[this part added by Tina, 1.1.2021] Combining  classical soil biogeochemical methods with amplicon sequencing
Traditional soil biogeochemical research also offers methods to quantify total microbial biomass in soil, such as chloroform fumigation extraction (CFE) or the measurement of phospholipid fatty acids (PLFAs). In contrast to PCR-based methods, they measure the concentration of chemical microbial biomarkers in soil directly, thereby avoiding possible biases by amplification of the target molecules.
Data on total microbial biomass provided by these methods may also help interpreting relative abundance data obtained by amplicon sequencing. However, the combined interpretation of datasets from biochemical and molecular methods with fundamentally different measurement principles may not be as straightforward as the combination of amplicon sequencing data with qPCR measurements would be, especially if they are based on the same primer pairs (see above).
In any case, for a sound interpretation of combined datasets, differences in measurement principles between the methods need to be taken into account before drawing conclusions. Chloroform fumigation extraction method, for example, measures soluble C compounds inside microbial cells, which are released when cells burst due to soil samples being fumigated with chloroform. Phospholipid fatty acid measurements, on the contrary, quantify the amount of phospholipids in microbial cell walls, whereas both qPCR and amplicon sequencing measures the abundances of 16S rRNA gene copy numbers. These three fundamentally different units of microbial biomass, may scale differently with changes in microbial biomass when accompanied by shifts in microbial community composition, as microbial phylogenetic groups may contain group-specific (but mostly unknown) contents of dissolved C compounds, cell wall phospholipids or 16S rRNA gene copy numbers. Any change in total microbial biomass which is combined with changing relative abundances of different microbial groups may thus be reflected differently in CFE, PLFAs or qPCR measures.
Despite these limitations, independent additional measures of total microbial biomass by classical methods may provide valuable support for interpreting amplicon sequencing data. The mere information whether total microbial biomass increased or decreased between treatments allows to interpret relative abundance changes observed by amplicon sequencing within a more realistic context (Fig. 4). 
PLFA measurements can not only be used as a robust and direct measure of total microbial biomass, but also to obtain additional information on the abundance of certain microbial groups on a coarse phylogenetic level. Most importantly, it allows to quantify fatty acid biomarkers for bacteria and fungi, as well as for specific bacterial groups, such as gram+, gram- or actinobacteria. This information could be used as a “benchmark” for interpreting relative abundance data (f.e. Drigo et al, PNAS, 2010) – keeping in mind the above-mentioned limitations caused by differences in the measurement principles.
PLFAs is also one of the rare measurement methods that allows to assess shifts in the relative proportions of fungi and bacteria, something which cannot be achieved with qPCR or amplicon sequencing. Datasets for fungi and bacteria are always separated when derived from PCR-based methods due to the need to use different primer sets. The joint interpretation of bacteria and fungal community compositions based on amplicon sequencing data – even if combined with qPCR data, thus always lacks the information on potential shift across these kingdoms. This could be overcome, if important for the research question, by investing in the additional effort of conducting complementary PLFA measurements (or metagenomics – maybe we should mention here as well?)
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