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Natural variability in hard-bottom communities and possible drivers assessed by a time-series study in the SW Baltic Sea: know the noise to detect the change

机译:通过SW波罗的海的时间序列研究评估的硬底部社区的自然变异性以及在SW波罗的海的时间序列进行评估:知道检测变化的噪音

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In order to detect shifts in community structure and function associated with global change, the natural background fluctuation in these traits must be known. In a 6 yr study we characterized the composition of young benthic communities at 7 sites along the 300 km coast of the Kiel and Lübeck bights in the German Baltic Sea and we quantified their interannual variability of taxonomic and functional composition. Along the salinity gradient from NW to SE, the relative abundance of primary producers decreased while that of heterotrophs increased. Along the same gradient, annual productivity tended to increase. Taxonomic and functional richness were higher in Kiel Bight as compared to Lübeck Bight. With increasing species richness functional group richness showed saturation indicating an increasing functional redundancy in species rich communities. While taxonomic fluctuations between years were substantial, functionality of the communities seem preserved in most cases. Environmental conditions potentially driving these fluctuations are winter temperatures and current regimes. We tentatively define a confidence range of natural variability in taxonomic and functional composition a departure from which might help identifying an ongoing regime shift driven by global change. In addition, we propose to use RELATE, a statistical procedure in the PRIMER (Plymouth Routines in Multivariate Ecological Research) package to distinguish directional shifts in time ("signal") from natural temporal fluctuations ("noise").
机译:为了检测社区结构和与全局变化相关的功能的转变,必须知道这些性状的自然背景波动。在6年的研究中,我们在德国波罗的海的300公里的沿岸的沿线沿岸的7个地点为7个地点的组成,我们量化了他们的分类和功能组合物的续集变异性。沿着NW至SE的盐度梯度,初级生产者的相对丰度随着异素的增加而降低。沿同一梯度,年生产力趋于增加。与Lübeck的偏见相比,基尔最近的分类和功能性较高。随着物种的增加,富含官能团的富含性群体显示饱和度,表明物种富裕社区的功能冗余。虽然多年来的分类学波动是大多数情况下的,但在大多数情况下,社区的功能似乎保存了。潜在地驾驶这些波动的环境条件是冬季温度和当前制度。我们暂时定义分类和功能组合中的自然变异性的置信范围,这可能有助于识别通过全球变革驱动的持续的政权转变。此外,我们建议使用涉及底漆(多变量生态学研究中的普利茅斯常规)统计程序,以区分定向转变(“信号”)从自然时间波动(“噪声”)。

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