Factors shaping community patterns of protists and bacteria on a European scale

Factors shaping community patterns of microorganisms are controversially discussed. Physical and chemical factors certainly limit the survival of individual taxa and maintenance of diversity. In recent years, a contribution of geographic distance and dispersal barriers to distribution patterns of protists and bacteria has been demonstrated. Organismic interactions such as competition, predation and mutualism further modify community structure and maintenance of distinct taxa. Here, we address the relative importance of these different factors in shaping protists and bacterial communities on a European scale using high-throughput sequencing data obtained from lentic freshwater ecosystems. We show that community patterns of protists are similar to those of bacteria. Our results indicate that cross-domain organismic factors are important variables with a higher influence on protists as compared with bacteria. Abiotic physical and chemical factors also contributed significantly to community patterns. The contribution of these latter factors was higher for bacteria, which may reflect a stronger biogeochemical coupling. The contribution of geographical distance was similar for both microbial groups.     

Quantifying the effects of switchgrass (Panicum virgatum) on deep organic C stocks using natural abundance 14C in three marginal soils

Perennial bioenergy crops have been shown to increase soil organic carbon (SOC) stocks, potentially offsetting anthropogenic C emissions. The effects of perennial bioenergy crops on SOC are typically assessed at shallow depths (<30 cm), but the deep root systems of these crops may also have substantial effects on SOC stocks at greater depths. We hypothesized that deep (>30 cm) SOC stocks would be greater under bioenergy crops relative to stocks under shallow‐rooted conventional crop cover. To test this, we sampled soils to between 1‐ and 3‐m depth at three sites in Oklahoma with 10‐ to 20‐year‐old switchgrass (Panicum virgatum) stands, and collected paired samples from nearby fields cultivated with shallow rooted annual crops. We measured root biomass, total organic C, ¹⁴C, ¹³C, and other soil properties in three replicate soil cores in each field and used a mixing model to estimate the proportion of recently fixed C under switchgrass based on ¹⁴C. The subsoil C stock under switchgrass (defined over 500–1500 kg/m² equivalent soil mass, approximately 30–100 cm depth) exceeded the subsoil stock in neighboring fields by 1.5 kg C/m² at a sandy loam site, 0.6 kg C/m² at a site with loam soils, and showed no significant difference at a third site with clay soils. Using the mixing model, we estimated that additional SOC introduced after switchgrass cultivation comprised 31% of the subsoil C stock at the sandy loam site, 22% at the loam site, and 0% at the clay site. These results suggest that switchgrass can contribute significantly to subsoil organic C—but also indicated that this effect varies across sites. Our analysis shows that agricultural strategies that emphasize deep‐rooted grass cultivars can increase soil C relative to conventional crops while expanding energy biomass production on marginal lands.     

Canadian polar bear population structure using genome‐wide markers

Predicting the consequences of environmental changes, including human‐mediated climate change on species, requires that we quantify range‐wide patterns of genetic diversity and identify the ecological, environmental, and historical factors that have contributed to it. Here, we generate baseline data on polar bear population structure across most Canadian subpopulations (n = 358) using 13,488 genome‐wide single nucleotide polymorphisms (SNPs) identified with double‐digest restriction site‐associated DNA sequencing (ddRAD). Our ddRAD dataset showed three genetic clusters in the sampled Canadian range, congruent with previous studies based on microsatellites across the same regions; however, due to a lack of sampling in Norwegian Bay, we were unable to confirm the existence of a unique cluster in that subpopulation. These data on the genetic structure of polar bears using SNPs provide a detailed baseline against which future shifts in population structure can be assessed, and opportunities to develop new noninvasive tools for monitoring polar bears across their range.