The South China Sea: analyzing fisheries catch data in an ecosystem context

The South China Sea is an important fishing area with an annual harvest of some 5 million tonnes, or 10% of the catches jointly taken by the developing nations of the world. Details are given of a model of the area describing fisheries catches and biological interactions. The area, viewed as a large marine ecosystem, was divided into 10 subsystems; each subsystem was then linked with adjacent subsystems by predatory links, and detritus flows. An analysis was then made of catch statistics for each of the subsystems. It is believed that if all systems could be harvested at around the highest efficiency, an additional 5-6 million tonnes could be taken annually from the South China Sea; however, more refined analyses are needed to further investigate these possibilities. If linked with careful studies of the economic and human aspects of fishing, such analyses will provide guidelines for integrated fisheries management advice.

Context-dependent partitioning of motor learning in bimanual movements.

Human subjects easily adapt to single dynamic or visuomotor perturbations. In contrast, when two opposing dynamic or visuomotor perturbations are presented sequentially, interference is often observed. We examined the effect of bimanual movement context on interference between opposing perturbations using pairs of contexts, in which the relative direction of movement between the two arms was different across the pair. When each perturbation direction was associated with a different bimanual context, such as movement of the arms in the same direction versus movement in the opposite direction, interference was dramatically reduced. This occurred over a short period of training and was seen for both dynamic and visuomotor perturbations, suggesting a partitioning of motor learning for the different bimanual contexts. Further support for this was found in a series of transfer experiments. Having learned a single dynamic or visuomotor perturbation in one bimanual context, subjects showed incomplete transfer of this learning when the context changed, even though the perturbation remained the same. In addition, we examined a bimanual context in which one arm was moved passively and show that the reduction in interference requires active movement. The sensory consequences of movement are thus insufficient to allow opposing perturbations to be co-represented. Our results suggest different bimanual movement contexts engage at least partially separate representations of dynamics and kinematics in the motor system.

Regional context of the climate of H.J. Andrews Experimental Forest, Oregon

H.J. Andrews Experimental Forest is a 6400 ha forest of Douglas fir, western hemlock, and Pacific silver fir located in, and typical of, the central portion of the western slope of the Cascade mountain range of Oregon. The forest is one of 19 sites in the Long-Term Ecological Research (LTER) program sponsored by the National Science Foundation. ... Because of the scientific significance of Andrews Forest, it is important to investigate the temporal variability of annual and seasonal temperature and precipitation values at the site and identify past times of anomalous climatic conditions. It is also important to establish quantitatively the relationships between the climate of Andrews Forest and that of its surrounding area and, hence, place the climate of Andrews Forest into its regional context.

The estimation of stochastic context-free grammars using the Inside-Outside algorithm

Using an entropy argument, it is shown that stochastic context-free grammars (SCFG's) can model sources with hidden branching processes more efficiently than stochastic regular grammars (or equivalently HMM's). However, the automatic estimation of SCFG's using the Inside-Outside algorithm is limited in practice by its O(n3) complexity. In this paper, a novel pre-training algorithm is described which can give significant computational savings. Also, the need for controlling the way that non-terminals are allocated to hidden processes is discussed and a solution is presented in the form of a grammar minimization procedure. © 1990.

Applications of stochastic context-free grammars using the Inside-Outside algorithm

This paper describes two applications in speech recognition of the use of stochastic context-free grammars (SCFGs) trained automatically via the Inside-Outside Algorithm. First, SCFGs are used to model VQ encoded speech for isolated word recognition and are compared directly to HMMs used for the same task. It is shown that SCFGs can model this low-level VQ data accurately and that a regular grammar based pre-training algorithm is effective both for reducing training time and obtaining robust solutions. Second, an SCFG is inferred from a transcription of the speech used to train a phoneme-based recognizer in an attempt to model phonotactic constraints. When used as a language model, this SCFG gives improved performance over a comparable regular grammar or bigram. © 1991.

Voluntary guidelines for securing sustainable small-scale fisheries in the context of food security and poverty eradication: summary

The Voluntary Guidelines for Securing Sustainable Small-scale Fisheries in the Context of Food Security and Poverty Eradication (SSF Guidelines) were adopted by member countries of the Food and Agriculture Organization of the United Nations (FAO) and were officially approved as an international instrument in June 2014. What is very special about the SSF Guidelines is that it was created as a result of a very long history of the struggles of small-scale fishworkers around the world appealing for greater recognition of their status and their role in the fisheries sector of their countries. These Guidelines have 100 paragraphs which are distributed across 13 sections. This document is only a summation of the contents of the Guidelines. It was produced for ICSF by John Kurien, founder Member of ICSF, who has worked for the last four decades with small-scale fishing communities in many areas around the world, particularly in Kerala, India.