Stock-recruitment relations controlled by feeding interactions alone

Stock-recruitment (S-R) relationships are the centrepiece of fisheries management aimed at achieving maximum sustainable yield (MSY). Here we consider the possibility that the density dependence evident in S-R relations is controlled by feeding interactions alone. We simulate a food-web model with dynamic representations of intra- and interspecific size structure and a linear relation between food intake and hatchling production of adults. Population sizes of individual stocks are modified by imposing additional mortality. The predominant functional forms and the steepness of resulting S-R relationships agree well with observations. We conclude that recruitment is plausibly regulated by feeding interactions alone.

Spatial statistics to estimate peat thickness using airborne radiometric data

Soil carbon stores are a major component of the annual returns required by EU governments to the Intergovernmental Panel on Climate Change. Peat has a high proportion of soil carbon due to the relatively high carbon density of peat and organic-rich soils. For this reason it has become increasingly important to measure and model soil carbon stores and changes in peat stocks to facilitate the management of carbon changes over time. The approach investigated in this research evaluates the use of airborne geophysical (radiometric) data to estimate peat thickness using the attenuation of bedrock geology radioactivity by superficial peat cover. Remotely sensed radiometric data are validated with ground peat depth measurements combined with non-invasive geophysical surveys. Two field-based case studies exemplify and validate the results. Variography and kriging are used to predict peat thickness from point measurements of peat depth and airborne radiometric data and provide an estimate of uncertainty in the predictions. Cokriging, by assessing the degree of spatial correlation between recent remote sensed geophysical monitoring and previous peat depth models, is used to examine changes in peat stocks over time. The significance of the coregionalisation is that the spatial cross correlation between the remote and ground based data can be used to update the model of peat depth. The result is that by integrating remotely sensed data with ground geophysics, the need is reduced for extensive ground-based monitoring and invasive peat depth measurements. The overall goal is to provide robust estimates of peat thickness to improve estimates of carbon stocks. The implications from the research have a broader significance that promotes a reduction in the need for damaging onsite peat thickness measurement and an increase in the use of remote sensed data for carbon stock estimations.

Trading Activity in Options and Stock Around Price-Sensitive News Announcements

This study investigates the trading activity in options and stock markets around informed events with extreme daily stock price movements. We find that informed agents are more likely to trade options prior to negative news and stocks ahead of positive news. We also show that optioned stocks overreact to the arrival of negative news, but react efficiently to positive news. However, the overreaction patterns are unique to the subsample of stocks with the lowest pre-event abnormal option/stock volume ratio (O/S). This finding suggests that the incremental benefit of option listing is related to the level of option trading activity, over and beyond the presence of an options market on the firm's stock. Finally, we find that the pre-event abnormal O/S is a better predictor of stock price patterns following a negative shock than is the pre-event O/S, implying that the former may contain more information about the future value of stocks than the latter.

Are early life factors considered when managing respiratory disease?:A British Thoracic Society survey of current practice

We hypothesised that early life events are not routinely considered by most respiratory specialists.

The cross-section of stock returns in an early stock market

Using a new dataset which contains monthly data on 1015 stocks traded on the London Stock Exchange between 1825 and 1870, we investigate the cross section of stock returns in this early capital market. Unique features of this market allow us to evaluate the veracity of several popular explanations of asset pricing behavior. Using portfolio analysis and Fama–MacBeth regressions, we find that stock characteristics such as beta, illiquidity, dividend yield, and past-year return performance are all positively correlated with stock returns. However, market capitalization and past-three-year return performance have no significant correlation with stock returns.