Dynamics of natural rotifer populations |
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Authors: | Snell Terry W. Serra Manuel |
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Affiliation: | (1) School of Biology, Georgia Institute of Technology, Atlanta, Georgia 30332-0230, USA;(2) Departament de Ecologia i Microbiologia, Universitat de Valencia, E-46100 Burjassot Valencia, Spain |
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Abstract: | New tools for analyzing ecological time series have permitted the construction of rigorous models from relatively short series.
We have applied these techniques to abundance data for nine natural rotifer populations to construct realistic models of their
dynamics. Species included are Asplanchna girodi, Filinia pejleri, Keratella tropica, Monostyla bulla, Brachionus rotundiformis,
and four other Brachionus species. The overall shapes of the time series were similar with an initial peak followed by oscillations
of varying amplitude around a mean of lower population density. Auto correlation functions (ACF) for all populations were
positive at small time lags and decayed rapidly to zero. This suggest that these are stationary, exponentially damped time
series, fluctuating arround a constant mean with constant variance. The rapid decay of the ACFs indicates that the effect
of a perturbation on these populations is quickly removed in one or two days. Phase portrait plots of log current population
density vs log lagged density indicate that the time series are stable and non-chaotic. One type of model yielded the highest
R2 for four of the nine species and was designated the consensus model. The mean R2 of this model for all nine species was 0.53 with a coefficient of variation of 38%. Lyapanov exponents were strongly negative,
indicating that these populations rapidly return to equilibrium after an exogenous perturbation. Rotifer populations appear
to be tracking very recent perturbations and their dynamics cannot be predicted from perturbations in the more distant past.
We investigated the effects of increasing the level of stochasticity in the consensus model on the length of the growing season
and resting egg production. Increasing stochastic variance increased the probability of extremely low population densities,
shortening the growing season. In shorter growing seasons, fewer resting eggs were produced, other factors being equal. Counteracting
this negative effect, was an increased probability of extremely high populations densities which increased mixis and resting
egg production. Constructing models accurately depicting the dynamics of natural zooplankton populations should improve aquatic
ecosystem models.
This revised version was published online in July 2006 with corrections to the Cover Date. |
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