6533b7ddfe1ef96bd1273cb4

RESEARCH PRODUCT

Environmental noise and population dynamics of the ciliated protozoa Tetrahymena thermophila in aquatic microcosms

Veijo KaitalaKatja LöytynojaJouni Laakso

subject

education.field_of_studyBiomass (ecology)biologyEcologyPopulation sizePopulationTetrahymenabiology.organism_classificationPopulation modelPopulation growthGrowth rateeducationMicrocosmEcology Evolution Behavior and Systematics

description

Population theory predicts that the reddened environmental noise, especially in combination with high population growth rate, reddens population dynamics, increases population variability and strengthens environment–population correlation. We tested these predictions with axenic populations of ciliated protozoa Tetrahymena thermophila. Populations with low and high growth rate were cultured in a stable environment, and in environments with sublethal temperature fluctuations that had blue, white and red spectra (i.e. negatively autocorrelated, uncorrelated, or positively autocorrelated, respectively). Population size and biomass of individuals were determined at 3-h intervals for 18 days. Dynamics of all populations were reddened, suggesting that internal mechanisms can redden the population spectra. However, population dynamics were reddest, variability highest, and environment–population correlation strongest in the red environment as predicted. Contrary to theoretical predictions and previous empirical findings, population growth rate (rmax being equal to 0.05 and 0.3 h−1) had no effect on population dynamics. Mean cell size and variability of cell size were affected by the presence and type of environmental noise suggesting that the physiological consequences of variability depend on colour. Environmental variability decreased mean population size and biomass and the decrease was strongest in rapidly fluctuating blue and white environments. The latter finding implies that rapid fluctuations are physiologically stressful, an effect that is not accounted for in the basic population models.

https://doi.org/10.1034/j.1600-0706.2003.12319.x