Laboratory of Nematology, Department of Plant Sciences, Wageningen University, WUR, Wageningen, The Netherlands.
PLoS One. 2012;7(10):e47555. doi: 10.1371/journal.pone.0047555. Epub 2012 Oct 24.
Soils are among the most complex, diverse and competitive habitats on Earth and soil biota are responsible for ecosystem services such as nutrient cycling, carbon sequestration and remediation of freshwater. The extreme biodiversity prohibits the making of a full inventory of soil life. Hence, an appropriate indicator group should be selected to determine the biological condition of soil systems. Due to their ubiquity and the diverse responses to abiotic and biotic changes, nematodes are suitable indicators for environmental monitoring. However, the time-consuming microscopic analysis of nematode communities has limited the scale at which this indicator group is used. In an attempt to circumvent this problem, a quantitative PCR-based tool for the detection of a consistent part of the soil nematofauna was developed based on a phylum-wide molecular framework consisting of 2,400 full-length SSU rDNA sequences. Taxon-specific primers were designed and tested for specificity. Furthermore, relationships were determined between the quantitative PCR output and numbers of target nematodes. As a first field test for this DNA sequence signature-based approach, seasonal fluctuations of nematode assemblages under open canopy (one field) and closed canopy (one forest) were monitored. Fifteen taxa from four feeding guilds (covering ∼ 65% of the free-living nematode biodiversity at higher taxonomical level) were detected at two trophic levels. These four feeding guilds are composed of taxa that developed independently by parallel evolution and we detected ecologically interpretable patterns for free-living nematodes belonging to the lower trophic level of soil food webs. Our results show temporal fluctuations, which can be even opposite within taxa belonging to the same guild. This research on nematode assemblages revealed ecological information about the soil food web that had been partly overlooked.
土壤是地球上最复杂、最多样和最具竞争力的栖息地之一，土壤生物群系负责提供养分循环、碳固存和淡水修复等生态系统服务。极端的生物多样性使得对土壤生物的全面普查成为不可能。因此，应该选择适当的指示物群组来确定土壤系统的生物状况。由于线虫在土壤中的普遍存在以及对线虫多样性和生物多样性变化的多样化响应，它们是环境监测的合适指示物。然而，对线虫群落进行耗时的微观分析限制了该指示物群组的应用规模。为了克服这个问题，我们基于包含 2400 条全长 SSU rDNA 序列的全门分子框架，开发了一种基于定量 PCR 的工具，用于检测土壤线虫区系的一致部分。设计并测试了针对特定分类群的引物，以确保其特异性。此外，还确定了定量 PCR 输出与目标线虫数量之间的关系。作为这种基于 DNA 序列特征的方法的首次现场测试，我们监测了开阔树冠（一个田野）和封闭树冠（一个森林）下线虫群落的季节性波动。在两个营养水平上检测到四个摄食群（涵盖较高分类水平上自由生活线虫生物多样性的约 65%）的 15 个分类群。这四个摄食群由通过平行进化独立形成的类群组成，我们检测到属于土壤食物网较低营养级别的自由生活线虫的生态可解释模式。我们的结果显示了时间上的波动，甚至在属于同一类群的类群内也存在相反的波动。这项关于线虫群落的研究揭示了土壤食物网的生态信息，这些信息在某种程度上被忽视了。
