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I. II. III. IV. V. References SUMMARY: Interactions between trees and microorganisms are tremendously complex and the multispecies networks resulting from these associations have consequences for plant growth and productivity. However, a more holistic view is needed to better understand trees as ecosystems and superorganisms, where many interacting species contribute to the overall stability of the system. While much progress has been made on microbial communities associated with individual tree niches and the molecular interactions between model symbiotic partners, there is still a lack of knowledge of the multi‐component interactions necessary for holistic ecosystem‐level understanding. We review recent studies in Populus to emphasize the importance of such holistic efforts across the leaf, stem and rooting zones, and discuss prospects for future research in these important ecosystems.

Bacterial and fungal communities associated with plant roots are central to the host health, survival and growth. However, a robust understanding of the root-microbiome and the factors that drive host associated microbial community structure have remained elusive, especially in mature perennial plants from natural settings. Here, we investigated relationships of bacterial and fungal communities in the rhizosphere and root endosphere of the riparian tree species Populus deltoides, and the influence of soil parameters, environmental properties (host phenotype and aboveground environmental settings), host plant genotype (Simple Sequence Repeat (SSR) markers), season (Spring vs. Fall) and geographic setting (at scales from regional watersheds to local riparian zones) on microbial community structure. Each of the trees sampled displayed unique aspects to its associated community structure with high numbers of Operational Taxonomic Units (OTUs) specific to an individual trees (bacteria >90%, fungi >60%). Over the diverse conditions surveyed only a small number of OTUs were common to all samples within rhizosphere (35 bacterial and 4 fungal) and endosphere (1 bacterial and 1 fungal) microbiomes. As expected, Proteobacteria and Ascomycota were dominant in root communities (>50%) while other higher-level phylogenetic groups (Chytridiomycota, Acidobacteria) displayed greatly reduced abundance in endosphere compared to the rhizosphere. Variance partitioning partially explained differences in microbiome composition between all sampled roots on the basis of seasonal and soil properties (4% to 23%). While most variation remains unattributed, we observed significant differences in the microbiota between watersheds (Tennessee vs. North Carolina) and seasons (Spring vs. Fall). SSR markers clearly delineated two host populations associated with the samples taken in TN vs. NC, but overall host genotypic distances did not have a significant effect on corresponding communities that could be separated from other measured effects.

Tree stems from wetland, floodplain and upland forests can produce and emit methane (CH₄). Tree CH₄ stem emissions have high spatial and temporal variability, but there is no consensus on the biophysical mechanisms that drive stem CH₄ production and emissions. Here, we summarize up to 30 opportunities and challenges for stem CH₄ emissions research, which, when addressed, will improve estimates of the magnitudes, patterns and drivers of CH₄ emissions and trace their potential origin.We identified the need: (1) for both long-term, high-frequency measurements of stem CH₄ emissions to understand the fine-scale processes, alongside rapid large-scale measurements designed to understand the variability across individuals, species and ecosystems; (2) to identify microorganisms and biogeochemical pathways associated with CH₄ production; and (3) to develop a mechanistic model including passive and active transport of CH₄ from the soil–tree–atmosphere continuum. Addressing these challenges will help to constrain the magnitudes and patterns of CH₄ emissions, and allow for the integration of pathways and mechanisms of CH₄ production and emissions into process-based models. These advances will facilitate the upscaling of stem CH₄ emissions to the ecosystem level and quantify the role of stem CH₄ emissions for the local to global CH₄ budget.

• It is increasingly evident that the plant microbiome is a strong determinant of plant health. While the ability to manipulate the microbiome in plants and ecosystems recovering from disturbance may be useful, our understanding of the plant microbiome in regenerating plant communities is currently limited. • Using 16S ribosomal RNA (rRNA) gene and internal transcribed spacer (ITS) region amplicon sequencing, we characterized the leaf, stem, fine root, rhizome, and rhizosphere microbiome of < 1-yr-old aspen saplings and the associated bulk soil after a recent high-intensity prescribed fire across a burn severity gradient. • Consistent with previous studies, we found that soil microbiomes are responsive to fire. We extend these findings by showing that certain plant tissue microbiomes also change in response to fire. Differences in soil microbiome compositions could be attributed to soil chemical characteristics, but, generally, plant tissue microbiomes were not related to plant tissue elemental concentrations. Using source tracking modeling, we also show that fire influences the relative dominance of microbial inoculum and the vertical inheritance of the sapling microbiome from the parent tree. • Overall, our results demonstrate how fire impacts plant microbiome assembly, diversity, and composition and highlights potential for further research towards increasing plant fitness and ecosystem recovery after fire events.

Root carbon (C) inputs may regulate decomposition rates in soil, and in this study we ask: how do labile C inputs regulate decomposition of plant residues, and soil microbial communities? In a 14 d laboratory incubation, we added C compounds often found in root exudates in seven different concentrations (0, 0.7, 1.4, 3.6, 7.2, 14.4 and 21.7 mg C g⁻¹ soil) to soils amended with and without ¹³C-labeled plant residue. We measured CO₂ respiration and shifts in relative fungal and bacterial rRNA gene copy numbers using quantitative polymerase chain reaction (qPCR). Increased labile C input enhanced total C respiration, but only addition of C at low concentrations (0.7 mg C g⁻¹) stimulated plant residue decomposition (+2%). Intermediate concentrations (1.4, 3.6 mg C g⁻¹) had no impact on plant residue decomposition, while greater concentrations of C (> 7.2 mg C g⁻¹) reduced decomposition (-50%). Concurrently, high exudate concentrations (> 3.6 mg C g⁻¹) increased fungal and bacterial gene copy numbers, whereas low exudate concentrations (< 3.6 mg C g⁻¹) increased metabolic activity rather than gene copy numbers. These results underscore that labile soil C inputs can regulate decomposition of more recalcitrant soil C by controlling the activity and relative abundance of fungi and bacteria.

• While recent reports demonstrate that the direct emission of methane from living tree trunks may be a significant terrestrial emission source, there has been debate whether tree emissions are due to transport from soils or produced in the wood environment itself. Reports of methanogens from wood of trees were prominent in the literature 40 years ago but have not been revisited with molecular ecology approaches. • We examined communities associated with Populus deltoides using rRNA gene sequence analyses and how these vary with tree and wood properties. • Our data indicate that wood environments are dominated by anaerobic microbiomes. Methanogens are prominent in heartwood (mean 34% relative abundance) compared to sapwood environments (13%), and dominant operational taxonomic units (OTUs) were classified as the Methanobacterium sp. Members of the Firmicutes phylum comprised 39% of total sequences and were in 42% greater abundance in sapwood over heartwood niches. Tree diameter was the strongest predictor of methanogen abundance, but wood moisture content and pH were also significant predictors of taxon abundance and overall community composition. • Unlike microbiomes of the soil, rhizosphere and phyllosphere, wood associated communities are shaped by unique environmental conditions and may be prominent and overlooked sources of methane emissions in temperate forest systems.

Climate feedbacks from soils can result from environmental change followed by response of plant and microbial communities, and/or associated changes in nutrient cycling. Explicit consideration of microbial life-history traits and functions may be necessary to predict climate feedbacks owing to changes in the physiology and community composition of microbes and their associated effect on carbon cycling. Here we developed the microbial enzyme-mediated decomposition (MEND) model by incorporating microbial dormancy and the ability to track multiple isotopes of carbon. We tested two versions of MEND, that is, MEND with dormancy (MEND) and MEND without dormancy (MEND_wod), against long-term (270 days) carbon decomposition data from laboratory incubations of four soils with isotopically labeled substrates. MEND_wod adequately fitted multiple observations (total C–CO 2 and 14 C–CO 2 respiration, and dissolved organic carbon), but at the cost of significantly underestimating the total microbial biomass. MEND improved estimates of microbial biomass by 20–71% over MEND_wod. We also quantified uncertainties in parameters and model simulations using the Critical Objective Function Index method, which is based on a global stochastic optimization algorithm, as well as model complexity and observational data availability. Together our model extrapolations of the incubation study show that long-term soil incubations with experimental data for multiple carbon pools are conducive to estimate both decomposition and microbial parameters. These efforts should provide essential support to future field- and global-scale simulations, and enable more confident predictions of feedbacks between environmental change and carbon cycling.

Dormancy is an essential strategy for microorganisms to cope with environmental stress. However, global ecosystem models typically ignore microbial dormancy, resulting in notable model uncertainties. To facilitate the consideration of dormancy in these large-scale models, we propose a new microbial physiology component that works for a wide range of substrate availabilities. This new model is based on microbial physiological states and the major parameters are the maximum specific growth and maintenance rates of active microbes and the ratio of dormant to active maintenance rates. A major improvement of our model over extant models is that it can explain the low active microbial fractions commonly observed in undisturbed soils. Our new model shows that the exponentially-increasing respiration from substrate-induced respiration experiments can only be used to determine the maximum specific growth rate and initial active microbial biomass, while the respiration data representing both exponentially-increasing and non-exponentially-increasing phases can robustly determine a range of key parameters including the initial total live biomass, initial active fraction, the maximum specific growth and maintenance rates, and the half-saturation constant. Our new model can be incorporated into existing ecosystem models to account for dormancy in microbially-driven processes and to provide improved estimates of microbial activities.

Background Plants have developed defense strategies for phytopathogen and herbivore protection via coordinated metabolic mechanisms. Low-molecular weight metabolites produced within plant tissues, such as salicylic acid, represent one such mechanism which likely mediates plant – microbe interactions above and below ground. Salicylic acid is a ubiquitous phytohormone at low levels in most plants, yet are concentrated defense compounds in Populus , likely acting as a selective filter for rhizosphere microbiomes. We propagated twelve Populus trichocarpa genotypes which varied an order of magnitude in salicylic acid (SA)-related secondary metabolites, in contrasting soils from two different origins. After four months of growth, plant properties (leaf growth, chlorophyll content, and net photosynthetic rate) and plant root metabolomics specifically targeting SA metabolites were measured via GC-MS. In addition, rhizosphere microbiome composition was measured via Illumina MiSeq sequencing of 16S and ITS2 rRNA-genes. Results Soil origin was the primary filter causing divergence in bacterial/archaeal and fungal communities with plant genotype secondarily influential. Both bacterial/archaeal and fungal evenness varied between soil origins and bacterial/archaeal diversity and evenness correlated with at least one SA metabolite (diversity: populin; evenness: total phenolics). The production of individual salicylic acid derivatives that varied by host genotype resulted in compositional differences for bacteria /archaea (tremuloidin) and fungi (salicylic acid) within one soil origin (Clatskanie) whereas soils from Corvallis did not illicit microbial compositional changes due to salicylic acid derivatives. Several dominant bacterial (e.g., Betaproteobacteria, Acidobacteria, Verrucomicrobia, Chloroflexi, Gemmatimonadete, Firmicutes ) and one fungal phyla ( Mortierellomycota ) also correlated with specific SA secondary metabolites; bacterial phyla exhibited more negative interactions (declining abundance with increasing metabolite concentration) than positive interactions. Conclusions These results indicate microbial communities diverge most among soil origin. However, within a soil origin, bacterial/archaeal communities are responsive to plant SA production within greenhouse-based rhizosphere microbiomes. Fungal microbiomes are impacted by root SA-metabolites, but overall to a lesser degree within this experimental context. These results suggest plant defense strategies, such as SA and its secondary metabolites, may partially drive patterns of both bacterial/archaeal and fungal taxa-specific colonization and assembly.

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., > 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. As the climate warms, soil carbon stores will likely be degraded by microbes and released as CO 2 , but these predictions are based on laboratory incubations that might not reflect real rates. Here the authors optimize model projections using dozens of short- and long-term incubations in forest and grasslands.