S. Charles et al., Annual spawning migrations in modelling brown trout population dynamics inside an arborescent river network, ECOL MODEL, 133(1-2), 2000, pp. 15-31
In the present paper, the annual spawning migration of adults is introduced
into a model, describing the Salmo trutta population dynamics in a hierarc
hically organized river network (four levels and 15 interconnected patches)
model based on previous work. The model describes simultaneously demograph
ic and migration processes taking place at different time scales: migration
s of individuals between patches at a fast time scale (e.g. the week or the
month), the annual spawning migration of adults and the demography at the
slow time scale of the year. The S. trutta population is sub-divided into t
hree age-classes (young of the year, juveniles, and adults). We used a Lesl
ie-type model, coupled with a migration matrix associated with the annual s
pawning process, and a second migration matrix associated with fast movemen
ts of individuals between patches throughout the year. All demographic and
migratory parameters are constant, leading to a linear model governing 45 s
tate variables (15 patches x three age-classes). By taking advantage of the
two time scales and using aggregation techniques for the case of discrete
time models, the complete model was approximated by a reduced one, with onl
y three global variables tone per age-class) evolving at the slow time scal
e. Demographic indices were calculated for the population, and a sensibilit
y analysis was performed to detect which parameters influence the most mode
l predictions. We also quantified how modifications of the river network st
ructure, by channels (change in connections between patches) or dams (patch
deletion), influence the global population dynamics. We checked that the s
trategy of annual spawning migrations is actually beneficial for the popula
tion (the asymptotic population growth rate is increased), and that dams ma
y have a more detrimental effect on the whole population dynamics than chan
nelling. (C) 2000 Elsevier Science B.V. All rights reserved.