El Niño-Southern Oscillation forcing on carbon and water cycling in a Bornean tropical rainforest.

Carbon dioxide and water vapor exchanges between tropical forest canopies and the atmosphere through photosynthesis, respiration, and evapotranspiration (ET) influence carbon and water cycling at the regional and global scales. Their inter- and intra-annual variations are sensitive to seasonal rhythms and longer-timescale tropical climatic events. In the present study, we assessed the El Niño-Southern Oscillation (ENSO) influence on ET and on the net ecosystem exchange (NEE), using eddy-covariance flux observations in a Bornean rainforest over a 10-y period (2010-2019) that included several El Niño and La Niña events. From flux model inversions, we inferred ecophysiological properties, notably the canopy stomatal conductance and "big-leaf" maximum carboxylation rate (Vcmax25_BL). Mean ET values were similar between ENSO phases (El Niño, La Niña, and neutral conditions). Conversely, the mean net ecosystem productivity was highest during La Niña events and lowest during El Niño events. Combining Shapley additive explanation calculations for nine controlling factors with a machine-learning algorithm, we determined that the primary factors for ET and NEE in the La Niña and neutral phases were incoming shortwave solar radiation and Vcmax25_BL, respectively, but that canopy stomatal conductance was the most significant factor for both ET and NEE in the El Niño phase. A combined stomatal-photosynthesis model approach further indicated that Vcmax25_BL differences between ENSO phases were the most significant controlling factor for canopy photosynthesis, emphasizing the strong need to account for ENSO-induced ecophysiological factor variations in model projections of the long-term carbon balance in Southeast Asian tropical rainforests.

Carbon uptake in Eurasian boreal forests dominates the high-latitude net ecosystem carbon budget.

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003-2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco ), net ecosystem CO2 exchange (NEE; Reco - GPP), and terrestrial methane (CH4 ) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of -850 Tg CO2 -C year-1 . Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4 ) were estimated at 35 Tg CH4 -C year-1 . Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions.

Wetlands are the largest natural source of methane (CH4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4 , but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model-iPEACE-reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes.

Cross-biome synthesis of source versus sink limits to tree growth.

Uncertainties surrounding tree carbon allocation to growth are a major limitation to projections of forest carbon sequestration and response to climate change. The prevalence and extent to which carbon assimilation (source) or cambial activity (sink) mediate wood production are fundamentally important and remain elusive. We quantified source-sink relations across biomes by combining eddy-covariance gross primary production with extensive on-site and regional tree ring observations. We found widespread temporal decoupling between carbon assimilation and tree growth, underpinned by contrasting climatic sensitivities of these two processes. Substantial differences in assimilation-growth decoupling between angiosperms and gymnosperms were determined, as well as stronger decoupling with canopy closure, aridity, and decreasing temperatures. Our results reveal pervasive sink control over tree growth that is likely to be increasingly prominent under global climate change.

A decade of CO2 flux measured by the eddy covariance method including the COVID-19 pandemic period in an urban center in Sakai, Japan.

Cities constitute an important source of greenhouse gases, but few results originating from long-term, direct CO2 emission monitoring efforts have been reported. In this study, CO2 emissions were quasi-continuously measured in an urban center in Sakai, Osaka, Japan by the eddy covariance method from 2010 to 2021. Long-term CO2 emissions reached 22.2 ± 2.0 kg CO2 m-2 yr-1 from 2010 to 2019 (± denotes the standard deviation) in the western sector from the tower representing the densely built-up area. Throughout the decade, the annual CO2 emissions remained stable. According to an emission inventory, traffic emissions represented the major source of CO2 emissions within the flux footprint. The interannual variations in the annual CO2 flux were positively correlated with the mean annual traffic counts at two highway entrances and exits. The CO2 emissions decreased suddenly, by 32% ± 3.1%, in April and May 2020 during the period in which the first state of emergency associated with COVID-19 was declared. The annual CO2 emissions also decreased by 25% ± 3.1% in 2020. Direct long-term observations of CO2 emissions comprise a useful tool to monitor future emission reductions and sudden disruptions in emissions, such as those beginning in 2020 during the COVID-19 pandemic.

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions.

Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales.

While wetlands are the largest natural source of methane (CH4 ) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.

Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties.

The regional variability in tundra and boreal carbon dioxide (CO2 ) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990-2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2 ) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE -46 and -29 g C m-2  yr-1 , respectively) compared to tundra (average annual NEE +10 and -2 g C m-2  yr-1 ). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990-2015, although uncertainty remains high.

Increased high-latitude photosynthetic carbon gain offset by respiration carbon loss during an anomalous warm winter to spring transition.

Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2 ) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010-2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon-climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes.

Autumn warming reduces the CO2 sink of a black spruce forest in interior Alaska based on a nine-year eddy covariance measurement.

Nine years (2003-2011) of carbon dioxide (CO2) flux were measured at a black spruce forest in interior Alaska using the eddy covariance method. Seasonal and interannual variations in the gross primary productivity (GPP) and ecosystem respiration (RE) were associated primarily with air temperature: warmer conditions enhanced GPP and RE. Meanwhile, interannual variation in annual CO2 balance was controlled predominantly by RE, and not GPP. During these 9 years of measurement, the annual CO2 balance shifted from a CO2 sink to a CO2 source, with a 9-year average near zero. The increase in autumn RE was associated with autumn warming and was mostly attributed to a shift in the annual CO2 balance. The increase in autumn air temperature (0.22 °C yr(-1)) during the 9 years of study was 15 times greater than the long-term warming trend between 1905 and 2011 (0.015 °C yr(-1)) due to decadal climate oscillation. This result indicates that most of the shifts in observed CO2 fluxes were associated with decadal climate variability. Because the natural climate varies in a cycle of 10-30 years, a long-term study covering at least one full cycle of decadal climate oscillation is important to quantify the CO2 balance and its interaction with the climate.

Growing season and spatial variations of carbon fluxes of Arctic and boreal ecosystems in Alaska (USA).

To better understand the spatial and temporal dynamics of CO2 exchange between Arctic ecosystems and the atmosphere, we synthesized CO2 flux data, measured in eight Arctic tundra and five boreal ecosystems across Alaska (USA) and identified growing season and spatial variations of the fluxes and environmental controlling factors. For the period examined, all of the boreal and seven of the eight Arctic tundra ecosystems acted as CO2 sinks during the growing season. Seasonal patterns of the CO2 fluxes were mostly determined by air temperature, except ecosystem respiration (RE) of tundra. For the tundra ecosystems, the spatial variation of gross primary productivity (GPP) and net CO2 sink strength were explained by growing season length, whereas RE increased with growing degree days. For boreal ecosystems, the spatial variation of net CO2 sink strength was mostly determined by recovery of GPP from fire disturbance. Satellite-derived leaf area index (LAI) was a better index to explain the spatial variations of GPP and NEE of the ecosystems in Alaska than were the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Multiple regression models using growing degree days, growing season length, and satellite-derived LAI explained much of the spatial variation in GPP and net CO2 exchange among the tundra and boreal ecosystems. The high sensitivity of the sink strength to growing season length indicated that the tundra ecosystem could increase CO2 sink strength under expected future warming, whereas ecosystem compositions associated with fire disturbance could play a major role in carbon release from boreal ecosystems.