Reproductive Consequences of Nest Site Use in Fork-tailed Storm-Petrels in the Aleutian Islands, Alaska: Potential Lasting Effects of an Introduced Predator

We examined the reproductive consequences of differential nest site use in Fork-tailed Storm-Petrels (Oceanodroma furcata) in the Aleutian Islands, Alaska, where birds on islands where foxes were introduced nest in rocky substrate rather than in typical soil habitat. We investigated how physical and microclimatic nest site characteristics influenced storm-petrel breeding success 20 years after fox removal. We then examined whether those nest site characteristics that affected success were related to the amount of rock that composed the nest. In both years of our study, nest temperature had the strongest influence on chick survival and overall reproductive success, appearing in all the top models and alone explaining 14–35% of the variation in chick survival. The relationship between reproductive success and nest temperature was positive in both years, with higher survival in warmer nests. In turn, the best predictor of nest temperature was the amount of rock that composed the site. Rockier nests had colder average temperatures, which were driven by lower daily minimum temperatures, compared to nests with more soil. Thus, the rockiness of the nest site appeared to affect chick survival and overall reproductive success through its influence on nest temperature. This study suggests that the use of rocky nest sites, presumed to be a result of historic predation from introduced foxes, could decrease breeding success in this recovering population, and thus be a long-lasting effect of introduced predators.

Educational attainment in poor comprehenders

To date, only one study has investigated educational attainment in poor (reading) comprehenders, providing evidence of poor performance on national UK school tests at age 11 years relative to peers (Cain & Oakhill, 2006). In the present study, we adopted a longitudinal approach, tracking attainment on such tests from 11 years to the end of compulsory schooling in the UK (age 16 years). We aimed to investigate the proposal that educational weaknesses (defined as poor performance on national assessments) might become more pronounced over time, as the curriculum places increasing demands on reading comprehension. Participants comprised 15 poor comprehenders and 15 controls; groups were matched for chronological age, nonverbal reasoning ability and decoding skill. Children were identified at age 9 years using standardised measures of nonverbal reasoning, decoding and reading comprehension. These measures, along with a measure of oral vocabulary knowledge, were repeated at age 11 years. Data on educational attainment were collected from all participants (N = 30) at age 11 and from a subgroup (n = 21) at 16 years. Compared to controls, educational attainment in poor comprehenders was lower at ages 11 and 16 years, an effect that was significant at 11 years. When poor comprehenders were compared to national performance levels, they showed significantly lower performance at both time points. Low educational attainment was not evident for all poor comprehenders. Nonetheless, our findings point to a link between reading comprehension difficulties in mid to late childhood and poor educational outcomes at ages 11 and 16 years. At these ages, pupils in the UK are making key transitions: they move from primary to secondary schools at 11, and out of compulsory schooling at 16.

Where were the monsoon regions and arid zones in Asia prior to the Tibetan Plateau uplift?

The impact of the Tibetan Plateau uplift on the Asian monsoons and inland arid climates is an important but also controversial question in studies of paleoenvironmental change during the Cenozoic. In order to achieve a good understanding of the background for the formation of the Asian monsoons and arid environments, it is necessary to know the characteristics of the distribution of monsoon regions and arid zones in Asia before the plateau uplift. In this study, we discuss in detail the patterns of distribution of the Asian monsoon and arid regions before the plateau uplift on the basis of modeling results without topography from a global coupled atmosphere–ocean general circulation model, compare our results with previous simulation studies and available biogeological data, and review the uncertainties in the current knowledge. Based on what we know at the moment, tropical monsoon climates existed south of 20°N in South and Southeast Asia before the plateau uplift, while the East Asian monsoon was entirely absent in the extratropics. These tropical monsoons mainly resulted from the seasonal shifts of the Inter-Tropical Convergence Zone. There may have been a quasi-monsoon region in central-southern Siberia. Most of the arid regions in the Asian continent were limited to the latitudes of 20–40°N, corresponding to the range of the subtropical high pressure year-around. In the meantime, the present-day arid regions located in the relatively high latitudes in Central Asia were most likely absent before the plateau uplift. The main results from the above modeling analyses are qualitatively consistent with the available biogeological data. These results highlight the importance of the uplift of the Tibetan Plateau in the Cenozoic evolution of the Asian climate pattern of dry–wet conditions. Future studies should be focused on effects of the changes in land–sea distribution and atmospheric CO2 concentrations before and after the plateau uplift, and also on cross-comparisons between numerical simulations and geological evidence, so that a comprehensive understanding of the evolution of the Cenozoic paleoenvironments in Asia can be achieved.

Constructing a Structural Macroeconomic Model Using Multiple Techniques

This project constructs a structural model of the United States Economy. This task is tackled in two separate ways: first econometric methods and then using a neural network, both with a structure that mimics the structure of the U.S. economy. The structural model tracks the performance of U.S. GDP rather well in a dynamic simulation, with an average error of just over 1 percent. The neural network performed well, but suffered from some theoretical, as well as some implementation issues.