ALBERT

Description: Temperate forest soils are often considered as an important sink for atmospheric carbon (C), thereby buffering anthropogenic CO2 emissions. However, the effect of tree species composition on the magnitude of this sink is unclear. We resampled a tree species common garden experiment (six sites) a decade after initial sampling to evaluate whether forest floor (FF) and topsoil organic carbon (Corg) and total nitrogen (Nt) stocks changed in dependence of tree species (Norway spruce—Picea abies L., European beech—Fagus sylvatica L., pedunculate oak—Quercus robur L., sycamore maple—Acer pseudoplatanus L., European ash—Fraxinus excelsior L. and small‐leaved lime—Tilia cordata L.). Two groups of species were identified in terms of Corg and Nt distribution: (1) Spruce with high Corg and Nt stocks in the FF developed as a mor humus layer which tended to have smaller Corg and Nt stocks and a wider Corg:Nt ratio in the mineral topsoil, and (2) the broadleaved species, of which ash and maple distinguished most clearly from spruce by very low Corg and Nt stocks in the FF developed as mull humus layer, had greater Corg and Nt stocks, and narrow Corg:Nt ratios in the mineral topsoil. Over 11 years, FF Corg and Nt stocks increased most under spruce, while small decreases in bulk mineral soil (esp. in 0–15 cm and 0–30 cm depth) Corg and Nt stocks dominated irrespective of species. Observed decadal changes were associated with site‐related and tree species‐mediated soil properties in a way that hinted towards short‐term accumulation and mineralisation dynamics of easily available organic substances. We found no indication for Corg stabilisation. However, results indicated increasing Nt stabilisation with increasing biomass of burrowing earthworms, which were highest under ash, lime and maple and lowest under spruce. Highlights We studied if tree species differences in topsoil Corg and Nt stocks substantiate after a decade. The study is unique in its repeated soil sampling in a multisite common garden experiment. Forest floors increased under spruce, but topsoil stocks decreased irrespective of species. Changes were of short‐term nature. Nitrogen was most stable under arbuscular mycorrhizal species.

Description: Deutsche Forschungsgemeinschaff (DFG)

Description: Little research attention has been given to validating clusters obtained from the groundwater geochemistry of the waterworks' capture zone with a prevailing lake‐groundwater exchange. To address this knowledge gap, we proposed a new scheme whereby Gaussian finite mixture modeling (GFMM) and Spike‐and‐Slab Bayesian (SSB) algorithms were utilized to cluster the groundwater geochemistry while quantifying the probability of the resulting cluster membership against each other. We applied GFMM and SSB to 13 geochemical parameters collected during different sampling periods at 13 observation points across the Barnim Highlands plateau located in the northeast of Berlin, Germany; this included 10 observation wells, two lakes, and a gallery of drinking production wells. The cluster analysis of GFMM yielded nine clusters, either with a probability ≥0.8, while the SSB produced three hierarchical clusters with a probability of cluster membership varying from 〈0.2 to 〉0.8. The findings demonstrated that the clustering results of GFMM were in good agreement with the classification as per the principal component analysis and Piper diagram. By superimposing the parameter clustering onto the observation clustering, we could identify discrepancies that exist among the parameters of a certain cluster. This enables the identification of different factors that may control the geochemistry of a certain cluster, although parameters of that cluster share a strong similarity. The GFMM results have shown that from 2002, there has been active groundwater inflow from the lakes towards the capture zone. This means that it is necessary to adopt appropriate measures to reverse the inflow towards the lakes.

Description: Article impact statement: The probability of cluster membership quantified using an algorithm should be validated against another probabilistic‐based classifier.

Description: Federal Ministry of Education and Research http://dx.doi.org/10.13039/501100002347