Pairing litter decomposition with microbial community structures using the Tea Bag Index (TBI)

Abstract

Abstract. Including information about soil microbial communities into global decomposition models is critical for predicting and understanding how ecosystem functions may shift in response to global change. Here we combined a standardised litter bag method for estimating decomposition rates, Tea Bag Index (TBI), with high-throughput sequencing of the microbial communities colonising the plant litter in the bags. Together with students of the Federal College for Viticulture and Fruit Growing, Klosterneuburg, Austria, acting as citizen scientists, we used this approach to investigate the diversity of prokaryotes and fungi colonising recalcitrant (rooibos) and labile (green tea) plant litter buried in three different soil types and during four seasons with the aim of (i) comparing litter decomposition [decomposition rates (k) and stabilisation factors (S)] between soil types and seasons, (ii) comparing the microbial communities colonising labile and recalcitrant plant litter between soil types and seasons (iii) correlating microbial diversity and taxa relative abundance patterns of colonisers with litter decomposition rates (k)and stabilisation factors (S). Stabilisation factor (S), but not decomposition rate (k), correlated with the season and was significantly lower in the summer. This finding highlights the necessity to include colder seasons in the efforts of determining decomposition dynamics in order to quantify nutrient cycling in soils accurately. With our approach, we further showed selective colonisation of plant litter by fungal and prokaryotic taxa sourced from the soil. The community structures of these microbial colonisers differed most profoundly between summer and winter, and rooibos litter was generally a stronger selector than green tea litter. Moreover, this study indicates an equal, if not higher, importance of fungal versus prokaryotic degraders for recalcitrant and labile plant litter decomposition. Our results collectively demonstrate the importance of analysing decomposition dynamics over multiple seasons and isolating the effect of the active component of the microbial community.