Functional models for growth and food consumption of Atlantic salmon parr, Salmo salar, from a Norwegian river

Abstract

1. The chief objectives were to analyse and model experimental data for maximum growth and food consumption of Atlantic salmon parr (Salmo salar) collected from a cold glacier fed river in western Norway. The growth and feeding models were also applied to groups of Atlantic salmon growing and feeding at rates below the maximum. The growth models were validated by comparing their predictions with observed growth in the river supplying the experimental fish. 2. Two different models were fitted, one originally developed for British salmon and the other based on a model for bacterial growth. Both gave estimates for optimum temperature for growth at 18–19 °C, somewhat higher than for Atlantic salmon from Britain. Higher optimal temperature for growth in salmon from a cold Norwegian river than from British rivers does not concur with predictions from the thermal adaptation hypothesis. 3. Model parameter estimates differed among growth groups in that the lower critical temperature for growth increased from fast to slow growing individuals. In contrast to findings for brown trout (Salmo trutta), the optimum temperature for growth did not decrease with decreasing levels of food consumption. 4. A new and simple model showed that food consumption (expressed in energy terms) peaked at 19.5–19.8 °C, which is similar to the optimal temperature for growth. Feeding began at a temperature 1.5 °C below the lower temperature for growth and ended about 1 °C above the maximum temperature for growth. Model parameter estimates for consumption differed among growth groups in a manner similar to the growth models. Maximum consumption was lower for Atlantic salmon than for brown trout, except at temperatures above 18 °C. 5. By combining the growth and food consumption models, growth efficiency was estimated and reached a maximum at about 14 °C for fast growing individuals, increasing to nearly 17 °C for slow growing ones, although it was lower overall for the latter group. Efficiency also declined with increasing fish size. Growth efficiency was generally higher for Atlantic salmon than for brown trout, particularly at high temperature.

The influence of hydroelectric power generation on the body composition of juvenile Atlantic salmon

“…Winter constitutes a major part of the year in northern streams and rivers. For example in the subartic river Altaelva, the water temperature is below the limit for normal summer growth (5-68C: Forseth et al, 2001) for about 245 days per year. In both the rivers Altaelva and Stjørdalselva a marked decline has been detected in juvenile salmon densities in the areas most heavily affected by regulation (Naesje et al, 1998, Arnekleiv et al, 2000Finstad et al, 2004a,b).…”

Natal movement in juvenile Atlantic salmon: a body size‐dependent strategy?

“…As for the stream-channel experiments, median dates of emergence of YOY from the nests were estimated based on temperatures experienced by the eggs in the hatchery combined with recorded stream temperatures (Crisp 1981(Crisp , 1988. Daily mean temperatures experienced following predicted emergence time were then used to calculate the predicted maximum body mass at the time of sampling (assuming a common starting mass value of 0.15 g), based on the model of fast growing salmon (Forseth et al 2001):…”

“…The constants b, d, g and c are given as 0.31, 0.530, 0.208 and 4.72, respectively, whereas the lower (T L ) and upper (T U ) temperatures for growth are given as 6.0 and 24.5°C (Forseth et al 2001). Using this model, values for M t were iterated in a stepwise fashion for each population and for each day t of the growth period.…”

Growth-rate variation in brown trout in small neighbouring streams: evidence for density-dependence?

“…To estimate the predicted maximum growth rate in the same period, estimated expected mass after time t was first estimated using a modified, five-parameter version of the growth model (Forseth et al, 2001;Ratkowsky et al, 1983):…”