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Sampling of Atlantic salmon Salmo salar from tanks and sea cages is size-biased
- Nilsson, Jonatan, Folkedal, Ole
- Aquaculture 2019 v.502 pp. 272-279
- Salmo salar, body size, cages, case studies, condition factor, fish, fish production, tanks
- Random samples of individual fish for the cause of estimating body size average and variation in fish groups is a widespread practice in scientific experiment as well as in fish production. Sample accuracy and precision naturally increases with sample size, but may very well depend on other factors such as fish size dependent success rate of capture method and spatial-behavioural size segregation. In 4 case studies with Atlantic salmon (Salmo salar) where the entire population was crowded and measured for length and weight, we show how the estimated mean weight and condition factor, and their deviation from the true population mean, evolve with number of sampled fish: 1) sampling of 3400 pre-smolts (77 g) netted by hand from a 5 m tank, 2) 466 post-smolts (711 g) netted by hand from a 5 m sea cage, 3) 5569 post-smolts (394 g) netted by hand from a 12 m sea cage, 4) the same fish as in 3, but 9 months later (3367 g, n = 5288) and netted out by using a crane mounted tarpaulin container. Sampling of cases 1, 3 and 4 took place over consecutive days. Cumulative mean, i.e. the mean for each new fish sampled, of weight and condition factor were calculated for each sampling day. To simulate a perfectly random sampling to compare with that observed, the order in which the individuals in the entire population were sampled were randomized, and cumulative means calculated in the same manner. With the randomized sampling order the cumulative mean values rapidly approached true population mean and remained at that level for both weight and condition factor in all days on all sampling events. In contrast, the cumulative mean weight and/or condition factor of the observed sampling order generally deviated from the true mean even after a large number of fish had been sampled, and the patterns in how cumulative mean values developed was inconsistent between days.