Despite significant advances in microbiome research across various environments1, the microbiome of Earth's largest biomass reservoir-the wood of living trees2-remains largely unexplored. Here, we illuminate the microbiome inhabiting and adapted to wood and further specialized to individual host tree species, revealing that wood is a harbour of biodiversity and potential key players in tree health and forest ecosystem functions. We demonstrate that a single tree hosts approximately one trillion bacteria in its woody tissues, with microbial communities distinctly partitioned between heartwood and sapwood, each maintaining unique microbiomes with minimal similarity to other plant tissues or ecosystem components. The heartwood microbiome emerges as a particularly unique ecological niche, distinguished by specialized archaea and anaerobic bacteria driving consequential biogeochemical processes. Our findings support the concept of plants as 'holobionts'3,4-integrated ecological units of host and associated microorganisms-with implications for tree health, disease and functionality. By characterizing the composition, structure and functions of tree internal microbiomes, our work opens up pathways for understanding tree physiology and forest ecology and establishes a new frontier in environmental microbiology.

Litter decomposition is an important ecosystem process and global carbon flux that has been shown to be controlled by climate, litter quality, and microbial communities. Process-based ecosystem models are used to predict responses of litter decomposition to climate change. While these models represent climate and litter quality effects on litter decomposition, they have yet to integrate empirical microbial community data into their parameterizations for predicting litter decomposition. To fill this gap, our research used a comprehensive leaf litterbag decomposition experiment at 10 temperate forest U.S. National Ecological Observatory Network (NEON) sites to calibrate (7 sites) and validate (3 sites) the MIcrobial-MIneral Carbon Stabilization (MIMICS) model. MIMICS was calibrated to empirical decomposition rates and to their empirical drivers, including the microbial community (represented as the copiotroph-to-oligotroph ratio). We calibrate to empirical drivers, rather than solely rates or pool sizes, to improve the underlying drivers of modeled leaf litter decomposition. We then validated the calibrated model and evaluated the effects of calibration under climate change using the SSP 3-7.0 climate change scenario. We find that incorporating empirical drivers of litter decomposition provides similar, and sometimes better (in terms of goodness-of-fit metrics), predictions of leaf litter decomposition but with different underlying ecological dynamics. For some sites, calibration also increased climate change-induced leaf litter mass loss by up to 5%, with implications for carbon cycle-climate feedbacks. Our work also provides an example for integrating data on the relative abundance of bacterial functional groups into an ecosystem model using a novel calibration method to bridge empiricism and process-based modeling, answering a call for the use of empirical microbial community data in process-based ecosystem models. We highlight that incorporating mechanistic information into models, as done in this study, is important for improving confidence in model projections of ecological processes like litter decomposition under climate change.

Animals exert control over biogeochemical processes within their ecosystems - the study of which is called zoogeochemistry. However, most zoogeochemical research stops short of examining how animal-driven biogeochemical processes feed back to influence the fitness and population dynamics of organisms. We outline how to use niche construction theory to investigate these feedbacks, introducing zoogeochemical niche construction to explicitly link zoogeochemistry with fitness and evolution trajectories. We specifically highlight how this framework reveals the capacity of animals to influence their own nutritional landscapes, creating closed zoogeochemical loops. To identify and test instances of zoogeochemical niche construction, we present experimental, correlative, and comparative tools. The novel application of niche construction theory provides alternative and complementary explanations for animal trait evolution.

Nitrification is a key biogeochemical process, with higher rates indicative of higher soil nitrogen availability and potential nitrogen losses from soils to waterways and the atmosphere. Heterotrophic microbes and plants compete with nitrifiers for mineralized nitrogen, thereby influencing the fraction of ammonium converted by nitrifiers to nitrate. Higher soil carbon availability fuels heterotrophic microbial ammonium demand, which can weaken the positive relationship between net nitrogen mineralization and nitrification by limiting ammonium supply to nitrifiers. Whether soil carbon availability remains a central control on the coupling of these processes under altered plant nitrogen demand remains relatively unexplored even as disturbances that reduce plant biomass increase globally. Using partially disturbed forests that vary in aboveground biomass and soil carbon availability, we test the generalizability of microbially available carbon as a control on the coupling of net nitrogen mineralization and nitrification. We analyze differences between harvested and unharvested forest stands, changes over time since harvest, and the effects of retained overstory trees. Higher levels of disturbance consistently strengthened the positive relationship between net nitrogen mineralization and nitrification. Yet reduced plant biomass, rather than microbially available carbon, primarily mediated the coupling of these processes. Our findings suggest that plant-mediated nitrogen demand can be a stronger control on the decoupling of nitrogen mineralization and nitrification than heterotrophic soil microbes following partial canopy disturbances. These results have important implications for understanding coupled carbon and nitrogen cycling processes in forests globally, highlighting a need to consider how shifting disturbance regimes could influence controls on nitrification.

Causal approaches employed at the scale of commercial agriculture are required to build high-quality evidence that climate-smart agricultural interventions result in real emissions reductions and removals. Such project-scale empirical data are additionally required to demonstrate and advance the viability of process-based models and digital measurement, reporting and verification as tools to scale soil carbon accounting.

Agricultural carbon crediting predominantly relies on process-based biogeochemical models to estimate accrual of soil organic carbon stock (SOC). We investigate the conditions under which it may be economical to estimate SOC accrual by measuring and remeasuring SOC, which relies on fewer assumptions than modeling. We analyze multi-field measure-and-remeasure SOC projects with two key features: first, practice assignment is randomized to compare the effect of a treatment (e.g. no tillage) to a control (e.g. conventional tillage); second, a random subset of fields is sampled (two stage cluster sampling) to cost-effectively measure SOC changes. We use statistical modeling to characterize the estimated treatment effect, accounting for within-field and between-field variability in SOC change, as well as measurement error. We then use these statistics to evaluate how prices for measurement, treatment, and carbon credits influence the economics of measure-and-remeasure projects. We specifically investigate the potential advantages of larger spatial scale (number of fields) and temporal scale (years before remeasurement). We find economies of both spatial and temporal scale so that projects with thousands of fields, with only about 10% of fields measured for SOC change, are likely to yield a competitive return on investment in five years if the treatment effects found in the research literature can be achieved commercially. Our analysis suggests that measure-and-remeasure can be cost effective in both market and non-market SOC projects at scale. Moreover, measure-and-remeasure projects provide valuable data for independent validation on commercial farms of the accrual rates estimated by biogeochemical models using field trials. We provide next steps and software for researchers, credit registries, and project developers to move forward with measure-and-remeasure SOC projects.

Urban natural area forests provide cities with crucial ecosystem services, including carbon storage and sequestration. Although previous work from a single city has suggested that urban natural area forests may be carbon-rich and dominated by native species, it is unclear if that pattern is widespread. Indeed, little is known about the species composition and carbon storage in these green spaces, or how urban natural area forests compared with similar rural forests. Here, we use data collected by the Forests in Cities network to quantify carbon stored in urban natural area forests across 1852 plots in eight of the most populous US cities and examine patterns in woody vegetation carbon storage by tree species composition and size class. We also compare the carbon storage in these urban natural area forests to similar rural forests using USDA FS Forest Inventory and Analysis data. We found that urban natural area forests store between 214 and 267 Mg C ha-1, with the majority (on average 55%) in the above-ground portion of live trees and shrubs. This carbon was primarily stored by native trees and increased with the proportion of native species, as native trees tended to be larger. The proportion of non-native species was higher in smaller size classes. Overall, the woody vegetation carbon density in urban natural area forests was higher than similar forest types in rural settings, a phenomenon driven by the presence of more large trees. Synthesis and applications: Together these results demonstrate the importance of urban natural area forests as carbon-dense ecosystems and havens for native tree species. However, because of the greater number of non-native species in smaller size classes, these forests may also be at risk of transitioning away from native-dominated systems. Therefore, greater monitoring efforts and increased management activities such as non-native species removal will be crucial to maintaining the high carbon storage and health of these ecosystems.

Quantitative data at real-world scales are needed to assess the effects of cover cropping and other practices on soil carbon storage. Large-scale medical studies provide a proven methodology.

Forests provide multiple benefits that include sequestering carbon, supporting biodiversity, and providing wood products. Managing temperate forests to achieve these benefits sustainably is challenging given the legacy of past human impacts, the complexity of forest development, and increasing but unpredictable disturbances. These intricacies prompted debate about the most effective management of temperate forests to achieve climate mitigation while sustaining forest productivity, regeneration, and diversity. Most research focused on management impacts under relatively stable environmental conditions, whereas forests are facing increasingly frequent and more severe climatic and biotic disturbances. Here, we used a regionally calibrated forest growth model to simulate the effects of forest management on carbon, biodiversity, and wood production under prevalent natural disturbances in the northeastern US. We developed scenarios combining forest management and disturbance regimes based on assumptions of species-specific tree regeneration and mortality rates. We compared passive management with no cutting that prioritizes maintaining existing forest trees with two common regional harvest practices: exploitative timber harvest that prioritizes short-term wood production and regenerative timber harvest that prioritizes regenerating biodiverse native forest tree seedlings. In the absence of natural disturbance, no cutting provides 41% higher forest carbon storage and 50% higher tree structural diversity after 100 years than exploitative or regenerative practices. The presence of drought, windstorm, pest, and disease disturbances altered these outcomes. Regenerative forest management provides 25% higher forest carbon storage and 26% higher tree structural diversity after 100 years than no cutting. Our results demonstrate that wood products and their carbon storage and fossil emission avoidance are important for determining the total climate benefits of forest management under natural disturbances. Our findings highlight that natural disturbance regimes should be considered when selecting management to promote multiple forest benefits, suggesting the need for tailored as opposed to one-size-fits-all policies to sustainably manage temperate forests worldwide.

In mature forests, tree and shrub mycorrhizal associations integrate plant and fungal functional traits, making these relationships important controls on soil nitrogen availability. Whether these plant-fungal effects are observed in forests during early succession following disturbances is largely unexplored. We quantify differences in soil nitrogen availability under an ectomycorrhizal tree (Betula lenta) and an ericoid mycorrhizal shrub (Kalmia latifolia) and explore the potential for known mechanisms, such as the availability of soil carbon, to explain the patterns observed. We analyze variables indicative of soil nitrogen and carbon availability for incubated soil samples collected from under ecto- or ericoid mycorrhizal plants within a recently harvested temperate forest. Specific measures include net nitrogen mineralization, nitrification, and carbon mineralization rates; active microbial biomass; particulate and mineral-associated soil organic carbon and nitrogen concentrations; and carbon and nitrogen concentrations in plant tissues. Net nitrogen mineralization and nitrification rates were lower under ericoid shrubs than ectomycorrhizal trees. Soil carbon availabilities were similar, suggesting that mechanisms other than carbon accumulation likely create nitrogen limitation under the ericoid shrub in early successional forests. Ectomycorrhizal plant tissues also had higher nitrogen contents and lower carbon-to-nitrogen ratios than ericoid shrubs, providing further support for greater soil nitrogen limitation in the ericoid plots. Our findings suggest local heterogeneity of plant mycorrhizal associations, or at least plant functional types, will be important for understanding differences in soil nitrogen availability in early versus mid- to late-successional forests and hence forest ecosystem responses to intensifying disturbance regimes.

Differences between arbuscular (AM) and ectomycorrhizal (EcM) trees strongly influence forest ecosystem processes, in part through their impact on saprotrophic fungal communities. Ericoid mycorrhizal (ErM) shrubs likely also impact saprotrophic communities given that they can shape nutrient cycling by slowing decomposition rates and intensifying nitrogen limitation. We investigated the depth distributions of saprotrophic and EcM fungal communities in paired subplots with and without a common understory ErM shrub, mountain laurel (Kalmia latifolia L.), across an AM to EcM tree dominance gradient in a temperate forest by analyzing soils from the organic, upper mineral (0-10 cm), and lower mineral (cumulative depth of 30 cm) horizons. The presence of K. latifolia was strongly associated with the taxonomic and functional composition of saprotrophic and EcM communities. Saprotrophic richness was consistently lower in the Oa horizon when this ErM shrub species was present. However, in AM tree-dominated plots, the presence of the ErM shrub was associated with a higher relative abundance of saprotrophs. Given that EcM trees suppress both the diversity and relative abundance of saprotrophic communities, our results suggest that separate consideration of ErM shrubs and EcM trees may be necessary when assessing the impacts of plant mycorrhizal associations on belowground communities. Shrubs that associate with ericoid mycorrhizal fungi are found to affect saprotrophic and ectomycorrhizal fungi that vary depending on tree mycorrhizal association.

Animals interact with nutrient cycles by consuming and depositing nutrients, interactions studied separately in nutritional ecology and zoogeochemistry. Recent theoretical work bridges these disciplines, highlighting that animal-driven nutrient recycling could be crucial in helping animals meet their nutritional needs. When animals exhibit site fidelity, they consistently deposit nutrients, potentially improving vegetation quality. We investigated this potential feedback by analysing changes in forage nitrogen stocks following simulated caribou calving. We found that forage nitrogen stocks increased after 2 weeks and remained elevated after 1 year, a change due to increased forage quality, not quantity. We also developed a nutrient budget within calving grounds, demonstrating that natal fluid and calf carcasses contribute substantial nitrogen subsidies. We, thus, highlight a positive zoogeochemical feedback whereby nutrients deposited during calving become bioavailable during lactation and provide evidence that site fidelity creates a biogeochemical boomerang in which animals deposit nutrients that can be reused later.

Mineral-associated soil organic matter (MAOM) is the largest, slowest cycling pool of carbon (C) in the terrestrial biosphere. MAOM is primarily derived from plant and microbial sources, yet the relative contributions of these two sources to MAOM remain unresolved. Resolving this issue is essential for managing and modeling soil carbon responses to environmental change. Microbial biomarkers, particularly amino sugars, are the primary method used to estimate microbial versus plant contributions to MAOM, despite systematic biases associated with these estimates. There is a clear need for independent lines of evidence to help determine the relative importance of plant versus microbial contributions to MAOM. Here, we synthesized 288 datasets of C/N ratios for MAOM, particulate organic matter (POM), and microbial biomass across the soils of forests, grasslands, and croplands. Microbial biomass is the source of microbial residues that form MAOM, whereas the POM pool is the direct precursor of plant residues that form MAOM. We then used a stoichiometric approach-based on two-pool, isotope-mixing models-to estimate the proportional contribution of plant residue (POM) versus microbial sources to the MAOM pool. Depending on the assumptions underlying our approach, microbial inputs accounted for between 34% and 47% of the MAOM pool, whereas plant residues contributed 53%-66%. Our results therefore challenge the existing hypothesis that microbial contributions are the dominant constituents of MAOM. We conclude that biogeochemical theory and models should account for multiple pathways of MAOM formation, and that multiple independent lines of evidence are required to resolve where and when plant versus microbial contributions are dominant in MAOM formation.

Managing for structural complexity to enhance forest health and resiliency is increasingly incorporated in silvicultural treatments. High spatial variability in stands managed for structural complexity could obscure forest management effects on surface soils. Yet few studies have assessed how within-stand variation in forest structure and other local controls influence the effects of timber harvesting on surface soil organic matter dynamics over time. We used a stratified random sampling design to capture variation in stand age, legacy structure, soil type, and topography in a second-growth, oak-hardwood forest in the northeastern U.S. We compared surface soil carbon and nitrogen content and availability in 15 harvested stands managed to promote tree regeneration (n = 144 plots) and five unharvested controls (n = 48 plots). We also examined changes over time since harvest in just the harvested stands using a 25-year chronosequence. Timber harvesting strongly influenced surface soil carbon and nitrogen dynamics. The harvested stands had lower soil carbon and nitrogen, microbial biomass, and carbon mineralization but higher nitrogen mineralization. These differences were more pronounced in the drier soil type with higher organic matter content than in the more moist soil type. Across the 25-year chronosequence, elevation, soil type, and downed woody material density dictated the direction of changes in surface soil carbon and nitrogen over time. Soil carbon and nitrogen accrued over time at drier, higher elevation (similar to 300 m) sites and was positively associated with higher densities of fine woody material but declined at lower elevations (similar to 180 m). Proximity to legacy trees was associated with higher soil carbon and nitrogen concentrations and availability. Our findings underscore the importance of silvicultural practices that retain structural legacies in shaping surface soil carbon and nitrogen dynamics over time. Our results also highlight how accounting for spatial variation in local controls on soil carbon and nitrogen, such as topography, can improve detection of changes from forest management practices that increase spatial heterogeneity within stands, such as irregular shelterwood and seed tree regeneration methods.

Background As interest in the voluntary soil carbon market surges, carbon registries have been developing new soil carbon measurement, reporting, and verification (MRV) protocols. These protocols are inconsistent in their approaches to measuring soil organic carbon (SOC). Two areas of concern include the type of SOC stock accounting method (fixed-depth (FD) vs. equivalent soil mass (ESM)) and sampling depth requirement. Despite evidence that fixed-depth measurements can result in error because of changes in soil bulk density and that sampling to 30 cm neglects a significant portion of the soil profile’s SOC stock, most MRV protocols do not specify which sampling method to use and only require sampling to 30 cm. Using data from UC Davis’s Century Experiment (“Century”) and UW Madison’s Wisconsin Integrated Cropping Systems Trial (WICST), we quantify differences in SOC stock changes estimated by FD and ESM over 20 years, investigate how sampling at-depth (> 30 cm) affects SOC stock change estimates, and estimate how crediting outcomes taking an empirical sampling-only crediting approach differ when stocks are calculated using ESM or FD at different depths. Results We find that FD and ESM estimates of stock change can differ by over 100 percent and that, as expected, much of this difference is associated with changes in bulk density in surface soils (e.g., r = 0.90 for Century maize treatments). This led to substantial differences in crediting outcomes between ESM and FD-based stocks, although many treatments did not receive credits due to declines in SOC stocks over time. While increased variability of soils at depth makes it challenging to accurately quantify stocks across the profile, sampling to 60 cm can capture changes in bulk density, potential SOC redistribution, and a larger proportion of the overall SOC stock. Conclusions ESM accounting and sampling to 60 cm (using multiple depth increments) should be considered best practice when quantifying change in SOC stocks in annual, row crop agroecosystems. For carbon markets, the cost of achieving an accurate estimate of SOC stocks that reflect management impacts on soils at-depth should be reflected in the price of carbon credits.

The opportunity of agricultural management practices to sequester soil organic carbon (SOC) is recognized as an important strategy for mitigating climate change. However, there is low confidence when it comes to understanding the magnitude of the climate benefit we can expect from SOC sequestration or how best to achieve it. Several issues are often confounded when it comes to the mitigation potential of SOC sequestration and greenhouse gas (GHG) reductions from agriculture, creating confusion and making it difficult to clearly identify the knowns, unknowns and risks to implementing policy and practice recommendations. Here, we identify and explain four major areas of uncertainty: (1) the expected changes in soil carbon or GHG emissions resulting from agricultural management practice changes; (2) the extent to which social, environmental and economic factors constrain mitigation potential; (3) the ability to execute reliable measurement, monitoring, reporting and verification (MMRV) frameworks; and (4) the perception of risk associated with different ways of promoting practice adoption (e.g., voluntary carbon markets fueled by the private sector, pay-for-practice programs funded by public investment). We aim to pinpoint knowledge gaps and areas of disagreement to help right-size expectations and guide effective investment in GHG removals and reductions from agriculture.

In their Letter‐to‐Editor, Liu & Chen (2024) raised the importance and suitability of our recent stoichiometric approach to assess the contribution of plant residue (litter) and microbial sources to mineral‐associated organic matter (MAOM). We highly appreciate their Letter as well as the further suggestion and comments and offer two points of clarification. We call for staying aware of methodological benefits and limitations of each approach, and further develop and compare multiple methods to develop a clearer picture of where and to what extent MAOM is formed from direct vs. indirect (via the microbial funnel) plant inputs.

Efforts to characterize microbial life across diverse environments have progressed tremendously, yet the microbiome of Earth's largest biomass reservoir-the wood of living trees-has been largely unexplored. Current understanding of the tree microbiome is largely confined to roots and leaves, with little attention given to the endophytic microbiome of wood, even though emergent studies have indicated this zone as a niche for unique taxa, of consequence for ecosystem health and global biogeochemical cycles. The lack of investigation derives partly from the physical recalcitrance of wood, which presents challenges during sampling, homogenization, and the extraction of nucleic acids. In response to these issues, we present an optimized method for processing wood for use in microbial analyses, from sampling through to downstream analyses. Using methane-cycling taxa as model endophytes, we assess losses in recovery during our method, and determine a limit-of-detection of approximately 500 cells per 100 mg of (dry) wood. For all six species evaluated-which represented several diverse taxa of hardwoods and softwoods-PCR inhibition proved minimal, and we expect this method to be applicable for a majority of tree species. The methods presented herein can facilitate future investigation into the wood microbiome and global microbial ecology of methane cycling.