Friday, July 7, 2017

Weekend reads

This short week passed by quickly. Nevertheless, I was able to find some interesting weekend reads for you.

Fungi play a key role in soil-plant interactions, nutrient cycling, and carbon flow and are essential for the functioning of arctic terrestrial ecosystems. Some studies have shown that the composition of fungal communities is highly sensitive to variations in environmental conditions, but little is known about how the conditions control the role of fungal communities (i.e. their ecosystem function). We used DNA metabarcoding to compare taxonomic and functional composition of fungal communities along a gradient of environmental severity in Northeast Greenland. We analysed soil samples from fell fields, heaths, and snowbeds, three habitats with very contrasting abiotic conditions. We also assessed within-habitat differences by comparing three widespread microhabitats (patches with high cover of Dryas, Salix, or bare soil). The data suggest that, along the sampled mesotopographic gradient, the greatest differences in both fungal richness and community composition are observed among habitats, while the effect of microhabitat is weaker, although still significant. Furthermore, we found that richness and community composition of fungi are shaped primarily by abiotic factors and to a lesser, though still significant extent, by floristic composition. Along this mesotopographic gradient, environmental severity is strongly correlated with richness in all fungal functional groups: positively in saprotrophic, pathogenic, and lichenised fungi, and negatively in ectomycorrhizal and root-endophytic fungi. Our results suggest complex interactions amongst functional groups, possibly due to nutrient limitation or competitive exclusion, with potential implications on soil carbon stocks. These findings are important in light of the environmental changes predicted for the Arctic.

Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic activities in marine environments. Traditionally, marine biomonitoring involves the sorting and morphological identification of benthic macro-invertebrates, which is time-consuming and taxonomic-expertise demanding. High-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) represents a promising alternative for benthic monitoring. However, an important fraction of eDNA sequences remains unassigned or belong to taxa of unknown ecology, which prevent their use for assessing the ecological quality status. Here, we show that supervised machine learning (SML) can be used to build robust predictive models for benthic monitoring, regardless of the taxonomic assignment of eDNA sequences. We tested three SML approaches to assess the environmental impact of marine aquaculture using benthic foraminifera eDNA, a group of unicellular eukaryotes known to be good bioindicators, as features to infer macro-invertebrates based biotic indices. We found similar ecological status as obtained from macro-invertebrates inventories. We argue that SML approaches could overcome and even bypass the cost and time-demanding morpho-taxonomic approaches in future biomonitoring.

Agricultural productivity relies on a wide range of ecosystem services provided by the soil biota. Plowing is a fundamental component of conventional farming, but long-term detrimental effects such as soil erosion and loss of soil organic matter have been recognized. Moving towards more sustainable management practices such as reduced tillage or crop residue retention can reduce these detrimental effects, but will also influence structure and function of the soil microbiota with direct consequences for the associated ecosystem services. Although there is increasing evidence that different tillage regimes alter the soil microbiome, we have a limited understanding of the temporal dynamics of these effects. Here, we used high-throughput sequencing of bacterial and fungal ribosomal markers to explore changes in soil microbial community structure under two contrasting tillage regimes (conventional and reduced tillage) either with or without crop residue retention. Soil samples were collected over the growing season of two crops (Vicia faba and Triticum aestivum) below the seedbed (15-20 cm). Tillage, crop and growing stage were significant determinants of microbial community structure, but the impact of tillage showed only moderate temporal dependency. Whereas the tillage effect on soil bacteria showed some temporal dependency and became less strong at later growing stages, the tillage effect on soil fungi was more consistent over time. Crop residue retention had only a minor influence on the community. Six years after the conversion from conventional to reduced tillage, soil moisture contents and nutrient levels were significantly lower under reduced than under conventional tillage. These changes in edaphic properties were related to specific shifts in microbial community structure. Notably, bacterial groups featuring copiotrophic lifestyles or potentially carrying the ability to degrade more recalcitrant compounds were favored under conventional tillage, whereas taxa featuring more oligotrophic lifestyles were more abundant under reduced tillage. Our study found that, under the specific edaphic and climatic context of central Belgium, different tillage regimes created different ecological niches that select for different microbial lifestyles with potential consequences for the ecosystem services provided to the plants and their environment.

Population-scale molecular studies of endangered and cryptic species are often limited by access to high-quality samples. The use of non-invasively collected samples or museum-preserved specimens reduces the pressure on modern populations by removing the need to capture and handle live animals. However, endogenous DNA content in such samples is low, making shotgun sequencing a financially prohibitive approach. Here, we apply a target enrichment method to retrieve mitochondrial genomes from 65 museum specimens and 56 non-invasively collected fecal samples of two endangered great ape species, Grauer's gorilla and the eastern chimpanzee. We show that the applied method is suitable for a wide range of sample types that differ in endogenous DNA content, increasing the proportion of target reads to over 300-fold. By systematically evaluating biases introduced during target enrichment of pooled museum samples we show that capture is less efficient for fragments shorter or longer than the baits, that the proportion of human contaminating reads increases post-capture although capture efficiency is lower for human compared to gorilla fragments with a gorilla-generated bait, and that the rate of jumping PCR is considerable, but can be controlled for with a double-barcoding approach. We succeed in capturing complete mitochondrial genomes from fecal samples, but observe reduced capture efficiency as sequence divergence increases between the bait and target species. As previously shown for museum specimens, we demonstrate here that mitochondrial genome capture from field-collected fecal samples is a robust, and reliable approach for population-wide studies of non-model organisms.

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