0000000000409940

AUTHOR

Sophia Leimer

0000-0001-6272-204x

Plant diversity enhances the natural attenuation of polycyclic aromatic compounds (PAHs and oxygenated PAHs) in grassland soils

Increasing plant species richness stimulates microbial activity in soil, which might favor biodegradation of polycyclic aromatic compounds (PACs). To explore the relationship between plant community composition and PACs in grassland soils (Fluvisols exposed to an urban atmosphere), we determined the concentrations of 29 polycyclic aromatic hydrocarbons (PAHs) and 15 oxygenated PAHs (OPAHs) in topsoils of 80 plots of a grassland biodiversity experiment. The plots included different levels of plant species richness (1, 2, 4, 8, 16, 60 species) and 1–4 plant functional groups (grasses, small herbs, tall herbs, and legumes) in a randomized block design. The concentrations (ng g−1) of ∑29PAHs an…

research product

Plant diversity effects on the water balance of an experimental grassland

In the literature, contrasting effects of plant species richness on the soil water balance are reported. Our objective was to assess the effects of plant species and functional richness and functional identity on soil water contents and water fluxes in the experimental grassland of the Jena Experiment. The Jena Experiment comprises 86 plots on which plant species richness (0, 1, 2, 4, 8, 16, and 60) and functional group composition (zero to four functional groups: legumes, grasses, tall herbs, and small herbs) were manipulated in a factorial design. We recorded meteorological data and soil water contents of the 0·0–0·3 and 0·3–0·7 m soil layers and calculated actual evapotranspiration (ETa)…

research product

Towards a new generation of high-resolution meteorological input data for small-scale hydrologic modeling

Summary Current and future challenges of hydrologic sciences are to accurately predict and assess climate-driven impacts on water resources for the relevant scales of planning. However, process-based small-scale hydrologic modeling is data demanding and large uncertainties exist in data-sparse areas. The aim of our study was to test the applicability of the COSMO-DE analysis data (COSMO-DE-A) for hydrologic modeling. COSMO-DE-A data are a new meteorological data set with high temporal and spatial resolution that originates from the German Weather Service data assimilation system using the COSMO-DE weather prediction model. We collected field parameters in a small (10 km 2 ) mountainous catc…

research product