The spatial heterogeneity of soil and the microbial communities therein does not only persist on the microscale, but certainly also on
a centimeter, meter, field, or ecosystem scale
\cite{Becker_2006,Wolfe_2006,Franklin_2003}. Sampling “the same soil” a few meters apart or at different depths in the soil profile might
result in individual samples with varying biogeochemical properties such as pH, water
saturation, soil texture, and also plant root distribution \cite{Zhang_2021}. Choosing a sufficient number of replicates to assess sample or plot variability while balancing the cost-to-gain ratio is certainly an important measure to address soil heterogeneity (see also section XYZ). In addition, it is critical to carefully evaluate the representativeness of technical and biological replicates. The common assumption that replicates
are more similar to each other as compared to treatment effects can certainly introduce bias into soil microbiome
interpretation. For example, a recent study showed distinct and consistend differences in bacterial and fungal communities between replicate soil samples throughout a season even though 10-15 cores were randomly sampled in individual subplots and pooled \cite{Carini_2020}. Another study showed that chemical soil properties as well as microbial biomass and communities exhibited high levels of spatial variation across 49 samples in a 6 \(\times\) 6 m forest plot
\cite{_tursov__2016}. Pooling of samples, individual extractions of DNA/RNA and/or amplification reactions made from a single DNA template can certainly minimize the effect of soil heterogeneity. Nevertheless, existing intraplot variability and representativeness of samples, as well as appropriateness of sampling strategies to correctly address it must be critically assessed in any study on soil microbiomes. Otherwise, drawing of generalized macroecological conclusions from soil samples taken pooled across large distances may yield speculative information at best \cite{Zhang_2020}\cite{Dini_Andreote_2020}.
Relic DNA may obscure community dynamics on temporal scales
When designing an experiment, one must not only consider the spatial scales at which microorganisms live and interact, but as well the temporal scale at which sampling should occur to capture dynamics of interest. Amplicon sequencing has helped to observe and understand changes of microbial communities in various soil ecosystems over time, ranging from days and weeks to months and years (REFs). However, amplicon sequencing represents a snapshot of microbial prevalence at a given moment which makes the rate of community change a critical parameter when temporal dynamics are to be investigated. Given that microbial turnover among different soils is expected to range from weeks to years as well (e.g. \cite{Spohn_2016}), it is difficult to assess the best temporal sampling strategy a priori.