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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Climate change–induced stress disrupts ectomycorrhizal interaction networks at the boreal–temperate ecotone

The interaction networks formed by ectomycorrhizal fungi (EMF) and their tree hosts, which are important to both forest recruitment and ecosystem carbon and nutrient retention, may be particularly susceptible to climate change at the boreal–temperate forest ecotone where environmental conditions are changing rapidly. Here, we quantified the compositional and functional trait responses of EMF communities and their interaction networks with two boreal ( Pinus banksiana and Betula papyrifera ) and two temperate ( Pinus strobus and Quercus macrocarpa ) hosts to a factorial combination of experimentally elevated temperatures and reduced rainfall in a long-term open-air field experiment. The study was conducted at the B4WarmED (Boreal Forest Warming at an Ecotone in Danger) experiment in Minnesota, USA, where infrared lamps and buried heating cables elevate temperatures (ambient, +3.1 °C) and rain-out shelters reduce growing season precipitation (ambient, ~30% reduction). EMF communities were characterized and interaction networks inferred from metabarcoding of fungal-colonized root tips. Warming and rainfall reduction significantly altered EMF community composition, leading to an increase in the relative abundance of EMF with contact-short distance exploration types. These compositional changes, which likely limited the capacity for mycelial connections between trees, corresponded with shifts from highly redundant EMF interaction networks under ambient conditions to less redundant (more specialized) networks. Further, the observed changes in EMF communities and interaction networks were correlated with changes in soil moisture and host photosynthesis. Collectively, these results indicate that the projected changes in climate will likely lead to significant shifts in the traits, structure, and integrity of EMF communities as well as their interaction networks in forest ecosystems at the boreal–temperate ecotone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Increasing Functional Diversity in a Global Land Surface Model Illustrates Uncertainties Related to Parameter Simplification

Abstract Simulations of the land surface carbon cycle typically compress functional diversity into a small set of plant functional types (PFT), with parameters defined by the average value of measurements of functional traits. In most earth system models, all wild plant life is represented by between five and 14 PFTs and a typical grid cell (≈100 × 100 km) may contain a single PFT. Model logic applied to this coarse representation of ecological functional diversity provides a reasonable proxy for the carbon cycle, but does not capture the non‐linear influence of functional traits on productivity. Here we show through simulations using the Energy Exascale Land Surface Model in 15 diverse terrestrial landscapes, that better accounting for functional diversity markedly alters predicted total carbon uptake. The shift in carbon uptake is as great as 30% and 10% in boreal and tropical regions, respectively, when compared to a single PFT parameterized with the trait means. The traits that best predict gross primary production vary based on vegetation phenology, which broadly determines where traits fall within the global distribution. Carbon uptake is more closely associated with specific leaf area for evergreen PFTs and the leaf carbon to nitrogen ratio in deciduous PFTs.

58 GEOSCIENCES↗
DOE OSTI2023

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Abstract Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integratesin-situmeasurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697µmolCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Environmental Sciences & Ecology↗
DOE OSTI2022

A 2-million-year-old ecosystem in Greenland uncovered by environmental DNA

Late Pliocene and Early Pleistocene epochs 3.6 to 0.8 million years ago had climates resembling those forecasted under future warming. Palaeoclimatic records show strong polar amplification with mean annual temperatures of 11–19 °C above contemporary values. The biological communities inhabiting the Arctic during this time remain poorly known because fossils are rare. Here we report an ancient environmental DNA (eDNA) record describing the rich plant and animal assemblages of the Kap København Formation in North Greenland, dated to around two million years ago. The record shows an open boreal forest ecosystem with mixed vegetation of poplar, birch and thuja trees, as well as a variety of Arctic and boreal shrubs and herbs, many of which had not previously been detected at the site from macrofossil and pollen records. The DNA record confirms the presence of hare and mitochondrial DNA from animals including mastodons, reindeer, rodents and geese, all ancestral to their present-day and late Pleistocene relatives. The presence of marine species including horseshoe crab and green algae support a warmer climate than today. The reconstructed ecosystem has no modern analogue. The survival of such ancient eDNA probably relates to its binding to mineral surfaces. Our findings open new areas of genetic research, demonstrating that it is possible to track the ecology and evolution of biological communities from two million years ago using ancient eDNA.

58 GEOSCIENCES↗
DOE OSTI2021

Seasonal calibration of the end-cretaceous Chicxulub impact event

The end-Cretaceous Chicxulub impact triggered Earth’s last mass-extinction, extinguishing ~ 75% of species diversity and facilitating a global ecological shift to mammal-dominated biomes. Temporal details of the impact event on a fine scale (hour-to-day), important to understanding the early trajectory of mass-extinction, have largely eluded previous studies. This study employs histological and histo-isotopic analyses of fossil fish that were coeval with a unique impact-triggered mass-death assemblage from the Cretaceous-Paleogene (KPg) boundary in North Dakota (USA). Patterns of growth history, including periodicity of δ 18 O and δ 13 C and growth band morphology, plus corroborating data from fish ontogeny and seasonal insect behavior, reveal that the impact occurred during boreal Spring/Summer, shortly after the spawning season for fish and most continental taxa. The severity and taxonomic symmetry of response to global natural hazards are influenced by the season during which they occur, suggesting that post-impact perturbations could have exerted a selective force that was exacerbated by seasonal timing. Data from this study can also provide vital hindsight into patterns of extant biotic response to global-scale hazards that are relevant to both current and future biomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Reducing uncertainty of high-latitude ecosystem models through identification of key parameters

Abstract Climate change is having significant impacts on Earth’s ecosystems and carbon budgets, and in the Arctic may drive a shift from an historic carbon sink to a source. Large uncertainties in terrestrial biosphere models (TBMs) used to forecast Arctic changes demonstrate the challenges of determining the timing and extent of this possible switch. This spread in model predictions can limit the ability of TBMs to guide management and policy decisions. One of the most influential sources of model uncertainty is model parameterization. Parameter uncertainty results in part from a mismatch between available data in databases and model needs. We identify that mismatch for three TBMs, DVM-DOS-TEM, SIPNET and ED2, and four databases with information on Arctic and boreal above- and belowground traits that may be applied to model parametrization. However, focusing solely on such data gaps can introduce biases towards simple models and ignores structural model uncertainty, another main source for model uncertainty. Therefore, we develop a causal loop diagram (CLD) of the Arctic and boreal ecosystem that includes unquantified, and thus unmodeled, processes. We map model parameters to processes in the CLD and assess parameter vulnerability via the internal network structure. One important substructure, feed forward loops (FFLs), describe processes that are linked both directly and indirectly. When the model parameters are data-informed, these indirect processes might be implicitly included in the model, but if not, they have the potential to introduce significant model uncertainty. We find that the parameters describing the impact of local temperature on microbial activity are associated with a particularly high number of FFLs but are not constrained well by existing data. By employing ecological models of varying complexity, databases, and network methods, we identify the key parameters responsible for limited model accuracy. They should be prioritized for future data sampling to reduce model uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Intensive aerosol properties of boreal and regional biomass burning aerosol at Mt. Bachelor Observatory: larger and black carbon (BC)-dominant particles transported from Siberian wildfires

We characterize the aerosol physical and optical properties of 13 transported biomass burning (BB) events. BB events included long-range influence from fires in Alaskan and Siberian boreal forests transported to Mt. Bachelor Observatory (MBO) in the free troposphere (FT) over 8–14+ d and regional wildfires in northern California and southwestern Oregon transported to MBO in the boundary layer (BL) over 10 h to 3 d. Intensive aerosol optical properties and normalized enhancement ratios for BB events were derived from measured aerosol light scattering coefficients (σ scat ), aerosol light-absorbing coefficients (σ abs ), fine particulate matter (PM 1 ), and carbon monoxide (CO) measurements made from July to September 2019, with particle size distribution collected from August to September. The observations showed that the Siberian BB events had a lower scattering Ångström exponent (SAE), a higher mass scattering efficiency (MSE; Δσ scat /ΔPM 1 ), and a bimodal aerosol size distribution with a higher geometric mean diameter (D g ). We hypothesize that the larger particles and associated scattering properties were due to the transport of fine dust alongside smoke in addition to contributions from condensation of secondary aerosol, coagulation of smaller particles, and aqueous-phase processing during transport. Alaskan and Siberian boreal forest BB plumes were transported long distances in the FT and characterized by lower absorption Ångström exponent (AAE) values indicative of black carbon (BC) dominance in the radiative budget. Significantly elevated AAE values were only observed for BB events with <1 d transport, which suggests strong production of brown carbon (BrC) in these plumes but limited radiative forcing impacts outside of the immediate region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Long-Term Changes in Concentration and Yield of Riverine Dissolved Silicon From the Poles to the Tropics

Riverine exports of silicon (Si) influence global carbon cycling through the growth of marine diatoms, which account for ~25% of global primary production. Climate change will likely alter river Si exports in biome-specific ways due to interacting shifts in chemical weathering rates, hydrologic connectivity, and metabolic processes in aquatic and terrestrial systems. Nonetheless, factors driving long-term changes in Si exports remain unexplored at local, regional, and global scales. We evaluated how concentrations and yields of dissolved Si (DSi) changed over the last several decades of rapid climate warming using long-term data sets from 60 rivers and streams spanning the globe (e.g., Antarctic, tropical, temperate, boreal, alpine, Arctic systems). We show that widespread changes in river DSi concentration and yield have occurred, with the most substantial shifts occurring in alpine and polar regions. The magnitude and direction of trends varied within and among biomes, were most strongly associated with differences in land cover, and were often independent of changes in river discharge. These findings indicate that there are likely diverse mechanisms driving change in river Si biogeochemistry that span the land-water interface, which may include glacial melt, changes in terrestrial vegetation, and river productivity. Finally, trends were often stronger in months outside of the growing season, particularly in temperate and boreal systems, demonstrating a potentially important role of shifting seasonality for the flux of Si from rivers. Our results have implications for the timing and magnitude of silica processing in rivers and its delivery to global oceans.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Tower-Based Remote Sensing Reveals Mechanisms Behind a Two-phased Spring Transition in a Mixed-Species Boreal Forest

The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower-based remotely sensed data (reflectance-based vegetation indices and Solar-Induced Chlorophyll Fluorescence [SIF]), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this data set shows a two-phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures, and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll-Carotenoid Index. Deciduous leaf-out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two-phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite-based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Intra‐species genetic variability drives carbon metabolism and symbiotic host interactions in the ectomycorrhizal fungus Pisolithus microcarpus

Summary Ectomycorrhizal (ECM) fungi are integral to boreal and temperate forest ecosystem functioning and nutrient cycling. ECM fungi, however, originate from diverse saprotrophic lineages and the impacts of genetic variation across species, and especially within a given ECM species, on function and interactions with the environment is not well understood. Here, we explore the extent of intra‐species variation between four isolates of the ECM fungus Pisolithus microcarpus , in terms of gene regulation, carbon metabolism and growth, and interactions with a host, Eucalyptus grandis . We demonstrate that, while a core response to the host is maintained by all of the isolates tested, they have distinct patterns of gene expression and carbon metabolism, resulting in the differential expression of isolate‐specific response pathways in the host plant. Together, these results highlight the importance of using a wider range of individuals within a species to understand the broader ecological roles of ECM fungi and their host interactions.

Plett, Krista L.↗
DOE OSTI2023

Projections of wildfire risk and activities under 1.5 °C and 2.0 °C global warming scenarios

Wildfires are important ecosystem processes that have a significant impact on terrestrial vegetation, environment, and climate. This study investigates how future wildfire risk and activities could change under 1.5 °C and 2.0 °C warming scenarios relative to pre-industrial levels using a modified McArthur Forest Fire Danger Index (FFDIn) and the CLM4.5-BGC land surface model. Sixteen Earth System Models (ESMs) from CMIP5 and CMIP6 were employed to supply the variables of climate change under low, middle, and high greenhouse emission scenarios in the 1.5 °C and 2.0 °C scenarios. The ensemble means from the FFDIn and results from the CLM4.5-BGC with multiple forcings show that the dry areas in the southwestern US, Brazilian Highlands, and Arabian islands are projected to face higher wildfire risk with larger burned areas and more carbon emissions under a warmer climate. The Congo Basin and part of the Amazon could have a lower wildfire risk with smaller burned areas and less carbon emissions. The absolute changes in the projected FFDIn are small, although large increases are observed in boreal areas, particularly in the winter and spring. Burned area and carbon emissions are projected to increase in general in the boreal area but decrease in northeastern Asia. Compared to the 1.5 °C scenario, the wildfire risk and burned area levels are projected to increase under the 2.0 °C scenario except in the western Amazon. However, fire carbon emissions are projected to decrease more in tropical areas under the 2.0 °C scenario. The different change directions in eastern North America and eastern China produced by the FFDIn and CLM4.5-BGC suggest the potential effect of non-meteorological elements on fire activities.

1.5 °C and 2.0 °C warming↗
DOE OSTI2021

The temperature sensitivity of soil: microbial biodiversity, growth, and carbon mineralization

Abstract Microorganisms drive soil carbon mineralization and changes in their activity with increased temperature could feedback to climate change. Variation in microbial biodiversity and the temperature sensitivities (Q10) of individual taxa may explain differences in the Q10 of soil respiration, a possibility not previously examined due to methodological limitations. Here, we show phylogenetic and taxonomic variation in the Q10 of growth (5–35 °C) among soil bacteria from four sites, one from each of Arctic, boreal, temperate, and tropical biomes. Differences in the temperature sensitivities of taxa and the taxonomic composition of communities determined community-assembled bacterial growth Q10, which was strongly predictive of soil respiration Q10 within and across biomes. Our results suggest community-assembled traits of microbial taxa may enable enhanced prediction of carbon cycling feedbacks to climate change in ecosystems across the globe.

Wang, Chao (ORCID:0000000257567505)↗
DOE OSTI2025

Warming is Associated With More Encoded Antimicrobial Resistance Genes and Transcriptions Within Five Drug Classes in Soil Bacteria: A Case Study and Synthesis

ABSTRACT The effect of warming on anti‐microbial resistance (AMR) genes in the environment has critical implications for public health but is little studied. We collected published soil bacterial genomes from the BV‐BRC database and tested the correlation between reported optimal growth temperature and the number of encoded AMR genes. Furthermore, we tested the relationship between temperature and AMR gene transcription in a natural ecosystem by analysing soil transcriptomes from a warming manipulation experiment in an Alaskan boreal forest. We hypothesised that there is a positive relationship between warming and AMR prevalence in gene content in bacterial genomes and transcriptomic sequences, and that this effect would vary by drug class. Regarding the bacterial genomes, we found a positive relationship between the fraction of encoded AMR genes and the reported optimal temperature of soil bacteria. The drug classes tetracycline and lincosamide/macrolide/streptogramin had the strongest positive relationship with reported optimal temperature. For the case study in a natural ecosystem, we found 61 significantly upregulated AMR gene‐associated transcripts spanning eight drug classes in warmed plots. In the Alaskan soil samples, we found that warming elicited the strongest positive effect on transcripts targeting lincosamide/streptogramin, beta‐lactam and phenicol/quinolone antibiotics. Overall, higher temperatures were linked to AMR gene prevalence.

Hacopian, Melanie T. [Department of Ecology and Ev↗
DOE OSTI2020

Modeling Functional Organic Chemistry in Arctic Rivers: An Idealized Siberian System

Rivers of the Arctic will become ever more important for the global climate, since they carry a majority of continental dissolved organic carbon flux into the rapidly changing polar ocean. Aqueous organics comprise a wide array of functional groups, several of which are likely to impact coastal and open water biophysical properties. Light attenuation, interfacial films, aerosol formation, gas release and momentum exchange can all be cited. We performed Lagrangian kinetic modeling for the evolution of riverine organic chemistry as the molecules in question make their way from the highlands to Arctic outlets. Classes as diverse as the proteins, sugars, lipids, re-condensates, humics, bio-tracers and small volatiles are all included. Our reduced framework constitutes an idealized northward flow driving a major hydrological discharge rate and primarily representing the Russian Lena. Mountainous, high solute and tundra sources are all simulated, and they meet up at several points between soil and delta process reactors. Turnover rates are parameterized beginning with extrapolated coastal values imposed along a limited tributary network, with connections between different terrestrial sub-ecologies. Temporal variation of our total dissolved matter most closely resembles the observations when we focus on the restricted removal and low initial carbon loads, suggesting relatively slow transformation along the water course. Thus, channel combinations and mixing must play a dominant role. Nevertheless, microbial and photochemical losses help determine the final concentrations for most species. Chemical evolution is distinct for the various functionalities, with special contributions from pre- and post-reactivity in soil and delta waters. Several functions are combined linearly to represent the collective chromophoric dissolved matter, characterized here by its absorption. Tributaries carry the signature of lignin phenols to segregate tundra versus taiga sources, and special attention is paid to the early then marine behaviors of low molecular weight volatiles. Heteropolycondensates comprise the largest percentage of reactive carbon in our simulations due to recombination/accumulation, and they tend to be preeminent at the mouth. Outlet concentrations of individual structures such as amino acids and absorbers lie above threshold values for biophysical influence, on the monolayer and light attenuation. The extent of coastal spreading is examined through targeted regional box modeling, relying on salinity and color for calibration. In some cases, plumes reach the scale of peripheral arctic seas, and amplification is expected during upcoming decades. Conclusions are mapped from the Lena to other boreal discharges, and future research questions are outlined regarding the bonding type versus mass release as permafrost degrades. Dynamic aqueous organic coupling is recommended for polar system models, from headwaters to coastal diluent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for “Tree root nutrient uptake kinetics vary with nutrient availability, environmental conditions, and root traits: A global analysis”

This data package contains data and code used in the paper “Tree root nutrient uptake kinetics vary with nutrient availability, environmental conditions, and root traits: A global analysis”. The central product is a global dataset of root inorganic nutrient uptake rates and kinetics parameters covering temperate, boreal, and sub/tropical tree species, representing a collection of nutrient uptake data from published studies. This dataset enables tree investigation of root nutrient uptake rates across species, space, and experimental conditions. The data can also be combined with supplementary data on root and soil traits or with external datasets (e.g. R scripts contained within use data from FRED 3.0; (Iversen et al., 2021)). Contained within is the main nutrient data “uptake_data.csv” as well as 4 additional .csv files that link uptake data to supplementary measurements, source references, taxonomic information, and additional nutrient uptake measurements across nutrient gradients, and 1 .csv file that records meta-analysis results for plotting with the R scripts. There are seven R scripts that support data analysis and creation of the figures in the related publication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Emerging signals of declining forest resilience under climate change

Forest ecosystems depend on their capacity to withstand and recover from natural and anthropogenic perturbations (that is, their resilience). Experimental evidence of sudden increases in tree mortality is raising concerns about variation in forest resilience, yet little is known about how it is evolving in response to climate change. Here we integrate satellite-based vegetation indices with machine learning to show how forest resilience, quantified in terms of critical slowing down indicators, has changed during the period 2000–2020. We show that tropical, arid and temperate forests are experiencing a significant decline in resilience, probably related to increased water limitations and climate variability. By contrast, boreal forests show divergent local patterns with an average increasing trend in resilience, probably benefiting from warming and CO 2 fertilization, which may outweigh the adverse effects of climate change. These patterns emerge consistently in both managed and intact forests, corroborating the existence of common large-scale climate drivers. Reductions in resilience are statistically linked to abrupt declines in forest primary productivity, occurring in response to slow drifting towards a critical resilience threshold. Approximately 23% of intact undisturbed forests, corresponding to 3.32 Pg C of gross primary productivity, have already reached a critical threshold and are experiencing a further degradation in resilience. Together, these signals reveal a widespread decline in the capacity of forests to withstand perturbation that should be accounted for in the design of land-based mitigation and adaptation plans

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Peatland fires in Alaska will double by the end of the century

During recent summers, warm and dry conditions have increased the occurrence of wildfires and potentially peat-fires across Alaska. Limitations in resolving the fine-scale distribution of peatlands and climate observations have constrained our ability to accurately predict peat-fire dynamics. Using a new high-resolution peatland map of Alaska, we evaluated the climate and environmental controls of past and future peat-fire activity. Ensemble machine learning models identified reduced soil moisture, higher temperatures, and evapotranspiration as key predictors of annual total burned peatland area (tenfold CV R 2 = 0.62, RMSE = 221.1 km 2 ). By the end of the twenty-first century, models forced with climate datasets from representative concentration pathways (RCPs) 4.5, 6.0, and 8.5 emission scenarios project a statewide doubling of burned peatlands (increasing 61–121%), with regional increases ranging from 25–165% in polar, 61–95% in boreal, and 102–106% in maritime ecoregions. These projections indicate that wildfires will progressively encroach further into organic-rich moist and wet peaty soils, potentially amplifying soil carbon release across Alaska.

climate-change ecology↗
DOE OSTI2023

Climate warming and elevated CO 2 alter peatland soil carbon sources and stability

Peatlands are an important carbon (C) reservoir storing one-third of global soil organic carbon (SOC), but little is known about the fate of these C stocks under climate change. Here, we examine the impact of warming and elevated atmospheric CO 2 concentration (eCO 2 ) on the molecular composition of SOC to infer SOC sources (microbe-, plant- and fire-derived) and stability in a boreal peatland. We show that while warming alone decreased plant- and microbe-derived SOC due to enhanced decomposition, warming combined with eCO 2 increased plant-derived SOC compounds. We further observed increasing root-derived inputs (suberin) and declining leaf/needle-derived inputs (cutin) into SOC under warming and eCO 2 . The decline in SOC compounds with warming and gains from new root-derived C under eCO 2 , suggest that warming and eCO 2 may shift peatland C budget towards pools with faster turnover. Together, our results indicate that climate change may increase inputs and enhance decomposition of SOC potentially destabilising C storage in peatlands.

54 ENVIRONMENTAL SCIENCES↗