SR22218Do admixed conifers change soil nutrient conditions of European beech stands?

Estela Covre Foltran , Christian Ammer and Norbert Lamersdorf

pp. 647-662

The increase in temperatures is likely to change the landscape composition, affecting highly sensitive species. Thus, in order to keep the biodiversity and ecosystem services provided by forests, some action must be taken, i.e. replacing species and increasing forest diversity. The manuscript considers the effects on soil fertility of enriching European beech forests with conifers, and introducing exotic species, like Douglas fir, as possible replacements for the native conifer, Norway spruce, in mixed forests.

SR23012Microbiological indicators as sensitive indicators in the assessment of areas contaminated by heavy metals

Eliane Guimarães Pereira Melloni , Rogério Melloni , Rocío Pastor-Jáuregui , Antonio Aguilar-Garrido and Francisco José Martín-Peinado

pp. 663-673

Twenty years after the Aznalcóllar disaster, the degree of biological activity of the soil is assessed. Residual As and Pb pollution caused negative impacts on soil microbiota, with lower microbial biomass and higher biological stress. Microbial indicators are essential in long-term monitoring of remediation of polluted soils.

SR22267Soil phosphorus and biomass carbon co-determine plantation soil organic carbon density: a case study in western Beijing, China

Shiqiang Wang and Yanpei Guo

pp. 674-684

We investigated the potential mechanism of afforestation elevation affecting plantation ecosystem carbon density and what determines of soil organic carbon density (SOCD). We found that growth periods at the higher elevation were delayed relative to those at the lower elevation; soil nitrogen content, litter nitrogen density, soil kalium content, soil phosphorus content, and biomass carbon density were main drivers of plantation SOCD. These results assist to maximise plantation carbon sequestration, contribute to the carbon neutralisation strategy of China.

SR22216Numerical modelling of soil–landscape relationships using diversity indices and conditional probability: a case study from an Iranian arid region

Mohsen Bagheri-Bodaghabadi , Azam Jafari, Mojtaba Zeraatpisheh, Hamidreza Owliaie , Peter Finke and Ming Xu

pp. 697-716

Quantitative and numerical modelling of conceptual and qualitative concepts in the soil–landscape relationship is of great interest for soil mapping. A quantitative approach was developed between geomorphology and soil classes, using the conditional probability and diversity indices. Results numerically demonstrated relationships between soils and geomorphic levels. Therefore, numerical soil–landscape relationships can improve soil map quality and accuracy while reducing time and costs.