Is there a link between the type of habitat and the patterns of abundance of holothurians in shallow rocky reefs?

[EN] The presence of a mosaic of habitats, largely determined by sea urchin grazing, across shallow rocky reefs may potentially influence in differences in the distribution patterns of invertebrates. The aim of this paper was to assess, using a correlative approach, whether the type of habitat influences the abundance patterns of holothurians in the eastern Atlantic. We hypothesized that abundances of large (> 10 cm) holothurians varied among four types of habitat (3 vegetated habitats with low abundances of the sea urchin D. antillarum versus ?barrens? with hyperabundances of sea urchins), and that these differences were consistent at a hierarchy of spatial scales, including two islands and several replicated sites within each type of habitat and island. Three species of large holothurians were found, accounting for a total of 300 specimens. We found remarkable differences in abundances of holothurians between the ?barrens? and the three vegetated habitats. This pattern was strongest for the numerically dominant species, Holothuria sanctorii. Total abundances of holothurians were between 5 ? 46 times more abundant in ?barrens? compared with the vegetated habitats. Inter-habitat differences were species-specific with some inconsistent patterns from one island to the other. The total abundances of holothurians tended to increase with the abundance of sea urchins within ?barrens?. Our study suggests that there may be a link, at least for the dominant species Holothuria sanctorii, between the distribution and abundances of large holothurians and the habitat across shallow-waters of the eastern Atlantic.

A comparison of face and facial feature detectors based on the viola-jones general object detection framework

[EN]The human face provides useful information during interaction; therefore, any system integrating Vision- BasedHuman Computer Interaction requires fast and reliable face and facial feature detection. Different approaches have focused on this ability but only open source implementations have been extensively used by researchers. A good example is the Viola–Jones object detection framework that particularly in the context of facial processing has been frequently used.