Different expressions of trypsin and chymotrypsin in relation to growth in Atlantic salmon (Salmo salar L.)

The expressions of trypsin and chymotrypsin in the pyloric caeca of Atlantic salmon (Salmo salar L.) were studied in three experiments. Two internal (trypsin phenotypes, life stages) and three common external factors (starvation, feeding, temperatures) influencing growth rates were varied. Growth was stimulated by increased temperature and higher feeding rate, and it was depressed during starvation. The interaction between trypsin phenotype and start-feeding temperature affected specific activity of trypsin, but not of chymotrypsin. Trypsin specific activity and the activity ratio of trypsin to chymotrypsin (T/C ratio) increased when growth was promoted. Chymotrypsin specific activity, on the other hand, increased when there was a reduction in growth rate whereas fish with higher growth had higher chymotrypsin specific activity resulting in lower T/C ratio value. During a rapid growth phase, trypsin specific activity did not correlate with chymotrypsin specific activity. On the other hand, a relationship between specific activities of trypsin and chymotrypsin could be observed when growth declined, such as during food deprivation. Trypsin is the sensitive key protease under conditions favouring growth and genetically and environmentally affected, while chymotrypsin plays a major role when growth is limited or depressed. Trypsin specific activity and the T/C ratio value are shown to be important factors in the digestion process affecting growth rate, and could be applicable as indicators for growth studies of fish in captive cultures and in the wild, especially when food consumption rate cannot be measured

Life in the fast lane: Revisiting the fast growth—High survival paradigm during the early life stages of fishes

Early life survival is critical to successful replenishment of fish populations, and hypotheses developed under the Growth-Survival Paradigm (GSP) have guided investigations of controlling processes. The GSP postulates that recruitment depends on growth and mortality rates during early life stages, as well as their duration, after which the mortality declines substantially. The GSP predicts a shift in the frequency distribution of growth histories with age towards faster growth rates relative to the initial population because slow-growing individuals are subject to high mortality (via starvation and predation). However, mortality data compiled from 387 cases published in 153 studies (1971–2022) showed that the GSP was only supported in 56% of cases. Selection against slow growth occurred in two-thirds of field studies, leaving a non-negligible fraction of cases showing either an absence of or inverse growth-selective survival, suggesting the growth-survival relationship is more complex than currently considered within the GSP framework. Stochastic simulations allowed us to assess the influence of key intrinsic and extrinsic factors on the characteristics of surviving larvae and identify knowledge gaps on the drivers of variability in growth-selective survival. We suggest caution when interpreting patterns of growth selection because changes in variance and autocorrelation of individual growth rates among cohorts can invalidate fundamental GSP assumptions. We argue that breakthroughs in recruitment research require a comprehensive, population-specific characterization of the role of predation and intrinsic factors in driving variability in the distribution and autocorrelation of larval growth rates, and of the life stage corresponding to the endpoint of pre-recruited life. -- Keywords : critical period ; growth-mortality ; individual characteristics ; larval physiology ; predation ; recruitment endpoint

Climate Change and Small Pelagic Fish.

Editeurs scientifique

Outlier Events of Solar Forecasts for Regional Power Grid in Japan Using JMA Mesoscale Model

To realize the safety control of electric power systems under high penetration of photovoltaic power systems, accurate global horizontal irradiance (GHI) forecasts using numerical weather prediction models (NWP) are becoming increasingly important. The objective of this study is to understand meteorological characteristics pertaining to large errors (i.e., outlier events) of GHI day-ahead forecasts obtained from the Japan Meteorological Agency, for nine electric power areas during four years from 2014 to 2017. Under outlier events in GHI day-ahead forecasts, several sea-level pressure (SLP) patterns were found in 80 events during the four years; (a) a western edge of anticyclone over the Pacific Ocean (frequency per 80 outlier events; 48.8%), (b) stationary fronts (20.0%), (c) a synoptic-scale cyclone (18.8%), and (d) typhoons (tropical cyclones) (8.8%) around the Japanese islands. In this study, the four case studies of the worst outlier events were performed. A remarkable SLP pattern was the case of the western edge of anticyclone over the Pacific Ocean around Japan. The comparison between regionally integrated GHI day-ahead forecast errors and cloudiness forecasts suggests that the issue of accuracy of cloud forecasts in high- and mid-levels troposphere in NWPs will remain in the future