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A large-scale approach can help detect general processes driving the dynamics of brown trout populations in extensive areas

Authors


C. Alonso, ETS Ingenieros de Montes, Universidad Politécnica de Madrid, 28040 Madrid, Spain. E-mail: carlos.alonso@upm.es

Abstract

Abstract –  Most studies on the population dynamics of stream-living salmonids have been conducted at the scale of a reach, a stream or a river basin. This can lead to overestimating the importance of local factors acting on a reduced scale compared to the more general factors that drive the dynamics of several populations. Two models were built on the basis of a data set from 60 sampling stations representing separated populations inhabiting a large heterogeneous area encompassing 18 years of quantifications. Our analyses showed the following: (i) Population growth rate (pgr) of a set of independent brown trout populations can be described by means of a single model; (ii) the youngest and the oldest year classes of these populations seem to be limited by the same constraints; (iii) there is a climatic control of the recruitment because of spring weather conditions, but also the abundance of oldest age class may be controlled by the climate, (iv) there is a nonlinear positive effect of winter North Atlantic Oscillation on pgr; (v) there is a 3-year lagged positive feedback tracing the upward trend of a stock-recruitment curve, and 1-year lagged negative feedback showing the downward trend of the curve; (vi) a strong cohort has a positive effect on the whole population that can be detected throughout the time. Our fitted models allowed to predict the mean population densities at a regional scale with <10% error and shed light onto the main factors and associated ecological processes that control these large-scale dynamics.

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