Top-down versus bottom-up and the Ruritanian bean bug

In a recent article, Hunter uses the late George Varley and George Gradwell’s long-term data on the winter moth (Operophtera brumata) and green tortrix (Tortrix viridana) populations to propose a method of quantifying the relative importance of top-down effects (because of natural enemies) and bottom-up effects (because of resource competition) in influencing population dynamics. We believe this approach is deeply flawed. Using Varley and Gradwell’s winter moth study, we show that the problems with Hunter’s analysis lie in his misinterpretation of the population dynamics and his inappropriate use of statistical techniques. We also emphasize the importance of distinguishing clearly between two quite different things: firstly, top-down and bottom-up regulation of populations and secondly, the much simpler task of categorizing factors affecting changes in population density as either top-down or bottom-up processes.

New trends in natural language processing: statistical natural language processing.

The field of natural language processing (NLP) has seen a dramatic shift in both research direction and methodology in the past several years. In the past, most work in computational linguistics tended to focus on purely symbolic methods. Recently, more and more work is shifting toward hybrid methods that combine new empirical corpus-based methods, including the use of probabilistic and information-theoretic techniques, with traditional symbolic methods. This work is made possible by the recent availability of linguistic databases that add rich linguistic annotation to corpora of natural language text. Already, these methods have led to a dramatic improvement in the performance of a variety of NLP systems with similar improvement likely in the coming years. This paper focuses on these trends, surveying in particular three areas of recent progress: part-of-speech tagging, stochastic parsing, and lexical semantics.