University of Georgia

About: University of Georgia is a education organization based out in Athens, Georgia, United States. It is known for research contribution in the topics: Population & Gene. The organization has 41934 authors who have published 93622 publications receiving 3713212 citations. The organization is also known as: UGA & Franklin College.

Complex working memory span tasks and higher-order cognition: A latent-variable analysis of the relationship between processing and storage

Abstract: Complex span tasks, assumed by many to measure an individual’s working memory capacity, are predictive of several aspects of higher-order cognition. However, the underlying cause of the relationships between ‘‘processing-and-storage’’ tasks and cognitive abilities is still hotly debated nearly 30 years after the tasks were first introduced. The current study utilised latent constructs across verbal, numerical, and spatial content domains to examine a number of questions regarding the predictive power of complex span tasks. In particular, the relations among processing time, processing accuracy, and storage accuracy from the complex span tasks were examined, in combination with their respective relationships with fluid intelligence. The results point to a complicated pattern of unique and shared variance among the constructs. Implications for various theories of working memory are discussed.

Action Research: Rethinking Lewin

Abstract: Fifty years after Kurt Lewin invented the idea of action research, action research remains an umbrella term for a host of activities intended to foster change on the group, organizational, and even...

Accuracy of the AVHRR vegetation index as a predictor of biomass, primary productivity and net CO2 flux

Abstract: The Normalized Difference Vegetation Index (NDVI) or ‘greenness index’, based on the Advanced Very High Resolution Radiometer (AVHRR) aboard the NOAA-7 satellite, has been widely interpreted as a measure of regional to global vegetation patterns. This study provides the first rigorous, quantitative evaluation of global relationships between the NDVI and geographically representative vegetation data-bases, including field metabolic measurements and carbon-balance results from global simulation models. Geographic reliability of the NDVI is judged by comparing NDVI values for different surface types with a general global trend and by statistical analysis of relationships to biomass amounts, net and gross primary productivity, and actual evapotranspiration. NDVI data appear to be relatively reliable predictors of primary productivity except in areas of complex terrain, for seasonal values at high latitudes, and in extreme deserts. The strength of the NDVI-productivity relationship seems comparable to that of earlier climate-based productivity models. Little consistent relationship was found, across different vegetation types, between NDVI and biomass amounts or net biospheric CO2 flux.