Morpho-functional classification of humus forms using the TerrHum-App: correlation of morphological indicators and standardised laboratory analysis parameters

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200208724

6. DWB Student Conference 2021: Forest and Soil Science update. Book of Abstracts (2021) , 17

As the most dynamic part in soil, humus forms are an integrative indicator for decomposition processes in a forest ecosystem. The TerrHum App provides a digital field manual for classifying terrestrial humus forms. This common morpho-functional classification system categorises the organic & organo-mineral topsoil based on morphological characteristics detectable with the naked eye in the field and links them to biological soil functioning. In the present study we investigate, how practicable the TerrHum-App is as a tool and how well the morphological-functional field indicators correlate with standardized laboratory parameters (chemical and soil microbial properties) which are used to characterize litter decomposition. The field survey comprised 30 ForSite plots (Forest Site Classification Styria 2019) in the Bruck-Mürzzuschlag district, stratified by substrate, climate and vegetation. Humus forms at three microsites per plot (erosive, intermediate and accumulating) were described using the TerrHum App. Area representative, volumetric samples were taken from the organic layer and topsoil horizons at the intermediate plot. In addition, sufficient amounts of samples
were taken in all relief-positions, homogenised and sieved in the field and stored within few hours at -20°C. We analyzed Corg & Norg (Elementary analyzer), pH-value and Cinorg (Scheibler, in case of calcareous Ahorizons) as well as soil microbial biomass, Cmic and Nmic (fumigation extraction method). The temperature and moisture response of heterotrophic respiration R & Q10 are analyzed on a subsample of representative humus profiles. We will use correlation analyses, analyses of variance, multiple comparisons as well as multivariate statistics (cluster analyses, PCA) in R in order to test the hypothesis: ‘We are able to predict indicators of SOM turnover based on a morphological description of humus forms.