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. 2012;7(10):e47819.
doi: 10.1371/journal.pone.0047819. Epub 2012 Oct 29.

Eating or meeting? Cluster analysis reveals intricacies of white shark (Carcharodon carcharias) migration and offshore behavior

Salvador J Jorgensen  1 , Natalie S Arnoldi, Ethan E Estess, Taylor K Chapple, Martin Rückert, Scot D Anderson, Barbara A Block
Affiliations

Eating or meeting? Cluster analysis reveals intricacies of white shark (Carcharodon carcharias) migration and offshore behavior

Salvador J Jorgensen et al. PLoS One. 2012.

Abstract

Elucidating how mobile ocean predators utilize the pelagic environment is vital to understanding the dynamics of oceanic species and ecosystems. Pop-up archival transmitting (PAT) tags have emerged as an important tool to describe animal migrations in oceanic environments where direct observation is not feasible. Available PAT tag data, however, are for the most part limited to geographic position, swimming depth and environmental temperature, making effective behavioral observation challenging. However, novel analysis approaches have the potential to extend the interpretive power of these limited observations. Here we developed an approach based on clustering analysis of PAT daily time-at-depth histogram records to distinguish behavioral modes in white sharks (Carcharodon carcharias). We found four dominant and distinctive behavioral clusters matching previously described behavioral patterns, including two distinctive offshore diving modes. Once validated, we mapped behavior mode occurrence in space and time. Our results demonstrate spatial, temporal and sex-based structure in the diving behavior of white sharks in the northeastern Pacific previously unrecognized including behavioral and migratory patterns resembling those of species with lek mating systems. We discuss our findings, in combination with available life history and environmental data, and propose specific testable hypotheses to distinguish between mating and foraging in northeastern Pacific white sharks that can provide a framework for future work. Our methodology can be applied to similar datasets from other species to further define behaviors during unobservable phases.

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Conflict of interest statement

Competing Interests: SJJ is currently employed by the Monterey Bay Aquarium. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Figure 1
Figure 1. Dendrogram of white shark behavior, determined from clustering analysis of differences in diving patterns.
Each column represents a 24-hour depth histogram (n = 5571 days from 53 sharks) and is colored by fraction of time. Distinct vertical distribution patterning is evident in the grouping of days with similar depth distributions. The size of each cluster, is indicated by the number of days (n), and percent of total days (in parentheses). The density variable is expressed as a fraction of each day spent in depth bins defined along the y-axis.
Figure 2
Figure 2. Daily median white shark position estimates from 53 tracks, Each position estimate is colored according to behavioral cluster; cluster 1 (yellow; ‘ROD’), cluster 2 (purple; ‘Cluster 2’), cluster 3 (green; ‘Travel’), cluster 4 (magenta; ‘DVM’), cluster 5 (orange; ‘Coastal’).
The distinct diving behaviors, distinguished by each cluster, generally differed in the locations where they most commonly occurred. The ‘Coastal’ behavior occurred primarily along the North American coast, ‘ROD’ primarily at the ‘white shark Café’, while ‘DVM’ occurred throughout the offshore area (the Café, Hawaii, and in between) and ‘Travel’ connected North America and the offshore core areas (the Café and Hawaii).
Figure 3
Figure 3. Diel patterns of white shark diving behavior from archival records queried by cluster.
High-resolution time and depth data were corrected for local time and aggregated by cluster over a 24-hour period. The relative density of data (log scale) is shown on a gridded surface for the four dominant clusters ‘Coastal’ (A), ‘Travel’ (B), ‘ROD’ (C), and ‘DVM’ (D) representing 97.9% of data. The clusters differed not only by overall daily depth distribution, but also in the diel pattern of depth occupancy. Note that a faint signal of DVM dive pattern can be detected in the other clusters. This is likely because sharks switched between behaviors at arbitrary times of day while the data were divided in regular 24-hour bins, resulting in some ‘bleeding’ of the behavior across clusters.
Figure 4
Figure 4. White shark seasonal and spatial patterns corresponding to each behavioral mode for males and females.
The dotted lines represent the coast of California (red; near 122°W), the Café (green; near 135°W) and Hawaii (blue; near 156°W) respectively. All longitude estimates for the entire male (left panels) and female (right panels) dataset are shown in grey in the background with only the relevant data for each cluster and sex highlighted in black.
Figure 5
Figure 5. Differences in white shark behavior categorized as ‘ROD’ (rapid oscillatory diving) in the Café (a) and in Hawaii (b).
High-resolution time and depth data were corrected for local time and aggregated by cluster over a 24-hour period. The relative density of data (log scale) is shown on a gridded surface. Clustering analysis placed most ROD in the Café, but some occurred in Hawaii. However, the high vertical swimming speed characteristic of ROD in the Café was not present in Hawaii. While the overall depth distribution was similar there were clear differences apparent at time-scales below the cluster data bin size (24 hrs) including a strong daytime density band around 50 m in Hawaii. These differences illustrate that the ROD behavior in the Café is unique.
Figure 6
Figure 6. Spatial dependence of white shark ‘ROD’ (A) and ‘DVM’ (B) behavior in the Café.
The regression shows that for ‘ROD’ the fraction of time (days) white sharks were engaged in ‘ROD’ declined steadily and linearly as a function of distance from the center of the Café region. In contrast no clear spatial relationship was evident for ‘DVM’.
Figure 7
Figure 7. The fraction of time each month that male (A) and female (B) white sharks engaged in ‘ROD’ (black) and ‘DVM’ (grey) behavior.
The bars represent median values, while the error bars show the upper inter-quartile range among individuals.
See this image and copyright information in PMC

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