Substrate quality drives fungal necromass decay and decomposer community structure under contrasting vegetation types

Abstract

Fungal mycelium is increasingly recognized as a central component of soil biogeochemical cycling, yet our current understanding of the ecological controls on fungal necromass decomposition is limited to single sites and vegetation types. By deploying common fungal necromass substrates in a temperate oak savanna and hardwood forest in the midwestern USA, we assessed the generality of the rate at which high‐ and low‐quality fungal necromass decomposes; further, we investigated how the decomposer ‘necrobiome’ varies both across and within sites under vegetation types dominated by either arbuscular or ectomycorrhizal plants. The effects of necromass quality on decay rate were robust to site and vegetation type differences, with high‐quality fungal necromass decomposing, on average, 2.5 times faster during the initial stages of decay. Across vegetation types, bacterial and fungal communities present on decaying necromass differed from bulk soil microbial communities and were influenced by necromass quality. Moulds, yeasts and copiotrophic bacteria consistently dominated the necrobiome of high‐quality fungal substrates. Synthesis. We show that regardless of differences in decay environments, high‐quality fungal substrates decompose faster and support different types of decomposer micro‐organisms when compared with low‐quality fungal tissues. These findings help to refine our theoretical understanding of the dominant factors affecting fast cycling components of soil organic matter and the microbial communities associated with rapid decay.

Variation in hyphal production rather than turnover regulates standing fungal biomass in temperate hardwood forests

“…This article is protected by copyright. All rights reserved soil, which could increase soil C (Fernandez et al 2019, Beidler et al 2020, at least in the short term.…”

Root presence modifies the long‐term decomposition dynamics of fungal necromass and the associated microbial communities in a boreal forest

“…Whereas identifying the factors determining rates of fungal necromass decomposition is increasingly well characterised, detailed description of the microbial communities associated with necromass decomposition have been more limited. Bacterial and fungal communities colonising fungal necromass during the first stages (up to 5 months) of incubation were recently described in both North American (Beidler et al, 2020; Fernandez & Kennedy, 2018; Maillard et al, 2020) and European forests (Brabcová et al, 2016, 2018). The bacterial communities associated with fungal necromass decomposition were notably consistent between those studies, being dominated by copiotrophic bacteria belonging to phyla Proteobacteria and Bacteroidetes (Beidler et al, 2020; Brabcová et al, 2016, 2018; Fernandez & Kennedy, 2018).…”

“…At both local and regional scales, the decomposition rate of the fungal necromass has been shown to be strongly affected by its biochemical quality (Beidler et al, 2020; Brabcová et al, 2018; Maillard et al, 2020). In particular, fungal necromass decomposition rate is known to be positively correlated with initial N concentration (Brabcová et al, 2018; Fernandez & Koide, 2012, 2014; Koide & Malcolm, 2009).…”

Nitrogen cycling microbiomes are structured by plant mycorrhizal associations with consequences for nitrogen oxide fluxes in forests

“…Examples of AM tree genera include maple ( Acer ), tulip ( Liriodendron ), cherry ( Prunus ), and ash ( Fraxinus ) while ECM tree genera include oak ( Quercus ), hickory ( Carya ), and beech ( Fagus ). Given that AM and ECM trees possess different nutrient use traits (Beidler et al, 2020; Cheeke et al, In press; Keller & Phillips, 2019; Lin et al., 2017) and promote unique soil microbial assemblages (Cheeke et al., 2017), the relative abundance of AM or ECM trees in a stand may be an effective integrator of various ecosystem processes (Phillips et al., 2013). Researchers have used the AM and ECM categorization to reflect distinct biogeochemical syndromes (e.g., AM: inorganic nutrient economy, fast N cycling; ECM: organic nutrient economy, slow N cycling).…”