Vitamin C: Effects of exercise and requirements with training

Ascorbic acid or vitamin C is involved in a number of biochemical pathways that are important to exercise metabolism and the health of exercising individuals. This review reports the results of studies investigating the requirement for vitamin C with exercise on the basis of dietary vitamin C intakes, the response to supplementation and alterations in plasma, serum, and leukocyte ascorbic acid concentration following both acute exercise and regular training. The possible physiological significance of changes in ascorbic acid with exercise is also addressed. Exercise generally causes a transient increase in circulating ascorbic acid in the hours following exercise, but a decline below pre-exercise levels occurs in the days after prolonged exercise. These changes could be associated with increased exercise-induced oxidative stress. On the basis of alterations in the concentration of ascorbic acid within the blood, it remains unclear if regular exercise increases the metabolism of vitamin C. However, the similar dietary intakes and responses to supplementation between athletes and nonathletes suggest that regular exercise does not increase the requirement for vitamin C in athletes. Two novel hypotheses are put forward to explain recent findings of attenuated levels of cortisol postexercise following supplementation with high doses of vitamin C.

On measuring quality of a probabilistic commodity forecast for a system that incorporates seasonal climate forecasts

Regional commodity forecasts are being used increasingly in agricultural industries to enhance their risk management and decision-making processes. These commodity forecasts are probabilistic in nature and are often integrated with a seasonal climate forecast system. The climate forecast system is based on a subset of analogue years drawn from the full climatological distribution. In this study we sought to measure forecast quality for such an integrated system. We investigated the quality of a commodity (i.e. wheat and sugar) forecast based on a subset of analogue years in relation to a standard reference forecast based on the full climatological set. We derived three key dimensions of forecast quality for such probabilistic forecasts: reliability, distribution shift, and change in dispersion. A measure of reliability was required to ensure no bias in the forecast distribution. This was assessed via the slope of the reliability plot, which was derived from examination of probability levels of forecasts and associated frequencies of realizations. The other two dimensions related to changes in features of the forecast distribution relative to the reference distribution. The relationship of 13 published accuracy/skill measures to these dimensions of forecast quality was assessed using principal component analysis in case studies of commodity forecasting using seasonal climate forecasting for the wheat and sugar industries in Australia. There were two orthogonal dimensions of forecast quality: one associated with distribution shift relative to the reference distribution and the other associated with relative distribution dispersion. Although the conventional quality measures aligned with these dimensions, none measured both adequately. We conclude that a multi-dimensional approach to assessment of forecast quality is required and that simple measures of reliability, distribution shift, and change in dispersion provide a means for such assessment. The analysis presented was also relevant to measuring quality of probabilistic seasonal climate forecasting systems. The importance of retaining a focus on the probabilistic nature of the forecast and avoiding simplifying, but erroneous, distortions was discussed in relation to applying this new forecast quality assessment paradigm to seasonal climate forecasts. Copyright (K) 2003 Royal Meteorological Society.