78 research outputs found

    Long-term carbon and nitrogen dynamics at SPRUCE revealed through stable isotopes in peat profiles

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    Peatlands encode information about past vegetation dynamics, climate, and microbial processes. Here, we used δ15N and δ13C patterns from 16 peat profiles to deduce how the biogeochemistry of the Marcell S1 forested bog in northern Minnesota responded to environmental and vegetation change over the past  ∼ 10000 years. In multiple regression analyses, δ15N and δ13C correlated strongly with depth, plot location, C∕N, %N, and each other. Correlations with %N, %C, C∕N, and the other isotope accounted for 80% of variance for δ15N and 38% of variance for δ13C, reflecting N and C losses. In contrast, correlations with depth and topography (hummock or hollow) reflected peatland successional history and climate. Higher δ15N in plots closer to uplands may reflect upland-derived DON inputs and accompanying shifts in N dynamics in the lagg drainage area surrounding the bog. The Suess effect (declining δ13CO2 since the Industrial Revolution) lowered δ13C in recent surficial samples. High δ15N from −35 to −55cm probably indicated the depth of ectomycorrhizal activity after tree colonization of the peatland over the last 400 years, as confirmed by the occasional presence of wood down to −35cm depth. High δ13C at  ∼ 4000 years BP (−65 to −105cm) could reflect a transition at that time to slower rates of peat accumulation, when 13C discrimination during peat decomposition may increase in importance. Low δ13C and high δ15N at −213 and −225cm ( ∼ 8500 years BP) corresponded to a warm period during a sedge-dominated rich fen stage. The above processes appear to be the primary drivers of the observed isotopic patterns, whereas there was no clear evidence for methane dynamics influencing δ13C patterns

    Nutrient Control of Microbial Carbon Cycling Along an Ombrotrophicminerotrophic Peatland Gradient

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    Future climate change and other anthropogenic activities are likely to increase nutrient availability in many peatlands, and it is important to understand how these additional nutrients will influence peatland carbon cycling. We investigated the effects of nitrogen and phosphorus on aerobic CH4 oxidation, anaerobic carbon mineralization (as CO2 and CH4 production), and anaerobic nutrient mineralization in a bog, an intermediate fen, and a rich fen in the Upper Peninsula of Michigan. We utilized a 5-week laboratory nutrient amendment experiment in conjunction with a 6-year field nutrient fertilization experiment to consider how the relative response to nitrogen and phosphorus differed among these wetlands over the short and long term. Field fertilizations generally increased nutrient availability in the upper 15 cm of peat and resulted in shifts in the vegetation community in each peatland. High nitrogen concentrations inhibited CH4 oxidation in bog peat during short-term incubations; however, long-term fertilization with lower concentrations of nitrogen stimulated rates of CH4 oxidation in bog peat. In contrast, no nitrogen effects on CH4 oxidation were observed in the intermediate or rich fen peat. Anaerobic carbon mineralization in bog peat was consistently inhibited by increased phosphorus availability, but similar phosphorus additions had few effects in the intermediate fen and stimulated CH4 production and nutrient mineralization in the rich fen. Our results demonstrate that nitrogen and phosphorus are important controls of peatland microbial carbon cycling; however, the role of these nutrients can differ over the short and long term and is strongly mediated by peatland type

    CO2 Enhancement of Forest Productivity Constrained by Limited Nitrogen Availability

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    Stimulation of terrestrial productivity by rising CO~2~ concentration is projected to reduce the airborne fraction of anthropogenic CO~2~ emissions; coupled climate-carbon (C) cycle models, including those used in the IPCC Fourth Assessment Report (AR4), are sensitive to this negative feedback on atmospheric CO~2~^1^. The representation of the so-called CO~2~ fertilization effect in the 11 models used in AR4 and subsequent models^2,3^ was broadly consistent with experimental evidence from four free-air CO~2~ enrichment (FACE) experiments, which indicated that net primary productivity (NPP) of forests was increased by 23 +/- 2% in response to atmospheric CO~2~ enrichment to 550 ppm^4^. Substantial uncertainty remains, however, because of the expectation that feedbacks through the nitrogen (N) cycle will reduce the CO~2~ stimulation of NPP^5,6^; these feedbacks were not included in the AR4 models and heretofore have not been confirmed by experiments in forests^7^. Here, we provide new evidence from a FACE experiment in a deciduous Liquidambar styraciflua (sweetgum) forest stand in Tennessee, USA, that N limitation has significantly reduced the stimulation of NPP by elevated atmospheric CO~2~ concentration (eCO~2~). Isotopic evidence and N budget analysis support the premise that N availability in this forest ecosystem has been declining over time, and declining faster in eCO~2~. Model analyses and evidence from leaf- and stand-level observations provide mechanistic evidence that declining N availability constrained the tree response to eCO2. These results provide a strong rationale and process understanding for incorporating N limitation and N feedback effects in ecosystem and global models used in climate change assessments

    Plant root distributions and nitrogen uptake predicted by a hypothesis of optimal root foraging

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    CO2-enrichment experiments consistently show that rooting depth increases when trees are grown at elevated CO2 (eCO2), leading in some experiments to increased capture of available soil nitrogen (N) from deeper soil. However, the link between N uptake an

    Responses of vascular plant fine roots and associated microbial communities to whole-ecosystem warming and elevated CO2 in northern peatlands

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    Warming and elevated CO2 (eCO2) are expected to facilitate vascular plant encroachment in peatlands. The rhizosphere, where microbial activity is fueled by root turnover and exudates, plays a crucial role in biogeochemical cycling, and will likely at least partially dictate the response of the belowground carbon cycle to climate changes. We leveraged the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment, to explore the effects of a whole-ecosystem warming gradient (+0°C to 9°C) and eCO2 on vascular plant fine roots and their associated microbes. We combined trait-based approaches with the profiling of fungal and prokaryote communities in plant roots and rhizospheres, through amplicon sequencing. Warming promoted self-reliance for resource uptake in trees and shrubs, while saprophytic fungi and putative chemoorganoheterotrophic bacteria utilizing plant-derived carbon substrates were favored in the root zone. Conversely, eCO2 promoted associations between trees and ectomycorrhizal fungi. Trees mostly associated with short-distance exploration-type fungi that preferentially use labile soil N. Additionally, eCO2 decreased the relative abundance of saprotrophs in tree roots. Our results indicate that plant fine-root trait variation is a crucial mechanism through which vascular plants in peatlands respond to climate change via their influence on microbial communities that regulate biogeochemical cycles

    Climate warming and elevated CO2 alter peatland soil carbon sources and stability

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    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 CO2_{2} concentration (eCO2_{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 eCO2_{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 eCO2_{2}. The decline in SOC compounds with warming and gains from new root-derived C under eCO2_{2}, suggest that warming and eCO2_{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

    Evaluating Alternative Ebullition Models for Predicting Peatland Methane Emission and Its Pathways via Data–Model Fusion

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    Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: (1) the ebullition bubble growth volume threshold approach (EBG) and (2) the modified ebullition concentration threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model–data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization

    Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data–model fusion

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    Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: (1) the ebullition bubble growth volume threshold approach (EBG) and (2) the modified ebullition concentration threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model–data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization

    Evaluating Alternative Ebullition Models for Predicting Peatland Methane Emission and Its Pathways via Data–Model Fusion

    Get PDF
    Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: (1) the ebullition bubble growth volume threshold approach (EBG) and (2) the modified ebullition concentration threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model–data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization
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