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Whale sharks, Rhincodon typus, are often perceived as solitary behemoths that live and feed in the open ocean. To the contrary, evidence is accumulating that they are gregarious and form seasonal aggregations in some coastal waters. One such aggregation occurs annually north of Cabo Catoche, off Isla Holbox on the Yucatán Peninsula of Mexico. Here we report a second, much denser aggregation of whale sharks (dubbed “the Afuera”) that occurs east of the tip of the Yucatán Peninsula in the Caribbean Sea. The 2009 Afuera event comprised the largest aggregation of whale sharks ever reported, with up to 420 whale sharks observed in a single aerial survey, all gathered in an elliptical patch of ocean approximately 18 km2. Plankton studies indicated that the sharks were feeding on dense homogenous patches of fish eggs, which DNA barcoding analysis identified as belonging to little tunny, Euthynnus alletteratus. This contrasts with the annual Cabo Catoche aggregation nearby, where prey consists mostly of copepods and sergestid shrimp. Increased sightings at the Afuera coincide with decreased sightings at Cabo Catoche, and both groups have the same sex ratio, implying that the same animals are likely involved in both aggregations; tagging data support this idea. With two whale shark aggregation areas, high coastal productivity and a previously-unknown scombrid spawning ground, the northeastern Yucatán marine region is a critical habitat that deserves more concerted conservation efforts.

What are the greatest sizes that the largest marine megafauna obtain? This is a simple question with a difficult and complex answer. Many of the largest-sized species occur in the world’s oceans. For many of these, rarity, remoteness, and quite simply the logistics of measuring these giants has made obtaining accurate size measurements difficult. Inaccurate reports of maximum sizes run rampant through the scientific literature and popular media. Moreover, how intraspecific variation in the body sizes of these animals relates to sex, population structure, the environment, and interactions with humans remains underappreciated. Here, we review and analyze body size for 25 ocean giants ranging across the animal kingdom. For each taxon we document body size for the largest known marine species of several clades. We also analyze intraspecific variation and identify the largest known individuals for each species. Where data allows, we analyze spatial and temporal intraspecific size variation. We also provide allometric scaling equations between different size measurements as resources to other researchers. In some cases, the lack of data prevents us from fully examining these topics and instead we specifically highlight these deficiencies and the barriers that exist for data collection. Overall, we found considerable variability in intraspecific size distributions from strongly left- to strongly right-skewed. We provide several allometric equations that allow for estimation of total lengths and weights from more easily obtained measurements. In several cases, we also quantify considerable geographic variation and decreases in size likely attributed to humans.

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Fig. 1. User interface of OnSet. The list of sets is on the right (the orange bar indicates the number of elements in the set). Each set is represented as a rectangular region with the set elements being smaller interior rectangles. This view shows two individual sets (one is dimmed) on the left and two compositions of individual sets on the right.Abstract-Visualizing sets to reveal relationships between constituent elements is a complex representational problem. Recent research presents several automated placement and grouping techniques to highlight connections between set elements. However, these techniques do not scale well for sets with cardinality greater than one hundred elements. We present OnSet, an interactive, scalable visualization technique for representing large-scale binary set data. The visualization technique defines a single, combined domain of elements for all sets, and models each set by the elements that it both contains and does not contain. OnSet employs direct manipulation interaction and visual highlighting to support easy identification of commonalities and differences as well as membership patterns across different sets of elements. We present case studies to illustrate how the technique can be successfully applied across different domains such as bio-chemical metabolomics and task and event scheduling.