Microbial and biochemical dynamics of ectomycorrhizal mat and non-mat forest soils

Dense hyphal mats formed by ectomycorrhizal (EcM) fungi are prominent features in Douglas-fir (Pseudotsuga menziesii) forest soils and have been estimated to cover up to 40% of the forest floor in some stands. Although previous studies have examined various aspects of EcM fungi, little is known about their associated microbial communities and activities. The objectives of my dissertation are 1) to provide a current account of chemical and biochemical properties associated with EcM fungi, and 2) to describe the communities and activities of microbes occupying EcM mat and non-mat forest soils. In the first phase of my research, I surveyed EcM mat and non-mat soils from early and late seral forest stands in the western Oregon Cascades. EcM mats were phylotyped and a variety of chemical and biochemical properties were measured. Results from this survey revealed distinct chemical and biochemical profiles for EcM mats in organic and mineral soils compared with their corresponding non-mat soil horizons. The second phase of my research followed up this work by focusing on Piloderma mats in old-growth Douglas-fir stands. A combination of community fragment profiles, clone libraries, and quantitative PCR of bacterial 16S and fungal ITS rRNA genes, in conjunction with chitinase enzyme assays, were used to assess the microbial community composition, abundance, and activity in a year-long temporal study. I found that Piloderma mats harbor distinct fungal and bacterial communities compared with non-mat soils. Furthermore, although microbial populations and enzyme activity of both soil types fluctuated throughout the year, their community compositions remained relatively stable. The results presented in this dissertation demonstrate that EcM mats create a unique soil environment with distinct microbial communities and activities compared to non-mat forest soils. This work provides a significant contribution to the understanding of how EcM fungi impact the soil environment and microbial communities

Multi-year incubation experiments boost confidence in model projections of long-term soil carbon dynamics

Global soil organic carbon (SOC) stocks may decline with a warmer climate. However, model projections of changes in SOC due to climate warming depend on microbially-driven processes that are usually parameterized based on laboratory incubations. To assess how lab-scale incubation datasets inform model projections over decades, we optimized five microbially-relevant parameters in the Microbial-ENzyme Decomposition (MEND) model using 16 short-term glucose (6-day), 16 short-term cellulose (30-day) and 16 long-term cellulose (729-day) incubation datasets with soils from forests and grasslands across contrasting soil types. Our analysis identified consistently higher parameter estimates given the short-term versus long-term datasets. Implementing the short-term and long-term parameters, respectively, resulted in SOC loss (–8.2 ± 5.1% or –3.9 ± 2.8%), and minor SOC gain (1.8 ± 1.0%) in response to 5 °C warming, while only the latter is consistent with a meta-analysis of 149 field warming observations (1.6 ± 4.0%). Comparing multiple subsets of cellulose incubations (i.e., 6, 30, 90, 180, 360, 480 and 729-day) revealed comparable projections to the observed long-term SOC changes under warming only on 480- and 729-day. Integrating multi-year datasets of soil incubations (e.g., \u3e 1.5 years) with microbial models can thus achieve more reasonable parameterization of key microbial processes and subsequently boost the accuracy and confidence of long-term SOC projections

Fungal and Bacterial Communities Exhibit Consistent Responses to Reversal of Soil Acidification and Phosphorus Limitation over Time

Chronic acid deposition affects many temperate hardwood forests of the northeastern United States, reduces soil pH and phosphorus (P) availability, and can alter the structure and function of soil microbial communities. The strategies that microorganisms possess for survival in acidic, low P soil come at a carbon (C) cost. Thus, how microbial communities respond to soil acidification in forests may be influenced by plant phenological stage as C allocation belowground varies; however, this remains largely unexplored. In this study, we examined microbial communities in an ecosystem level manipulative experiment where pH and/or P availability were elevated in three separate forests in Northeastern Ohio. Tag-encoded pyrosequencing was used to examine bacterial and fungal community structure at five time points across one year corresponding to plant phenological stages. We found significant effects of pH treatment and time on fungal and bacterial communities in soil. However, we found no interaction between pH treatment and time of sampling for fungal communities and only a weak interaction between pH elevation and time for bacterial communities, suggesting that microbial community responses to soil pH are largely independent of plant phenological stage. In addition, fungal communities were structured largely by site, suggesting that fungi were responding to differences between the forests, such as plant community differences

Mycorrhizal Response to Experimental pH and P Manipulation in Acidic Hardwood Forests

<div><p>Many temperate forests of the Northeastern United States and Europe have received significant anthropogenic acid and nitrogen (N) deposition over the last century. Although temperate hardwood forests are generally thought to be N-limited, anthropogenic deposition increases the possibility of phosphorus (P) limiting productivity in these forest ecosystems. Moreover, inorganic P availability is largely controlled by soil pH and biogeochemical theory suggests that forests with acidic soils (i.e., </p></div

Rarefaction curves showing the expected number of species (97% OTUs) as a function of the number of EcM root tips from each treatment.

<p>Although the control appears to have lower diversity than the treatments, this visual difference is not statistically significant (95% confidence intervals not shown to improve figure clarity).</p

CCA ordinations showing the effect of location, treatment, pH, and P availability on the on AM (A) and EcM (B) communities.

<p>Region is denoted by shape: glaciated (triangles) and unglaciated (inverted triangles) and treatment is denoted with color: control (white), elevated pH (grey), elevated P (dotted grey), and elevated pH+P (black). Centroids and error bars represent the mean and standard errors of axes scores within a given treatment. Monte Carlo <i>P</i>-values for eigenvalues for the AM and EcM ordinations were 0.03 and <0.01, respectively. Joint-plot overlays were unable to detect any significant correlations between tree species and either the AM or EcM community composition.</p

The effect of region and treatments on soil pH and phosphorus with mean values and standard errors.

<p><i>P</i>-values for the effect of region and treatments from the LME model with forest blocks as the random effect (n = 9). Asterisks denote a significant difference, in comparison to controls, at <i>P</i><0.05 (**) and <i>P</i><0.10 (*).</p