Vasseur David A, Gaedke Ursula
Department of Biology, McGill University, Montreal, Quebec, Canada.
Ecology. 2007 Aug;88(8):2058-71. doi: 10.1890/06-1899.1.
Community biomass is often less variable than the biomasses of populations within the community, yet attempts to implicate compensatory dynamics between populations as a cause of this relationship often fail. In part, this may be due to the lack of appropriate metrics for variability, but there is also great potential for large-scale processes such as seasonality or longer-term environmental change to obscure important dynamics at other temporal scales. In this study, we apply a scale-resolving method to long-term plankton data, to identify the specific temporal scales at which community-level variability is influenced by synchrony or compensatory dynamics at the population level. We show that variability at both the population and community level is influenced strongly by a few distinct temporal scales: in phytoplankton, ciliate, rotifer, and crustacean communities, synchronous dynamics are predominant at most temporal scales. However, in phytoplankton and crustacean communities, compensatory dynamics occur at a sub-annual scale (and at the annual scale in crustaceans) leading to substantial reductions in community-level variability. Aggregate measures of population and community variability do not detect compensatory dynamics in these communities; thus, resolving their scale dependence unmasks dynamics that are important for community stability in this system. The methods and results presented herein will ultimately lead to a better understanding of how stability is achieved in communities.
群落生物量的变化通常比群落内种群的生物量变化小,然而,试图将种群间的补偿动态作为这种关系的一个原因往往是失败的。部分原因可能是缺乏合适的变异性度量指标,但季节性或长期环境变化等大规模过程也很有可能掩盖其他时间尺度上的重要动态。在本研究中,我们将一种尺度解析方法应用于长期浮游生物数据,以确定群落水平变异性受种群水平同步或补偿动态影响的特定时间尺度。我们表明,种群和群落水平的变异性都受到一些不同时间尺度的强烈影响:在浮游植物、纤毛虫、轮虫和甲壳类群落中,同步动态在大多数时间尺度上占主导地位。然而,在浮游植物和甲壳类群落中,补偿动态发生在亚年度尺度(在甲壳类中为年度尺度),导致群落水平变异性大幅降低。种群和群落变异性的总体度量并未检测到这些群落中的补偿动态;因此,解析它们的尺度依赖性揭示了对该系统中群落稳定性很重要的动态。本文提出的方法和结果最终将有助于更好地理解群落如何实现稳定性。