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The metabolism of lake plankton does not support the metabolic theory of ecology

机译:浮游生物的新陈代谢不支持生态学的新陈代谢理论

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We tested if the metabolic theory of ecology (MTE) correctly predicts plankton metabolism in a temperate lake, based on a long-term (about 15 years), high-frequency dataset of body size, abundance and production, using two different techniques: least squares regression and maximum likelihood. For phytoplankton, the general fit was relatively poor (rpo=0.53). The assumption of the MTE on temperature dependence of metabolism was not supported, and the assumed value of [fraction three-quarters] of the allometric exponent was barely within 95% confidence limits. For some of the models, the value of b was significantly higher than [fraction three-quarters]. When radiation was included as an additional predictor, it improved the model considerably (rpo=0.67). Including grazing by zooplankton reduced the model residuals during the summer period, when grazing is a dominant factor. The allometric exponent had virtually no effect for phytoplankton, due to little variability in average individual size. Zooplankton production, on the other hand, was better predicted by MTE, showing stronger effects of temperature and body size, the average of which varied by a factor of more than a hundred. However, the best-fitting value of the allometric exponent for zooplankton was 0.85, and significantly higher than the [fraction three-quarters] predicted by the theory. The ratio of observed production to biomass for the entire plankton community declined linearly with the body size (in log-log) with a slope corresponding to a value of b=0.85. We conclude that the MTE has little predictive power for the metabolism of lacustrine plankton, in particular for phytoplankton, and especially at the scale of variability of this study, and that this could be improved by incorporating radiation into the model.
机译:我们使用两种不同的技术,基于长期(约15年)的人体大小,丰度和生产量的高频数据集,测试了生态学的代谢理论(MTE)是否能正确预测温带湖泊中的浮游生物代谢。平方回归和最大似然。对于浮游植物,总体适应性相对较差(rpo = 0.53)。不支持MTE依赖于代谢的温度依赖性的假设,并且异速指数的[四分之三]假设值仅在95%的置信范围内。对于某些模型,b的值显着高于[分数的四分之三]。当将辐射作为附加预测因子时,它将大大改善模型(rpo = 0.67)。夏季,当放牧成为主要因素时,包括浮游动物的放牧会减少模型残留。由于平均个体大小几乎没有变化,因此异速指数对浮游植物几乎没有影响。另一方面,MTE可以更好地预测浮游动物的产量,显示出温度和体型的影响更大,它们的平均值相差100倍以上。但是,浮游生物的异速指数的最合适值是0.85,并且明显高于理论预测的[四分之三]。整个浮游生物群落的观察到的生产量与生物量的比率随着身体尺寸(对数对数)线性下降,其斜率对应于b = 0.85。我们得出的结论是,MTE对湖泊浮游生物的代谢,特别是对浮游植物的代谢,尤其是在本研究的可变性尺度上,没有预测力,可以通过将辐射纳入模型中来改善。

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