Factors regulating brown trout populations in two French rivers: application of a dynamic population model
Article first published online: 28 SEP 2001
Copyright © 2001 John Wiley & Sons, Ltd.
Regulated Rivers: Research & Management
Special Issue: Eighth International Symposium on Regulated Streams
Volume 17, Issue 4-5, pages 557–569, July - October 2001
How to Cite
Gouraud, V., Baglinière, J.L., Baran, P., Sabaton, C., Lim, P. and Ombredane, D. (2001), Factors regulating brown trout populations in two French rivers: application of a dynamic population model. Regul. Rivers: Res. Mgmt., 17: 557–569. doi: 10.1002/rrr.655
- Issue published online: 28 SEP 2001
- Article first published online: 28 SEP 2001
- Manuscript Accepted: 24 APR 2001
- Manuscript Revised: 6 FEB 2001
- Manuscript Received: 1 AUG 2000
- Leslie Matrix;
- population dynamics;
- Salmo trutta L.
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. Copyright © 2001 John Wiley & Sons, Ltd.