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Total lengths (LT) of 50 free‐swimming fish in a tank, silver carp Hypophthalmichthys molitrix and rainbow trout Oncorhynchus mykiss, were measured using a DIDSON (Dual‐frequency IDentification SONar) camera. Using Sound Metrics software, multiple measurements of each fish (LT, side aspect angle and distance from the camera) at different times were analysed by two experienced operators while a subset of data was analysed by two inexperienced operators. The main result showed high variability in intra‐fish LT measurements. The number of measurements required to minimise errors and to obtain robust fish measurements (true LT ± 3 cm) was estimated by a bootstrap method. Three to five measurements per fish were recommended for fish surveys in rivers. In this experimental study, aiming to reproduce river conditions, no evidence of fish position (side aspect angle and distance from the camera) effect was detected, but an operator effect (partially explained by training) was observed. General linear mixed models also showed that lengths of the smallest fish (LT < 57 cm) were overestimated and lengths of the largest fish (LT > 57 cm) were underestimated in comparison with their true lengths. In conclusion, we highlight that this technology, like any monitoring methods, returns imperfect observations. We advise DIDSON users to ensure that measurements are carried out correctly in order to draw accurate conclusion from this new technology.

A mathematical model representing the long‐term change in a trout population under different river management scenarios is presented. It describes the structure of a population broken down into age classes based on the Leslie matrix; if the population structure for any given month is known, the model should be able to estimate that of the following month. The passage from one month to the next takes into account various relevant factors: survival rate of individuals in the different age classes; fertility rate of females; linear and weighted growth rates; displacement linked to habitat fluctuations using weighted usable area (WUA) values. The model was applied to two French rivers. Regular monitoring of trout populations on the River Kernec enabled comparison of the response of the model with no displacement, with actual variations in fish stocks on the first river. In addition, the knowledge of WUA chronologies on the River Echez made it possible to carry out initial simulations of the response of a fish population to different river management scenarios at the second site.

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A dynamic population model was developed to study the impact of biotic and abiotic environmental factors on changes in trout populations. The model is based on the Leslie Matrix and simulates population change by age class in terms of biological parameters (i.e. fish survival, fertility, growth rates), which are dependent on environmental conditions. Changes in physical habitat, expressed as Weighted Usable Area, cause displacement of fish and increased mortality. Calculations were made at 1-month intervals to account for the effect of climatic variations on the population.The model was used to analyze the dynamics of two trout populations, quite different in terms of their biological characteristics: one in Lower Normandy in the Oir watershed and the other in the Pyrenees Mountains in the Neste d'Oueil watershed. Application of the model to those populations revealed two types of stabilizing mechanisms. The first was a capacity for population restoration, which is well-represented by the model through the phenomenon of density-dependent mortality in the first months of life. The second was adjustment of the adult population to the carrying capacity of the environment.The two applications demonstrate the utility of this type of model for understanding and simulating the dynamics of different cohorts of a population. Coupling habitat models and dynamic population models facilitates the identification of key periods during which carrying capacity -related to the hydrology -becomes a limiting factor for fish. This brings new perspectives to water management and may facilitate analysis of instream flow requirements related to water development projects, such as hydropower plants.