Children who experienced autism, mental retardation, and language disorders; and, children in a clinical control group were shown photographs of human female, orangutan, and canine (boxer) faces expressing happiness, sadness, anger, surprise and a neutral expression. For each species of faces, children were asked to identify the happy, sad, angry, or surprised expressions. In Experiment 1, error patterns suggested that children who experienced autism were attending to features of the lower face when making judgements about emotional expressions. Experiment 2 supported this impression. When recognizing facial emotion, children without autism performed better when viewing the full face, compared to the upper and lower face alone. Children with autism performed no better when viewing the full face than they did when viewing partial faces; and, performed no better than chance when viewing the upper face alone. The results are discussed with respect to differences in the manner that children with and without autism process social information communicated by the face.
Jellyfish blooms are important events controlling plankton dynamics in coastal waters worldwide, yet factors that influence bloom development are not well understood. We used the scyphomedusa Chrysaora quinquecirrha as a model to examine physical factors that control jellyfish populations and to develop an ecological forecasting system. Over 700 in situ observations collected from Chesapeake Bay and its tributaries during 1987-2000 were used to develop habitat models that predict the probability of occurrence and the likely concentration of medusae as a function of seasurface temperature and salinity. Medusae were found within a relatively narrow range of temperature (26 to 30°C) and salinity (10 to 16). Regression analyses reveal that a combination of temperature and salinity is a significant predictor of medusa occurrence. Assessments of the predictive performance of these models using medusae and environmental data collected at independent survey sites (n = 354) indicated that model-predicted medusa occurrence and concentration correspond well with observations. Our models can be forced with near-real time and retrospective estimates of temperature and salinity to generate probability of occurrence maps of C. quinquecirrha medusa presence and abundance in order to better understand how this top predator varies in space and time, and how this species could potentially affect energy flow through the Chesapeake Bay system.
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