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Soil microbes play a crucial role in the carbon (C) cycle; however, they have been overlooked in predicting the terrestrial C cycle. We applied a microbial-explicit Earth system model – the Community Land Model-Microbe (CLM-Microbe) – to investigate the dynamics of soil microbes during 1901 to 2016. The CLM-Microbe model was able to reproduce the variations of gross (GPP) and net (NPP) primary productivity, heterotrophic (HR) and soil (SR) respiration, microbial (MBC) biomass C in fungi (FBC) and bacteria (BBC) in the top 30 cm and 1 m, and dissolved (DOC) and soil organic C (SOC) in the top 30 cm and 1 m during 1901–2016. During the study period, simulated C variables increased by approximately 12 PgC yr−1 for HR, 25 PgC yr−1 for SR, 1.0 PgC for FBC and 0.4 PgC for BBC in 0–30 cm, and 1.2 PgC for FBC and 0.7 PgC for BBC in 0–1 m. Increases in microbial C fluxes and pools were widely found, particularly at high latitudes and in equatorial regions, but we also observed their decreases in some grids. Overall, the area-weighted averages of HR, SR, FBC, and BBC in the top 1 m were significantly correlated with those of soil moisture and soil temperature in the top 1 m. These results suggested that microbial C fluxes and pools were jointly governed by vegetation C input and soil temperature and moisture. Our simulations revealed the spatial and temporal patterns of microbial C fluxes and pools in response to environmental change, laying the foundation for an improved understanding of soil microbial roles in the global terrestrial C cycle.

Cities generate 70% of anthropogenic greenhouse gas emissions, a fraction that is growing with global urbanization. While cities play an important role in climate change mitigation, there has been little focus on reducing urban methane (CH4) emissions. Here, we develop a conceptual framework for CH4 mitigation in cities by describing emission processes, the role of measurements, and a need for new institutional partnerships. Urban CH4 emissions are likely to grow with expanding use of natural gas and organic waste disposal systems in growing population centers; however, we currently lack the ability to quantify this increase. We also lack systematic knowledge of the relative contribution of these distinct source sectors on emissions. We present new observations from four North American cities to demonstrate that CH4 emissions vary in magnitude and sector from city to city and hence require different mitigation strategies. Detections of fugitive emissions from these systems suggest that current mitigation approaches are absent or ineffective. These findings illustrate that tackling urban CH4 emissions will require research efforts to identify mitigation targets, develop and implement new mitigation strategies, and monitor atmospheric CH4 levels to ensure the success of mitigation efforts. This research will require a variety of techniques to achieve these objectives and should be deployed in cities globally. We suggest that metropolitan scale partnerships may effectively coordinate systematic measurements and actions focused on emission reduction goals. Key points Unintended (fugitive) methane emissions are ubiquitous in urban systems, and come from biogenic as well as natural gas sources Methane emission sources and their magnitudes vary greatly among cities Urban methane mitigation will require new observations with a suite of techniques, and new institutional partnerships Plain Language Summary 70% of greenhouse gases emitted by humans come from cities. This number is growing as more of the world's population moves to cities. Cities have been active in reducing emissions of CO2, the most important greenhouse gas, but not of methane, the second most important gas. In cities, methane is mainly thought to come from natural gas handling systems, and waste disposal facilities. Both of these methane sources are growing over time; however, we do not know exact amounts or how fast these emissions will grow. We also do not know how much different methane sources contribute to the citywide budget. We present observations from four North American cities that demonstrate how methane emission amounts and sources can vary in different places. This suggests that different approaches will be needed to reduce methane emissions in different cities. Observations of unintentional methane releases suggest that not enough is currently being done to reduce emissions. We need new research to identify places where methane can be reduced most effectively, and how this can be achieved most efficiently. Several different measurement methods will be needed to meet this goal, and should be used in cities around the world. We suggest that city level partnerships could be the best way to make measurements and carry out actions to reduce methane emissions from cities.

Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest site in the Pacific Northwest region of the United States (Wind River AmeriFlux site), characterized by a Mediterranean climate that subjects trees to water stress each summer. CLM was driven by site-observed meteorology and calibrated primarily using parameter values observed at the site or at similar stands in the region. Key model adjustments included parameters controlling specific leaf area and stomatal conductance. Default values of these parameters led to significant underestimation of gross primary production, overestimation of evapotranspiration, and consequently overestimation of photosynthetic 13C discrimination, reflected in reduced 13C : 12C ratios of carbon fluxes and pools. Adjustments in soil hydraulic parameters within CLM were also critical, preventing significant underestimation of soil water content and unrealistic soil moisture stress during summer. After calibration, CLM was able to simulate energy and carbon fluxes, leaf area index, biomass stocks, and carbon isotope ratios of carbon fluxes and pools in reasonable agreement with site observations. Overall, the calibrated CLM was able to simulate the observed response of canopy conductance to atmospheric vapor pressure deficit (VPD) and soil water content, reasonably capturing the impact of water stress on ecosystem functioning. Both simulations and observations indicate that stomatal response from water stress at Wind River was primarily driven by VPD and not soil moisture. The calibration of the Ball–Berry stomatal conductance slope (mbb) at Wind River aligned with findings from recent CLM experiments at sites characterized by the same plant functional type (needleleaf evergreen temperate forest), despite significant differences in stand composition and age and climatology, suggesting that CLM could benefit from a revised mbb value of 6, rather than the default value of 9, for this plant functional type. Conversely, Wind River required a unique calibration of the hydrology submodel to simulate soil moisture, suggesting that the default hydrology has a more limited applicability. This study demonstrates that carbon isotope data can be used to constrain stomatal conductance and intrinsic water use efficiency in CLM, as an alternative to eddy covariance flux measurements. It also demonstrates that carbon isotopes can expose structural weaknesses in the model and provide a key constraint that may guide future model development.

Stable isotope ratio measurements of atmospheric water vapor (δ18Ov and δ2Hv) are scarce relative to those in precipitation. This limitation is rapidly changing due to advances in absorption spectroscopy technology and the development of automatically calibrated field-deployable instrument systems. These systems allow high throughput, in situ monitoring of the temporal variability in δ18Ov and δ2Hv. This paper presents a robust calibration procedure for reliable, high-precision δ18Ov and δ2Hv measurements at less than hourly intervals in this study. The method described here was developed and tested using a coupled system consisting of a commercial water vapor isotopic source device and a commercial water vapor isotope analyzer [Los Gatos Research (LGR) model WVIA-24] based on the off-axis integrated cavity output spectroscopy (off-axis ICOS) technique. The isotope analyzer shows a time-dependent response that varies with water vapor mixing ratio, suggesting the need of regular (hourly) calibration achievable by a single reference water source evaluated at a range of mixing ratios. By using a three-point calibration procedure with a range of user-specified water vapor mixing ratios, the authors were able to produce hourly δ18Ov and δ2Hv measurements with an overall accuracy (±0.2‰ for δ18O, ±0.5‰ for δ2H) and precision (±0.3‰ for δ18O, ±3.0‰ for δ2H) in the laboratory. The calibration procedure reliably produced data that were consistent with those collected by the conventional cryogenic method in an old-growth forest.

We evaluated an idealized boundary layer (BL) model with simple parameterizations using vertical transport information from community model outputs (NCAR/NCEP Reanalysis and ECMWF Interim Analysis) to estimate regional‐scale net CO2 fluxes from 2002 to 2007 at three forest and one grassland flux sites in the United States. The BL modeling approach builds on a mixed‐layer model to infer monthly average net CO2 fluxes using high‐precision mixing ratio measurements taken on flux towers. We compared BL model net ecosystem exchange (NEE) with estimates from two independent approaches. First, we compared modeled NEE with tower eddy covariance measurements. The second approach (EC‐MOD) was a data‐driven method that upscaled EC fluxes from towers to regions using MODIS data streams. Comparisons between modeled CO2 and tower NEE fluxes showed that modeled regional CO2 fluxes displayed interannual and intra‐annual variations similar to the tower NEE fluxes at the Rannells Prairie and Wind River Forest sites, but model predictions were frequently different from NEE observations at the Harvard Forest and Howland Forest sites. At the Howland Forest site, modeled CO2 fluxes showed a lag in the onset of growing season uptake by 2 months behind that of tower measurements. At the Harvard Forest site, modeled CO2 fluxes agreed with the timing of growing season uptake but underestimated the magnitude of observed NEE seasonal fluctuation. This modeling inconsistency among sites can be partially attributed to the likely misrepresentation of atmospheric transport and/or CO2 gradients between ABL and the free troposphere in the idealized BL model. EC‐MOD fluxes showed that spatial heterogeneity in land use and cover very likely explained the majority of the data‐model inconsistency. We show a site‐dependent atmospheric rectifier effect that appears to have had the largest impact on ABL CO2 inversion in the North American Great Plains. We conclude that a systematic BL modeling approach provided new insights when employed in multiyear, cross‐site synthesis studies. These results can be used to develop diagnostic upscaling tools, improving our understanding of the seasonal and interannual variability of surface CO2 fluxes. Key Points We evaluated an idealized BL model to estimate regional‐scale NEE at 4 AmeriFlux sites Radiation forcing acts commonly on the evolution of the ABL and NEE Site‐specific importance of the seasonal rectifier effect on regional carbon balance

Leaf water ¹⁸O enrichment (Δo) influences the isotopic composition of both gas exchange and organic matter, with Δo values responding to changes in atmospheric parameters. In order to examine possible influences of plant parameters on Δo dynamics, we measured oxygen isotope ratios (δ¹⁸O) of leaf and stem water on plant species representing different life forms in Amazonia forest and pasture ecosystems. We conducted two field experiments: one in March (wet season) and another in September (dry season) 2004. In each experiment, leaf and stem samples were collected at 2-h intervals at night and hourly during the day for 50 h from eight species including upper-canopy forest trees, upper-canopy forest lianas, and lower-canopy forest trees, a C₄ pasture grass and a C₃ pasture shrub. Significant life form-related differences were detected in ¹⁸O leaf water values. Initial modeling efforts to explain these observations over-predicted nighttime Δo values by as much as 10[per thousand]. Across all species, errors associated with measured values of the δ¹⁸O of atmospheric water vapor (δv) appeared to be largely responsible for the over-predictions of nighttime Δo observations. We could not eliminate collection or storage of water vapor samples as a possible error and therefore developed an alternative, plant-based method for estimating the daily average δv value in the absence of direct (reliable) measurements. This approach differs from the common assumption that isotopic equilibrium exists between water vapor and precipitation water, by including transpiration-based contributions from local vegetation through ¹⁸O measurements of bulk leaf water. Inclusion of both modified δv and non-steady state features resulted in model predictions that more reliably predicted both the magnitude and temporal patterns observed in the data. The influence of life form-specific patterns of Δo was incorporated through changes in the effective path length, an important but little known parameter associated with the Péclet effect.

Temperate forests play an important role in the global carbon cycle, and are thought to currently be a sink for atmospheric CO₂. However, we lack understanding of the drivers of forest carbon accumulation and loss, hampering our ability to predict carbon cycle responses to global change. In this study, we used CO₂ flux and radiocarbon (¹⁴C) measurements to investigate the role of seasonal drivers on soil respiration. Radiocarbon measurements of CO₂ evolved during incubation of fine roots and root-free soils at the beginning and end of the growing season (April and August) showed that these two soil respiration sources (fine roots vis-à-vis soils) have different mean residence times that stayed constant between seasons. Radiocarbon measurements show that root respiration was made up of carbon fixed 3-5 years prior to sampling, and that heterotrophic respiration was made up of carbon fixed 7-10 years prior. The difference in radiocarbon signature between the two sources allowed us to partition autotrophic and heterotrophic respiration sources for soil respiration measurements in the field. We observed a small but significant increase in Δ¹⁴C of soil respiration between April and August, suggesting an increase in heterotrophic respiration sources over the growing season. Using a two end-member mixing model, we estimate that 55 ± 22% of soil respiration originated from autotrophic (root) sources in April, but their contribution dropped to 38 ± 21% in August. These findings suggest that the contribution of root respiration increases at a time of high productivity and/or as a result of relatively low microbial respiration in the early spring in this old-growth coniferous forest.

An understanding of atmospheric water vapor content and its isotopic composition is important if we are to be able to model future water vapor dynamics and their potential feedback on future climate change. Here we present diurnal and vertical patterns of water isotope ratios in forest air (δ²Hv and δ¹⁸Ov) not observed previously. Water vapor observed at three heights over 3 consecutive days in a coniferous forest in the Pacific Northwest of the United States, shows a stratified nocturnal structure of δ²Hv and δ¹⁸Ov, with the most positive values consistently observed above the canopy (60 m). Differences between 0.5 m and 60 m range between 2-6‰ for δ¹⁸O and 20-40‰ for δ²H at night. Using a box model, we simulated H₂O isotope fluxes and showed that the low to high δ²Hv and δ¹⁸Ov profiles can be explained by the vapor flux associated with evaporation from the forest floor and canopy transpiration. We used d-excess as a diagnostic tracer to identify processes that contribute to the diurnal variation in atmospheric moisture. Values of d-excess derived from water vapor measurements showed a repeated diel pattern, with the lowest values occurring in the early morning and the highest values occurring at midday. The isotopic composition of rain water, collected during a light rain event in the first morning of our experiment, suggested that considerable below-cloud secondary evaporation occurred during the descent of raindrops. We conclude that atmospheric entrainment appears to drive the isotopic variation of water vapor in the early morning when the convective boundary layer rapidly develops, while evapotranspiration becomes more important in the mid-afternoon as a primary moisture source of water vapor in this forest. Our results demonstrate the interplay between the effects of vegetation and boundary layer mixing under the influence of rain evaporation, which has implications for larger-scale predictions of precipitation across the terrestrial landscape.

The eddy correlation technique was employed to measure net ecosystem carbon dioxide (CO2) (NEE) and water vapor exchange (LE) over a C3/C4 co‐occurring wet temperate Miscanthus‐type grassland in the Kanto plain of Japan in the 1999 growing season. The maximal mean canopy height and maximal leaf area index were 1.0 m and 5.5, respectively. The daily maximal LE was approximately 540 W m−2. The maximum value of daily accumulative LE was 16.3 MJ day−1. Daily variation of the decoupling factor (Ω) suggests that in the morning LE decoupled with the atmosphere, and the available energy was the major driving force for LE, whereas in the afternoon LE coupled strongly with the atmosphere, and the atmospheric evaporative demand played a critical role in LE. The decline in Ω (from 0.8 to 0.5) with the growing season demonstrates that LE decoupled from the atmosphere in the later growth season. The peak NEE value was 57.4 µmol CO2 m−2 s−1 (the positive value signifies the canopy carbon gain was from the air). The maximal daily integrated NEE was 1.06 mol CO2 m−2 day−1 observed during the peak growth stage. A rectangular hyperbolic model was used to describe the relation between daytime NEE and incident photosynthetic photon flux density (PPFD). The net ecosystem CO2 was not light‐saturated up to a PPFD level of 2000 µmol m−2 s−1. The initial slope estimated with the NEE–PPFD response model was approximately 0.042 mol CO2 mol−1 photon on average. The canopy light compensation point ranged from 210 to 430 µmol m−2 s−1 with an average of approximately 310µmol m−2 s−1. Both the initial slope and the canopy light compensation point decreased as the canopy senesced. The switch in dominance from C3 to C4 plants played an important role in the canopy fluxes.

A significant fraction of Earth consists of mountainous terrain. However, the question of how to monitor the surface–atmosphere carbon exchange over complex terrain has not been fully explored. This article reports on studies by a team of investigators from U.S. universities and research institutes who carried out a multiscale and multidisciplinary field and modeling investigation of the CO₂ exchange between ecosystems and the atmosphere and of CO₂ transport over complex mountainous terrain in the Rocky Mountain region of Colorado. The goals of the field campaign, which included ground and airborne in situ and remote-sensing measurements, were to characterize unique features of the local CO₂ exchange and to find effective methods to measure regional ecosystem–atmosphere CO₂ exchange over complex terrain. The modeling effort included atmospheric and ecological numerical modeling and data assimilation to investigate regional CO₂ transport and biological processes involved in ecosystem–atmosphere carbon exchange. In this report, we document our approaches, demonstrate some preliminary results, and discuss principal patterns and conclusions concerning ecosystem–atmosphere carbon exchange over complex terrain and its relation to past studies that have considered these processes over much simpler terrain.