropriate) were fitted to both sexes. Grey bar depicts the predicted δ¹³C range of the KwaZulu-Natal (KZN) coastal habitat of <i>G</i>. <i>cuvier</i>.</p

Randomized cumulative prey curves derived from the stomach contents of <i>G</i>. <i>cuvier</i> caught in the KwaZulu-Natal shark nets and drumlines, 1983–2014.

<p>a) Small, b) medium, c) large size classes and d) all sharks combined. The order in which the stomachs were analysed was randomised 500 times and the means (solid lines) and 95% confidence levels (dashed lines) presented.</p