Tree-ring reconstructions of winter climate and circulation indices for the southwestern United States

A key to understanding the causes for climate variability lies in understanding how atmospheric circulation influences regional climate. The goal of this research is to investigate the long-term relationships between atmospheric circulation and winter climate in the southwestern United States. Patterns of atmospheric circulation are described by circulation indices, and winter climate is defined as number of days with precipitation and mean maximum temperature for the winter wet season, November through March. Records of both circulation indices and climate variables were reconstructed with tree-ring chronologies for the period 1702-1983. The years of the highest and lowest values of circulation indices and climate variables were compared in order to investigate possible spatial and temporal relationships between extremes in circulation and climate.

Present status and future scope of fisheries in the Andaman group of islands

The coastal area of approximately 2000 km and the water-bodies in between the Andaman and Nicobar islands are rich in fishery potential which range from 0.012-0.47 million tonnes. The fishery is dominated by catches of sardines, perches, carangids, mackerels, Leiognathus elasmobranchs, seerfish, mullets and tunas. About 2050 fishermen, with 1150 country craft, 113 mechanised boats and 1367 different kinds of nets and lines are engaged in active fishing in the island. Numerous bays, lagoons and creeks are available among the group of islands for mariculture activities. The mangroves of these islands provide feeding and nursery grounds for juveniles of penaeid prawns, crabs and finfishes.

Tree-Structured Stick Breaking Processes for Hierarchical Data

Many data are naturally modeled by an unobserved hierarchical structure. In this paper we propose a flexible nonparametric prior over unknown data hierarchies. The approach uses nested stick-breaking processes to allow for trees of unbounded width and depth, where data can live at any node and are infinitely exchangeable. One can view our model as providing infinite mixtures where the components have a dependency structure corresponding to an evolutionary diffusion down a tree. By using a stick-breaking approach, we can apply Markov chain Monte Carlo methods based on slice sampling to perform Bayesian inference and simulate from the posterior distribution on trees. We apply our method to hierarchical clustering of images and topic modeling of text data.