Plant-mediated CH4 transport (PMT) is the dominant pathway through which soil-produced CH4 can escape into the atmosphere and thus plays an important role in controlling ecosystem CH4 emission. PMT is affected by abiotic and biotic factors simultaneously, and the effects of biotic factors, such as the dominant plant species and their traits, can override the effects of abiotic factors. Increasing evidence shows that plant-mediated CH4 fluxes include not only PMT, but also within-plant CH4 production and oxidation due to the detection of methanogens and methanotrophs attached to the shoots. Despite the inter-species and seasonal differences, and the probable contribution of within-plant microbes to total plant-mediated CH4 exchange (PME), current process-based ecosystem models only estimate PMT based on the bulk biomass or leaf area index of aerenchymatous plants. We highlight five knowledge gaps to which more research efforts should be devoted. First, large between-species variation, even within the same family, complicates general estimation of PMT, and calls for further work on the key dominant species in different types of wetlands. Second, the interface (rhizosphere-root, root-shoot, or leaf-atmosphere) and plant traits controlling PMT remain poorly documented, but would be required for generalizations from species to relevant functional groups. Third, the main environmental controls of PMT across species remain uncertain. Fourth, the role of within-plant CH4 production and oxidation is poorly quantified. Fifth, the simplistic description of PMT in current process models results in uncertainty and potentially high errors in predictions of the ecosystem CH4 flux. Our review suggest that flux measurements should be conducted over multiple growing seasons and be paired with trait assessment and microbial analysis, and that trait-based models should be developed. Only then we are capable to accurately estimate plant-mediated CH4 emissions, and eventually ecosystem total CH4 emissions at both regional and global scales. 

Plant-mediated CH4 exchange in wetlands: A review of mechanisms and measurement methods with implications for modelling.

Abstract Boreal‐Arctic regions are key stores of organic carbon (C) and play a major role in the greenhouse gas balance of high‐latitude ecosystems. The carbon‐climate (C‐climate) feedback potential of northern high‐latitude ecosystems remains poorly understood due to uncertainty in temperature and precipitation controls on carbon dioxide (CO 2 ) uptake and the decomposition of soil C into CO 2 and methane (CH 4 ) fluxes. While CH 4 fluxes account for a smaller component of the C balance, the climatic impact of CH 4 outweighs CO 2 (28–34 times larger global warming potential on a 100‐year scale), highlighting the need to jointly resolve the climatic sensitivities of both CO 2 and CH 4 . Here, we jointly constrain a terrestrial biosphere model with in situ CO 2 and CH 4 flux observations at seven eddy covariance sites using a data‐model integration approach to resolve the integrated environmental controls on land‐atmosphere CO 2 and CH 4 exchanges in Alaska. Based on the combined CO 2 and CH 4 flux responses to climate variables, we find that 1970‐present climate trends will induce positive C‐climate feedback at all tundra sites, and negative C‐climate feedback at the boreal and shrub fen sites. The positive C‐climate feedback at the tundra sites is predominantly driven by increased CH 4 emissions while the negative C‐climate feedback at the boreal site is predominantly driven by increased CO 2 uptake (80% from decreased heterotrophic respiration, and 20% from increased photosynthesis). Our study demonstrates the need for joint observational constraints on CO 2 and CH 4 biogeochemical processes—and their associated climatic sensitivities—for resolving the sign and magnitude of high‐latitude ecosystem C‐climate feedback in the coming decades. 

Resolving the carbon‐climate feedback potential of wetland CO2 and CH4 fluxes in Alaska

Because methane is a potent greenhouse gas (GHG), understanding controls on methane emissions from reservoirs is an important goal. Yet, reservoirs are complex ecosystems, and mechanisms by which reservoir operations influence methane emissions are poorly understood. In part, this is because emissions occur in ‘hot spots’ and ‘hot moments’. In this study, we address three research questions, ‘What are the causal pathways through which reservoir operations and resulting water level fluctuations (WLF) influence methane emissions?’; ‘How do influences from WLF differ for seasonal drawdown and diurnal hydropeaking operations?’; and ‘How does understanding causal pathways inform practical options for mitigation?’. A graphical conceptual model is presented that links WLF in reservoirs to methane emissions via four causal pathways: (1) water-column mixing (2) drying–rewetting cycles, (3) sediment delivery and redistribution, and (4) littoral vegetation. We review what is known about linkages for WLF at seasonal and diurnal resolutions generate research questions, and hypothesize strategies for moderating methane emissions by interrupting each causal pathway. Those related to flow management involve basin-scale management of tributary flows, seasonal timing of hydropeaking (pathway #1), timing and rates of drawdown (pathway #2). In addition, we describe how sediment (pathway #3) and vegetation management (pathway #4) could interrupt linkages between WLF and emissions. We demonstrate the strength of conceptual modeling as a tool for generating plausible hypotheses and suggesting mitigation strategies. Future research is needed to develop simpler models at appropriate timescales that can be validated and used to manage flow releases from reservoirs. 

Understanding How Reservoir Operations Influence Methane Emissions: A Conceptual Model

Diurnal fluctuations in methane (CH4 ) emission are frequently observed in rice paddy fields, yet the driving mechanisms behind these variations are not fully understood. We posited that the observed diurnal patterns are predominantly due to temperature-dependent bubbling emissions (ebullition). To investigate this hypothesis, we conducted measurements of CH4 emission in a Japanese rice paddy using static chambers coupled with a high-time-resolution CH4 analyzer that allowed us to partition the total flux into its two principal components: plant-mediated transport and ebullition. Diurnal variation in the total flux was minimal during the early parts of reproductive growth (panicle formation and booting stages), when plant-mediated emission was dominant. At a later stage (heading period), ebullition accounted for 43%-70% of the total emission, and CH4 emission via both pathways varied diurnally; however, the diurnal range was much greater for bubbling emission (ratio of maximum to minimum = 3.5) than for plant-mediated emission (ratio of maximum to minimum = 1.4). The magnitude of emissions due to ebullition depended on the temperature, but was greater during the flux-increasing phase in the morning than the flux-decreasing phase in the afternoon even at the same temperature, forming a hysteresis in the flux versus temperature relationship. These findings support our hypothesis and indicate that abiotic processes, such as a change in the solubility of gases and the temperature dependence of the gas-phase volume (Charles's law), may play a central role in shaping the diurnal pattern of the CH4 ebullition. 

Diurnal variation in methane emission from a rice paddy due to ebullition

Abstract. Ecosystem manipulative experiments are one of the most powerful tools to understand terrestrial ecosystem responses to global change because they measure real responses in real ecosystems. However, their scope is limited in space and time due to cost and labour intensity. This makes generalising results from such experiments difficult, which creates a conceptual gap between local scale process understanding and global scale future predictions. Recent efforts have seen results from such experiments used in combination with dynamic global vegetation models, most commonly to evaluate model predictions under global change drivers. However, there is much more potential in combining models and experiments. Here, we discuss the value and potential of a workflow for using ecosystem experiments together with process-based models to enhance the potential of both. We suggest that models can be used prior to the start of an experiment to generate hypotheses, identify data needs and in general guide experimental design. Models, when adequately constrained with observations, can also predict variables which are difficult to measure frequently or at all, and together with the data can provide a more complete picture of ecosystem states. Finally, models can be used to help generalise the experimental results in space and time, by providing a framework in which process understanding derived from site-level experiments can be incorporated. We also discuss the potential for using manipulative experiments together with models in formalised model-data integration frameworks for parameter estimation and model selection, a path made possible by the increasing number of ecosystem experiments and diverse observation streams. The ideas presented here can provide a roadmap to future experiment - model studies. 

/pdf/ideas-and-perspectives-beyond-model-evaluation-combining-5ekljhse.pdf

Ideas and perspectives: Beyond model evaluation – combining experiments and models to advance terrestrial ecosystem science

Abstract. 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. 

/pdf/evaluating-alternative-ebullition-models-for-predicting-2kzgfgcw.pdf

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

Model-Data Integration at the SPRUCE Experiment

Accurate Earth system model simulations of the terrestrial carbon cycle and its feedbacks to climate critically depend on algorithms representing the decomposition of litter and soil organic matter. Litter bag studies, in which specific types of plant litter are subject to varying environmental conditions in the field and decomposition is measured, serve as valuable benchmarks for model performance. Here we test the Energy Exascale Earth System land model (ELM), which has two different structural representations of decomposition, using observations from the Long-term Intersite Decomposition Experiment (LIDET) over six different biomes and six different leaf litter types. We find that seasonal patterns in soil conditions and nutrient availability have large effects on decomposition rates, and that it is critical to include this in the simulation design. Despite widely differing base decomposition rates between the two different model structures, the models produce similar temporal patterns of decomposition when nitrogen is limiting. Both models overpredict the fraction of original nitrogen present as a function of carbon remaining when using default parameterizations. A parameter sensitivity analysis indicates strong dependence of model outputs on nitrogen limitation, carbon use efficiency and decomposition rates. A large spread in model predictions when considering an ensemble of possible parameter combinations strongly suggests parameter uncertainty may be more influential than model structural uncertainty, and that new measurement and modelling approaches may be necessary to constrain these uncertainties. 

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Abstract. The importance of carbon (C)-nutrient interactions to the prediction of future C uptake has long been recognized. The Energy Exascale Earth System Model (E3SM) land model (ELM) version 1 is one of the few land surface models that include both N and P cycling and limitation (ELMv1-CNP). Here we provide a global scale evaluation of ELMv1-CNP using International Land Model Benchmarking (ILAMB) system. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. Compared to simulations with optimal P availability, simulations with ELMv1-CNP produces better performance, particularly for simulated biomass, leaf area index (LAI), and global net C balance. We also show ELMv1-CNP simulated N and P cycling are in good agreement with data-driven estimates. We compared ELMv1-CNP simulated response to CO2 enrichment with meta-analysis of observations from similar manipulation experiments. We show that ELMv1-CNP is able to capture the field observed responses for photosynthesis, growth, and LAI. We investigated the role of P limitation in the historical balance and show that global C sources and sinks are significantly affected by P limitation, as the historical CO2 fertilization effect was reduced by 20 % and C emission due to land use and land cover change was 11 % lower when P limitation was considered. Our simulations suggest that introduction of P cycle dynamics and C-N-P coupling will likely have substantial consequences for projections of future C uptake. 

/pdf/global-evaluation-of-elmv1-cnp-and-the-role-of-the-lxm47bzd.pdf

Global evaluation of ELMv1-CNP and the role of the phosphorus cycle in the historical terrestrial carbon balance

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