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Aim: Fresh carbon (C) inputs to the soil can have important consequences for the decomposition rates of soil organic matter (priming effect), thereby impacting the delicate global C balance at the soil–atmosphere interface. Yet, the environmental factors that control soil priming effect intensity remain poorly understood at a global scale. Location: Global. Time period: 1980–2020. Major taxa studied: Soil priming effect intensity. Methods: We conducted a global dataset of CO2 effluxes in 711 pairwise soils with 13C or 14C simple C sources inputs and without C inputs from incubation experiments in which isotope‐labelled C was used to quantify fresh C‐induced rather than exudate‐induced priming. Results: Soil priming effect intensity is predominantly positive. Soil texture and C content were identified as the most important factors associated with priming effects, with sandy soils from tropical and mid‐latitudes supporting the highest soil priming effect intensity, and soils with greater C content and fine textures from high latitudes maintaining the lowest soil priming effects. The negative association between C content and soil priming effect intensity was also indirectly driven by changing mean annual temperature, net primary productivity, and fungi : bacteria ratio. Using this information, we generated a global map of soil priming effect intensity, and found that the priming was lower at high latitudes and higher at lower latitudes. Main conclusions: Global patterns of soil priming effect intensity can be predicted using environmental data, with soil texture and C content playing a predominant role in explaining in priming effects. These effects were also indirectly driven by climate, vegetation and soil microbial properties. We present the first global atlas of soil priming effect intensity and advance our knowledge on the potential mechanisms underlying soil priming effect intensity, which are integral to improving the climate change and soil C dynamics components of Earth System models. [ABSTRACT FROM AUTHOR]

Lakes provide enormous economic, recreational, and aesthetic benefits to citizens. These ecosystem services may be adversely impacted by climate change. In the Twin Cities Metropolitan Area of Minnesota, USA, many lakes have been at historic low levels and water augmentation strategies have been proposed to alleviate the problem. White Bear Lake (WBL) is a notable example. Its water level declined 1.5 m during 2003–2013 for reasons that are not fully understood. This study examined current, past, and future lake evaporation to better understand how climate will impact the water balance of lakes within this region. Evaporation from WBL was measured from July 2014 to February 2017 using two eddy covariance (EC) systems to provide better constraints on the water budget and to investigate the impact of evaporation on lake level. The estimated annual evaporation losses for years 2014 through 2016 were 559 ± 22 mm, 779 ± 81 mm, and 766 ± 11 mm, respectively. The higher evaporation in 2015 and 2016 was caused by the combined effects of larger average daily evaporation and a longer ice-free season. The EC measurements were used to tune the Community Land Model 4 – Lake, Ice, Snow and Sediment Simulator (CLM4-LISSS) to estimate lake evaporation over the period 1979–2016. Retrospective analyses indicate that WBL evaporation increased during this time by about 3.8 mm year −1 , which was driven by increased wind speed and lake-surface vapor pressure gradient. Using a business-as-usual greenhouse gas emission scenario (RCP8.5), lake evaporation was modeled forward in time from 2017 to 2100. Annual evaporation is expected to increase by 1.4 mm year −1 over this century, largely driven by lengthening ice-free periods. These changes in ice phenology and evaporation will have important implications for the regional water balance, and water management and water augmentation strategies that are being proposed for these Metropolitan lakes. [ABSTRACT FROM AUTHOR]

Abstract: The stable carbon isotope ratio, , is a valuable tracer for studying the processes controlling the autotrophic (F Ra ) and heterotrophic (F Rh ) contributions to ecosystem respiration (F R ) and the influence of photosynthesis on F R . There is increasing interest in quantifying the temporal variability of the carbon isotope composition of ecosystem respiration (δ R ) because it contains information about the sources contributing to respiration and is an important parameter used for partitioning net ecosystem CO2 exchange using stable isotope methods. In this study, eddy covariance, flux gradient, automated chambers, and stable carbon isotope techniques were used to quantify and improve our understanding of the temporal variability in F R and δ R in a C3/C4 agricultural ecosystem. Six years (2004–2009) of isotope flux-gradient measurements indicated that δ R had a very consistent annual pattern during both C3 (soybean) and C4 (corn) growing seasons due to significant contributions from F Ra , which was strongly influenced by the isotope composition of the recent photosynthate. However, in the spring, δ R exhibited a C3 signal regardless of the crop grown in the previous season. One hypothesis for this anomaly is that at these low soil temperatures microbial activity relied predominantly on C3 substrates. Automated chamber measurements of soil respiration () and its isotope composition () were initiated in the early corn growing season of 2009 to help interpret the variability in δ R . These measurements showed good agreement with EC measurements of F R (within 0.5μmolm2 s−1) and isotope flux gradient measurements of δ R (within 2‰) at nighttime for near-bare soil conditions (LAI<0.1). At peak growth, nighttime δ R above the corn canopy was consistently 1–6‰ more enriched than . The relatively enriched signal above the canopy indicates that δ R was strongly influenced by aboveground plant respiration (F R,ag ), which accounted for about 40% of F R . The automated chamber data and analyses also revealed a strong diel pattern in . In the early growth period, showed a sharp morning enrichment of up to 4‰ followed by a gradual depletion throughout the afternoon and evening. Daytime enrichment in was most pronounced during dry conditions and was not observed when the upper soil was near saturation. We provide anecdotal evidence that the diel variability during early growth may have been influenced by turbulence (advection/non-diffusive transport), which reduced the kinetic fractionation effect. At peak growth, there is evidence that the sheltering effect of the corn plants diminished the influence of turbulence on the chamber measurement of . Further research is needed to evaluate and separate the contributions of biotic and abiotic (advection and non-steady state effects) influences on chamber observations. [Copyright &y& Elsevier]

Abstract This paper presents an empirical model of net ecosystem CO2 exchange (NEE) developed for a subarctic fen near Churchill, Manitoba. The model with observed data helps explain the interannual variability in growing season NEE. Five years of tower-flux data are used to test and examine the seasonal behaviour of the model simulations. Processes controlling the observed interannual variability of CO2 exchange at the fen are examined by exploring the sensitivity of the model to changes in air temperature, precipitation and leaf area index. Results indicate that the sensitivity of NEE to changing environmental controls is complex and varies interannually depending on the initial conditions of the wetland. Changes in air temperature and the timing of precipitation events have a strong influence on NEE, which is largely manifest in gross ecosystem photosynthesis (GEP). Climate change scenarios indicate that warmer air temperatures will increase carbon acquisition during wet years but may act to reduce wetland carbon storage in years that experience a large water deficit early in the growing season. Model simulations for this subarctic sedge fen indicate that carbon acquisition is greatest during wet and warm conditions. This suggests therefore that carbon accumulation was greatest at this subarctic fen during its early developmental stages when hydroclimatic conditions were relatively wet and warm at approximately 2500 years before present. [ABSTRACT FROM AUTHOR]

SummaryLandscape- and community-level CO2 measurements were made at a subarctic sedge fen near Churchill Manitoba during the 1997 growing season. Climatic conditions were warmer and drier than the 30-y normal. Landscape-scale micrometeorological measurements indicated that the wetland gained 49 g CO2 m-2 during the growing season. Chamber-scale measurements from the main vegetation community types showed that small hummocks (Carex spp. sites) dominated the CO2 exchange, yielding an effective scaling factor of 70%. Scaled parameters of two algorithms describing photosynthesis and respiration for each community type show strong similarity to those derived at the landscape level. Scaling photosynthesis, respiration, and net ecosystem CO2 exchange from the community to landscape-level over the season is within the maximum probable error of each methodological approach and helps substantiate the 1997 CO2 budget. We explore the equilibrium response of net ecosystem CO2 exchange of this fen to climatic change by examining the feedback of water table position on vegetation distribution and nitrogen availability. Based on the effective scaling factors computed for each community type, we hypothesize that a small decrease in mean water table position could nearly triple the net uptake of CO2 at this wetland. [ABSTRACT FROM AUTHOR]

• First evaluation of the new E3SM land model (ELM) in an Amazonian peatland. • A surrogate-assisted Bayesian approach was implemented for parameter optimization. • Improved functions and optimized parameters greatly enhanced model performance. • Modeled energy, CO 2 and CH 4 fluxes were most sensitive to phenological parameters. • Parameter importance depended on biogeochemical process and shifted with season. Tropical peatlands are one of the largest natural sources of atmospheric methane (CH 4) and play a significant role in regional and global carbon budgets. However, large uncertainties persist regarding their feedbacks to climate variations. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is an ongoing state-of-the-science model, which has developed new representations of soil hydrology and biogeochemistry and includes a new microbial-functional-group-based CH 4 module. This model has been tested in boreal forest peatlands, but has not yet been evaluated for simulating energy and carbon exchange for tropical peatlands. Here, we evaluated the ELM performance in simulating energy, carbon dioxide (CO 2) and CH 4 fluxes of an Amazonian palm swamp peatland in Iquitos, Peru. ELM simulations using default parameter values resulted in poor performance of seasonal carbon dynamics. Several algorithms were improved according to site-specific characteristics and key parameters were optimized using an objective surrogate-assisted Bayesian approach. The modified algorithms included the soil water retention curve, a water coverage scalar function for CH 4 processes, and a seasonally varying leaf carbon-to-nitrogen ratio function. The revised tropics-specific model better simulated the diel and seasonal patterns of energy and carbon fluxes of the palm swamp peatland. Global sensitivity analyses indicated that the strong controls on energy and carbon fluxes were mainly attributed to the parameters associated with vegetation activities, such as plant carbon distribution, stomatal regulation, photosynthetic capacity, and leaf phenology. Parameter relative importance depended on biogeochemical processes and shifted significantly between wet and dry seasons. This modeling study advanced the understanding of biotic controls on the energy and carbon exchange in Amazonian palm swamp peatlands and identified knowledge gaps that need to be addressed for better prediction of carbon cycle processes and budgets for tropical peatlands. [ABSTRACT FROM AUTHOR]