Data from: The differential impact of a native and a non-native ragwort species (Senecioneae) on the first and second trophic level of the rhizosphere food web

Whereas the impact of exotic plant species on above-ground biota is relatively well-documented, far less is known about the effects of non-indigenous plants on the first and second trophic level of the rhizosphere food web. Here, rhizosphere communities of the invasive narrow-leaved ragwort Senecio inaequidens and the native tansy ragwort Jacobaea vulgaris, co-occurring in three semi-natural habitats are compared. For both species, two life stages were taken into consideration. Quantitative PCR assays for the analyses of bacterial and fungal communities at a high taxonomic level were optimized, and it was investigated whether changes in the primary decomposer community were translated in alterations in bacterivorous and fungivorous nematode communities. In contrast to J. vulgaris, small but significant reductions were observed for Actinobacteria and Bacteroidetes (both p < 0.05) in case of the invasive S. inaequidens. More pronounced changes were detected for the overall nematode community density, and, more specifically, for the bacterivorous genus Anaplectus and the family Monhysteridae (both p < 0.05), as well as the necromenic Pristionchus (p < 0.001). At high taxonomic level, no differences were observed in fungal rhizosphere communities between native and non-native ragwort species. The impact of plant developmental stages on rhizosphere biota was prominent. The overall bacterial and fungal biomasses, as well as a remarkably consistent set of constituents (Actinobacteria, α- and β-Proteobacteria and Bacteroidetes) were negatively affected by plant stage for both ragwort species. Although later developmental stages of plants generally coincided with lower levels for individual nematode taxa, densities of the fungivorous genera Diphtherophora and Tylolaimophorus remain unaltered. Hence, even at a high taxonomic level, differential effects of native and non-native ragwort could be pinpointed. However, plant developmental stage has a more prominent impact and this impact was similar in nature for both native and non-native ragwort species

Converted-qPCR-Data_nematodes_bacteria_fungi

In this data file you can find the data we used to execute our statistical tests. Converted Ct values are shown and the transformed data is shown in purple. (Making use of linear relationship between primary qPCR output, Ct values, and the number of individuals, nematode concentrations expressed as individuals per 100 g of soil were calculated. As both the resulting nematode densities and the concentrations of bacterial and fungal DNA (ng per 0.25 g soil) didn’t show a normal distribution, data were transformed. Primary counts were log transformed (ln(y+0.1)). A constant (0.1) was added to push data away from the lower bound zero.) A legend is added to explain the meaning of the first six rows

Spatial distribution of soil nematodes relates to soil organic matter and life strategy

Soils are among the most biodiverse and densely inhabited environments on our planet. However, there is little understanding of spatial distribution patterns of belowground biota, and this hampers progress in understanding species interactions in belowground communities. We investigated the spatial distribution of nematodes, which are highly abundant and diverse metazoans in most soil ecosystems. To gain insight into nematode patchiness, we mapped distribution patterns in twelve apparently homogeneous agricultural fields (100 m × 100 m each) with equal representation of three soil textures (marine clay, river clay and sandy soil). Quantitative PCRs were used to measure the abundances of 48 distinct nematode taxa in ≈1200 plots. Multivariate analysis showed that within this selection of sites, soil texture more strongly affected soil nematode communities than land management. Geostatistical analysis of nematode distributions revealed both taxon-specific and field-specific patchiness. The average geostatistical range (indicating patch diameter) of 48 nematode taxa in these fields was 36 m, and related to soil organic matter. Soil organic matter content affected the spatial variance (indicating within-field variation of densities) in a life-strategy dependent manner. The r-strategists (fast-growing bacterivores and fungivores) showed a positive correlation between organic matter content and spatial variance, whereas most K-strategists (slow-growing omnivores and carnivores) showed a negative correlation. Hence, the combination of two parameters, soil organic matter content and a general life-strategy characterisation, can be used to explain the spatial distribution of nematodes at field scale

Spatial distribution of soil nematodes relates to soil organic matter and life strategy

Soils are among the most biodiverse and densely inhabited environments on our planet. However, there is little understanding of spatial distribution patterns of belowground biota, and this hampers progress in understanding species interactions in belowground communities. We investigated the spatial distribution of nematodes, which are highly abundant and diverse metazoans in most soil ecosystems. To gain insight into nematode patchiness, we mapped distribution patterns in twelve apparently homogeneous agricultural fields (100 m × 100 m each) with equal representation of three soil textures (marine clay, river clay and sandy soil). Quantitative PCRs were used to measure the abundances of 48 distinct nematode taxa in ≈1200 plots. Multivariate analysis showed that within this selection of sites, soil texture more strongly affected soil nematode communities than land management. Geostatistical analysis of nematode distributions revealed both taxon-specific and field-specific patchiness. The average geostatistical range (indicating patch diameter) of 48 nematode taxa in these fields was 36 m, and related to soil organic matter. Soil organic matter content affected the spatial variance (indicating within-field variation of densities) in a life-strategy dependent manner. The r-strategists (fast-growing bacterivores and fungivores) showed a positive correlation between organic matter content and spatial variance, whereas most K-strategists (slow-growing omnivores and carnivores) showed a negative correlation. Hence, the combination of two parameters, soil organic matter content and a general life-strategy characterisation, can be used to explain the spatial distribution of nematodes at field scale.</p

SSU Ribosomal DNA-Based Monitoring of Nematode Assemblages Reveals Distinct Seasonal Fluctuations within Evolutionary Heterogeneous Feeding Guilds

<div><p>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.</p> </div

Temporal patterns of fungivorous nematode families.

<p>Seasonal variation in densities for fungivores in the field (<b>A</b>) and in the forest (<b>B</b>). Please note that the <i>y</i>-axis scales differ. Aphelenchidae (Aphe, blue), Aphelenchoididae (Acho, red), and two genera belonging to Diphtherophoridae –<i>viz</i>. <i>Tylolaimophorus</i> (Tylo, green) and <i>Diphtherophora</i> (Diph, yellow)– show different patterns over the seasons between open and close canopies. As these taxa represent all observed fungivores, a partial Mantel analysis performed in a matrix describing the community structure in the field (open canopies, matrix Y) and in the forest (close canopies, matrix X) using the squared Euclidean distance was performed using the total entries and the same set of entities. A positive association between the matrices is indicated over the seasons by observed Z greater than average Z from randomized runs (<i>P</i> = 0.0297).</p

Quantitative coverage of the DNA-based tool using environmental samples.

<p>Logarithm of the total of individuals as detected by optical microscopy (<i>x</i>-axis) plotted against the logarithm of the total of individuals as estimated by quantitative PCR (<i>y</i>-axis). The correlations of quantitative PCR with classical analyses seem to be accurate, with no Studentized residuals higher than | 2 |. The solid line shows the trend of all data and the two dashed lines show the boundaries of one-order-of-magnitude precision. The dotted line represents an equal amount of nematodes for both methods. Such a coverage is expected to be lower than 100% as obligate plant parasites were not included, although the fungivorous Aphelenchidae and Aphelenchoididae may harbor facultative plant parasites as shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047555#pone-0047555-t002" target="_blank">Table 2</a>. Given that taxa like Rhabditidae, Qudsianematidae or Nordiidae appear to be both poly- and paraphyletic <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047555#pone.0047555-VanMegen1" target="_blank">[23]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047555#pone.0047555-Holterman2" target="_blank">[65]</a>, no rDNA-based detection assay on family level could be developed for those nematodes.</p

Development and testing of a nematode family-specific primer combination.

<p>Here we use the Metateratocephalidae (one bacterivorous family harboring the <i>Metateratocephalus</i> and <i>Euteratocephalus</i> genera) as an example of primer development. (<b>A</b>) All primers were designed to have optimal annealing temperature (T_a) of 63°C, with C_t values varying at temperatures above and below the target T_a. (<b>B</b>) Specificity test of a Metateratocephalidae primer combination with plasmid DNAs from three target species, SSU rDNA fragments from 11 potential false positives (as selected by ARB <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047555#pone.0047555-Ludwig1" target="_blank">[39]</a>) and a negative water control. Clade numbers are according to Van Megen <i>et al</i>. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047555#pone.0047555-VanMegen1" target="_blank">[23]</a>. In the quantitative PCR graph the gap between the target and the non-target signal (ΔC_t) is shown. (<b>C</b>) Pictures of the head region of a representative of both genera. (<b>D</b>) The relationship between C_t values and numbers of nematodes for quantification of densities. A linear relationship between C_t values and numbers of nematodes till ¹/_1,000 part of a single nematode is shown (equivalent to a single nematode cell harboring ∼50 copies of the ribosomal DNA cistron). Hand-picked individuals of <i>Metateratocephalus</i> (purple circles) and <i>Euteratocephalus</i> (blue squares) were used to quantify the Metateratocephalidae-specific primers.</p

Overview of nematode diversity at genus level (microscopic analysis) in the topsoil (depth 0–25 cm) of the former arable field and the adjacent pristine beech forest.

<p>Obligate plant-parasitic nematodes are shown in grey [taxa ara given in brackets] and are not included in the molecular part of this research. Only the genera marked by ‘q’ are included in the quantitative PCR analysis and for most of these genera quantitative ranges (‘r’) are available (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047555#pone-0047555-g004" target="_blank">Fig. 4</a> and text for more details). For the taxonomy of the families we adhered to De Ley <i>et al</i>. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047555#pone.0047555-DeLey1" target="_blank">[66]</a>.</p

Temporal patterns of bacterivorous, omnivorous and predatory nematode families.

<p>We determined DNA-based variation in the nematode densities per 100 ml soil (note differences in <i>y</i>-axes) of representatives from seven bacterivorous families: Teratocephalidae, Prismatolaimidae, Cephalobidae, Plectidae (<i>i.e.</i>, all Plectidae excl. <i>Anaplectus</i> and ‘<i>Anaplectus</i>’, both in a dashed gray box), Alaimidae, Metateratocephalidae, Monhysteridae; the omnivorous family Dorylaimidae (D3 region <i>sensu </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047555#pone.0047555-Holterman2" target="_blank">[65]</a>); and the predatory families Mononchidae (M3, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047555#pone.0047555-Holterman2" target="_blank">[65]</a>) and Mylonchulidae. Sampling weeks as <i>x</i>-axes (constant scales); samples from the field are represented by orange triangles and samples from the forest by green diamonds. Trends are given as two-period moving averages: the averaged 2^nd and 3^rd data points are portrayed by the 1^st data point and so forth.</p