Inferred drought-induced plant allocation shifts and their impact on drought legacy at a tropical forest site.

While droughts predominantly induce immediate reductions in plant carbon uptake, they can also exert long-lasting effects on carbon fluxes through associated changes in leaf area, soil carbon, etc. Among other mechanisms, shifts in carbon allocation due to water stress can contribute to the legacy effects of drought on carbon fluxes. However, the magnitude and impact of these allocation shifts on carbon fluxes and pools remain poorly understood. Using data from a wet tropical flux tower site in French Guiana, we demonstrate that drought-induced carbon allocation shifts can be reliably inferred by assimilating Net Biosphere Exchange (NBE) and other observations within the CARbon DAta MOdel fraMework. This model-data fusion system allows inference of optimized carbon and water cycle parameters and states from multiple observational data streams. We then examined how these inferred shifts affected the duration and magnitude of drought's impact on NBE during and after the extreme event. Compared to a static allocation scheme analogous to those typically implemented in land surface models, dynamic allocation reduced average carbon uptake during drought recovery by a factor of 2.8. Additionally, the dynamic model extended the average recovery time by 5 months. The inferred allocation shifts influenced the post-drought period by altering foliage and fine root pools, which in turn modulated gross primary productivity and heterotrophic respiration for up to a decade. These changes can create a bust-boom cycle where carbon uptake is enhanced some years after a drought, compared to what would have occurred under drought-free conditions. Overall, allocation shifts accounted for 65% [45%-75%] of drought legacy effects in modeled NBE. In summary, drought-induced carbon allocation shifts can play a substantial role in the enduring influence of drought on cumulative land-atmosphere CO2 exchanges and should be accounted for in ecosystem models.

Underestimated Dry Season Methane Emissions from Wetlands in the Pantanal.

Tropical wetlands contribute ∼30% of the global methane (CH4) budget. Limited observational constraints on tropical wetland CH4 emissions lead to large uncertainties and disparities in representing emissions. In this work, we combine remote sensing observations with atmospheric and wetland models to investigate dry season wetland CH4 emissions from the Pantanal region of South America. We incorporate inundation maps generated from the Cyclone Global Navigation Satellite System (CYGNSS) satellite constellation together with traditional inundation maps to generate an ensemble of wetland CH4 emission realizations. We challenge these realizations with daily satellite observations for May-July when wetland CH4 emission predictions diverge. We find that the CYGNSS inundation products predict larger emissions in May, in better agreement with observations. We use the model ensemble to generate an empirical observational constraint on CH4 emissions independent of choice of inundation map, finding large dry season wetland CH4 emissions (31.7 ± 13.6 and 32.0 ± 20.2 mg CH4/m2/day in May and June/July during 2018/2019, respectively). These May/June/July emissions are 2-3 times higher than current models, suggesting that annual wetland emissions may be higher than traditionally simulated. Observed trends in the early dry season indicate that dynamics during this period are of importance in representing tropical wetland CH4 behaviors.

Global net biome CO2 exchange predicted comparably well using parameter-environment relationships and plant functional types.

Accurate estimation and forecasts of net biome CO2 exchange (NBE) are vital for understanding the role of terrestrial ecosystems in a changing climate. Prior efforts to improve NBE predictions have predominantly focused on increasing models' structural realism (and thus complexity), but parametric error and uncertainty are also key determinants of model skill. Here, we investigate how different parameterization assumptions propagate into NBE prediction errors across the globe, pitting the traditional plant functional type (PFT)-based approach against a novel top-down, machine learning-based "environmental filtering" (EF) approach. To do so, we simulate these contrasting methods for parameter assignment within a flexible model-data fusion framework of the terrestrial carbon cycle (CARDAMOM) at a global scale. In the PFT-based approach, model parameters from a small number of select locations are applied uniformly within regions sharing similar land cover characteristics. In the EF-based approach, a pixel's parameters are predicted based on underlying relationships with climate, soil, and canopy properties. To isolate the role of parametric from structural uncertainty in our analysis, we benchmark the resulting PFT-based and EF-based NBE predictions with estimates from CARDAMOM's Bayesian optimization approach (whereby "true" parameters consistent with a suite of data constraints are retrieved on a pixel-by-pixel basis). When considering the mean absolute error of NBE predictions across time, we find that the EF-based approach matches or outperforms the PFT-based approach at 55% of pixels-a narrow majority. However, NBE estimates from the EF-based approach are susceptible to compensation between errors in component flux predictions and predicted parameters can align poorly with the assumed "true" values. Overall, though, the EF-based approach is comparable to conventional approaches and merits further investigation to better understand and resolve these limitations. This work provides insight into the relationship between terrestrial biosphere model performance and parametric uncertainty, informing efforts to improve model parameterization via PFT-free and trait-based approaches.

GriddingMachine, a database and software for Earth system modeling at global and regional scales.

Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities.

Amazonian terrestrial water balance inferred from satellite-observed water vapor isotopes.

Atmospheric humidity and soil moisture in the Amazon forest are tightly coupled to the region's water balance, or the difference between two moisture fluxes, evapotranspiration minus precipitation (ET-P). However, large and poorly characterized uncertainties in both fluxes, and in their difference, make it challenging to evaluate spatiotemporal variations of water balance and its dependence on ET or P. Here, we show that satellite observations of the HDO/H2O ratio of water vapor are sensitive to spatiotemporal variations of ET-P over the Amazon. When calibrated by basin-scale and mass-balance estimates of ET-P derived from terrestrial water storage and river discharge measurements, the isotopic data demonstrate that rainfall controls wet Amazon water balance variability, but ET becomes important in regulating water balance and its variability in the dry Amazon. Changes in the drivers of ET, such as above ground biomass, could therefore have a larger impact on soil moisture and humidity in the dry (southern and eastern) Amazon relative to the wet Amazon.

Changes in global terrestrial live biomass over the 21st century.

Live woody vegetation is the largest reservoir of biomass carbon, with its restoration considered one of the most effective natural climate solutions. However, terrestrial carbon fluxes remain the largest uncertainty in the global carbon cycle. Here, we develop spatially explicit estimates of carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show that live biomass has removed 4.9 to 5.5 PgC year-1 from the atmosphere, offsetting 4.6 ± 0.1 PgC year-1 of gross emissions from disturbances and adding substantially (0.23 to 0.88 PgC year-1) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink.

Aircraft-based inversions quantify the importance of wetlands and livestock for Upper Midwest methane emissions.

We apply airborne measurements across three seasons (summer, winter and spring 2017-2018) in a multi-inversion framework to quantify methane emissions from the US Corn Belt and Upper Midwest, a key agricultural and wetland source region. Combing our seasonal results with prior fall values we find that wetlands are the largest regional methane source (32 %, 20 [16-23] Gg/d), while livestock (enteric/manure; 25 %, 15 [14-17] Gg/d) are the largest anthropogenic source. Natural gas/petroleum, waste/landfills, and coal mines collectively make up the remainder. Optimized fluxes improve model agreement with independent datasets within and beyond the study timeframe. Inversions reveal coherent and seasonally dependent spatial errors in the WetCHARTs ensemble mean wetland emissions, with an underestimate for the Prairie Pothole region but an overestimate for Great Lakes coastal wetlands. Wetland extent and emission temperature dependence have the largest influence on prediction accuracy; better representation of coupled soil temperature-hydrology effects is therefore needed. Our optimized regional livestock emissions agree well with the Gridded EPA estimates during spring (to within 7 %) but are ∼25 % higher during summer and winter. Spatial analysis further shows good top-down and bottom-up agreement for beef facilities (with mainly enteric emissions) but larger (∼30 %) seasonal discrepancies for dairies and hog farms (with >40 % manure emissions). Findings thus support bottom-up enteric emission estimates but suggest errors for manure; we propose that the latter reflects inadequate treatment of management factors including field application. Overall, our results confirm the importance of intensive animal agriculture for regional methane emissions, implying substantial mitigation opportunities through improved management.

Fire decline in dry tropical ecosystems enhances decadal land carbon sink.

The terrestrial carbon sink has significantly increased in the past decades, but the underlying mechanisms are still unclear. The current synthesis of process-based estimates of land and ocean sinks requires an additional sink of 0.6 PgC yr-1 in the last decade to explain the observed airborne fraction. A concurrent global fire decline was observed in association with tropical agriculture expansion and landscape fragmentation. Here we show that a decline of 0.2 ± 0.1 PgC yr-1 in fire emissions during 2008-2014 relative to 2001-2007 also induced an additional carbon sink enhancement of 0.4 ± 0.2 PgC yr-1 attributable to carbon cycle feedbacks, amounting to a combined sink increase comparable to the 0.6 PgC yr-1 budget imbalance. Our results suggest that the indirect effects of fire, in addition to the direct emissions, is an overlooked mechanism for explaining decadal-scale changes in the land carbon sink and highlight the importance of fire management in climate mitigation.

Large loss of CO2 in winter observed across the northern permafrost region.

Recent warming in the Arctic, which has been amplified during the winter1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.

Response to Comment on "Contrasting carbon cycle responses of the tropical continents to the 2015-2016 El Niño".

Chevallier showed a column CO2 ([Formula: see text]) anomaly of ±0.5 parts per million forced by a uniform net biosphere exchange (NBE) anomaly of 2.5 gigatonnes of carbon over the tropical continents within a year, so he claimed that the inferred NBE uncertainties should be larger than presented in Liu et al We show that a much concentrated NBE anomaly led to much larger [Formula: see text] perturbations.

Accelerating rates of Arctic carbon cycling revealed by long-term atmospheric CO2 measurements.

The contemporary Arctic carbon balance is uncertain, and the potential for a permafrost carbon feedback of anywhere from 50 to 200 petagrams of carbon (Schuur et al., 2015) compromises accurate 21st-century global climate system projections. The 42-year record of atmospheric CO2 measurements at Barrow, Alaska (71.29 N, 156.79 W), reveals significant trends in regional land-surface CO2 anomalies (ΔCO2), indicating long-term changes in seasonal carbon uptake and respiration. Using a carbon balance model constrained by ΔCO2, we find a 13.4% decrease in mean carbon residence time (50% confidence range = 9.2 to 17.6%) in North Slope tundra ecosystems during the past four decades, suggesting a transition toward a boreal carbon cycling regime. Temperature dependencies of respiration and carbon uptake suggest that increases in cold season Arctic labile carbon release will likely continue to exceed increases in net growing season carbon uptake under continued warming trends.

Nongrowing season methane emissions-a significant component of annual emissions across northern ecosystems.

Wetlands are the single largest natural source of atmospheric methane (CH4 ), a greenhouse gas, and occur extensively in the northern hemisphere. Large discrepancies remain between "bottom-up" and "top-down" estimates of northern CH4 emissions. To explore whether these discrepancies are due to poor representation of nongrowing season CH4 emissions, we synthesized nongrowing season and annual CH4 flux measurements from temperate, boreal, and tundra wetlands and uplands. Median nongrowing season wetland emissions ranged from 0.9 g/m2 in bogs to 5.2 g/m2 in marshes and were dependent on moisture, vegetation, and permafrost. Annual wetland emissions ranged from 0.9 g m-2  year-1 in tundra bogs to 78 g m-2  year-1 in temperate marshes. Uplands varied from CH4 sinks to CH4 sources with a median annual flux of 0.0 ± 0.2 g m-2  year-1 . The measured fraction of annual CH4 emissions during the nongrowing season (observed: 13% to 47%) was significantly larger than that was predicted by two process-based model ensembles, especially between 40° and 60°N (modeled: 4% to 17%). Constraining the model ensembles with the measured nongrowing fraction increased total nongrowing season and annual CH4 emissions. Using this constraint, the modeled nongrowing season wetland CH4 flux from >40° north was 6.1 ± 1.5 Tg/year, three times greater than the nongrowing season emissions of the unconstrained model ensemble. The annual wetland CH4 flux was 37 ± 7 Tg/year from the data-constrained model ensemble, 25% larger than the unconstrained ensemble. Considering nongrowing season processes is critical for accurately estimating CH4 emissions from high-latitude ecosystems, and necessary for constraining the role of wetland emissions in a warming climate.

Reduced biomass burning emissions reconcile conflicting estimates of the post-2006 atmospheric methane budget.

Several viable but conflicting explanations have been proposed to explain the recent ~8 p.p.b. per year increase in atmospheric methane after 2006, equivalent to net emissions increase of ~25 Tg CH4 per year. A concurrent increase in atmospheric ethane implicates a fossil source; a concurrent decrease in the heavy isotope content of methane points toward a biogenic source, while other studies propose a decrease in the chemical sink (OH). Here we show that biomass burning emissions of methane decreased by 3.7 (±1.4) Tg CH4 per year from the 2001-2007 to the 2008-2014 time periods using satellite measurements of CO and CH4, nearly twice the decrease expected from prior estimates. After updating both the total and isotopic budgets for atmospheric methane with these revised biomass burning emissions (and assuming no change to the chemical sink), we find that fossil fuels contribute between 12-19 Tg CH4 per year to the recent atmospheric methane increase, thus reconciling the isotopic- and ethane-based results.

Contrasting carbon cycle responses of the tropical continents to the 2015-2016 El Niño.

The 2015-2016 El Niño led to historically high temperatures and low precipitation over the tropics, while the growth rate of atmospheric carbon dioxide (CO2) was the largest on record. Here we quantify the response of tropical net biosphere exchange, gross primary production, biomass burning, and respiration to these climate anomalies by assimilating column CO2, solar-induced chlorophyll fluorescence, and carbon monoxide observations from multiple satellites. Relative to the 2011 La Niña, the pantropical biosphere released 2.5 ± 0.34 gigatons more carbon into the atmosphere in 2015, consisting of approximately even contributions from three tropical continents but dominated by diverse carbon exchange processes. The heterogeneity of the carbon-exchange processes indicated here challenges previous studies that suggested that a single dominant process determines carbon cycle interannual variability.

Hypotheses for Near-Surface Exchange of Methane on Mars.

UNLABELLED: The Curiosity rover recently detected a background of 0.7 ppb and spikes of 7 ppb of methane on Mars. This in situ measurement reorients our understanding of the martian environment and its potential for life, as the current theories do not entail any geological source or sink of methane that varies sub-annually. In particular, the 10-fold elevation during the southern winter indicates episodic sources of methane that are yet to be discovered. Here we suggest a near-surface reservoir could explain this variability. Using the temperature and humidity measurements from the rover, we find that perchlorate salts in the regolith deliquesce to form liquid solutions, and deliquescence progresses to deeper subsurface in the season of the methane spikes. We therefore formulate the following three testable hypotheses. The first scenario is that the regolith in Gale Crater adsorbs methane when dry and releases this methane to the atmosphere upon deliquescence. The adsorption energy needs to be 36 kJ mol(-1) to explain the magnitude of the methane spikes, higher than existing laboratory measurements. The second scenario is that microorganisms convert organic matter in the soil to methane when they are in liquid solutions. This scenario does not require regolith adsorption but entails extant life on Mars. The third scenario is that deep subsurface aquifers produce the bursts of methane. Continued in situ measurements of methane and water, as well as laboratory studies of adsorption and deliquescence, will test these hypotheses and inform the existence of the near-surface reservoir and its exchange with the atmosphere. KEY WORDS: Mars-Methane-Astrobiology-Regolith. Astrobiology 16, 539-550.

The decadal state of the terrestrial carbon cycle: Global retrievals of terrestrial carbon allocation, pools, and residence times.

The terrestrial carbon cycle is currently the least constrained component of the global carbon budget. Large uncertainties stem from a poor understanding of plant carbon allocation, stocks, residence times, and carbon use efficiency. Imposing observational constraints on the terrestrial carbon cycle and its processes is, therefore, necessary to better understand its current state and predict its future state. We combine a diagnostic ecosystem carbon model with satellite observations of leaf area and biomass (where and when available) and soil carbon data to retrieve the first global estimates, to our knowledge, of carbon cycle state and process variables at a 1° × 1° resolution; retrieved variables are independent from the plant functional type and steady-state paradigms. Our results reveal global emergent relationships in the spatial distribution of key carbon cycle states and processes. Live biomass and dead organic carbon residence times exhibit contrasting spatial features (r = 0.3). Allocation to structural carbon is highest in the wet tropics (85-88%) in contrast to higher latitudes (73-82%), where allocation shifts toward photosynthetic carbon. Carbon use efficiency is lowest (0.42-0.44) in the wet tropics. We find an emergent global correlation between retrievals of leaf mass per leaf area and leaf lifespan (r = 0.64-0.80) that matches independent trait studies. We show that conventional land cover types cannot adequately describe the spatial variability of key carbon states and processes (multiple correlation median = 0.41). This mismatch has strong implications for the prediction of terrestrial carbon dynamics, which are currently based on globally applied parameters linked to land cover or plant functional types.

Are inventory based and remotely sensed above-ground biomass estimates consistent?

Carbon emissions resulting from deforestation and forest degradation are poorly known at local, national and global scales. In part, this lack of knowledge results from uncertain above-ground biomass estimates. It is generally assumed that using more sophisticated methods of estimating above-ground biomass, which make use of remote sensing, will improve accuracy. We examine this assumption by calculating, and then comparing, above-ground biomass area density (AGBD) estimates from studies with differing levels of methodological sophistication. We consider estimates based on information from nine different studies at the scale of Africa, Mozambique and a 1160 km(2) study area within Mozambique. The true AGBD is not known for these scales and so accuracy cannot be determined. Instead we consider the overall precision of estimates by grouping different studies. Since an the accuracy of an estimate cannot exceed its precision, this approach provides an upper limit on the overall accuracy of the group. This reveals poor precision at all scales, even between studies that are based on conceptually similar approaches. Mean AGBD estimates for Africa vary from 19.9 to 44.3 Mg ha(-1), for Mozambique from 12.7 to 68.3 Mg ha(-1), and for the 1160 km(2) study area estimates range from 35.6 to 102.4 Mg ha(-1). The original uncertainty estimates for each study, when available, are generally small in comparison with the differences between mean biomass estimates of different studies. We find that increasing methodological sophistication does not appear to result in improved precision of AGBD estimates, and moreover, inadequate estimates of uncertainty obscure any improvements in accuracy. Therefore, despite the clear advantages of remote sensing, there is a need to improve remotely sensed AGBD estimates if they are to provide accurate information on above-ground biomass. In particular, more robust and comprehensive uncertainty estimates are needed.

Global methane emission estimates from ultraviolet irradiation of terrestrial plant foliage.

SUMMARY: *Several studies have reported in situ methane (CH(4)) emissions from vegetation foliage, but there remains considerable debate about its significance as a global source. Here, we report a study that evaluates the role of ultraviolet (UV) radiation-driven CH(4) emissions from foliar pectin as a global CH(4) source. *We combine a relationship for spectrally weighted CH(4) production from pectin with a global UV irradiation climatology model, satellite-derived leaf area index (LAI) and air temperature data to estimate the potential global CH(4) emissions from vegetation foliage. *Our results suggest that global foliar CH(4) emissions from UV-irradiated pectin could account for 0.2-1.0 Tg yr(-1), of which 60% is from tropical latitudes, corresponding to < 0.2% of total CH(4) sources. *Our estimate is one to two orders of magnitude lower than previous estimates of global foliar CH(4) emissions. Recent studies have reported that pectin is not the only molecular source of UV-driven CH(4) emissions and that other environmental stresses may also generate CH(4). Consequently, further evaluation of such mechanisms of CH(4) generation is needed to confirm the contribution of foliage to the global CH(4) budget.

Large-scale controls of methanogenesis inferred from methane and gravity spaceborne data.

Wetlands are the largest individual source of methane (CH4), but the magnitude and distribution of this source are poorly understood on continental scales. We isolated the wetland and rice paddy contributions to spaceborne CH4 measurements over 2003-2005 using satellite observations of gravity anomalies, a proxy for water-table depth Gamma, and surface temperature analyses TS. We find that tropical and higher-latitude CH4 variations are largely described by Gamma and TS variations, respectively. Our work suggests that tropical wetlands contribute 52 to 58% of global emissions, with the remainder coming from the extra-tropics, 2% of which is from Arctic latitudes. We estimate a 7% rise in wetland CH4 emissions over 2003-2007, due to warming of mid-latitude and Arctic wetland regions, which we find is consistent with recent changes in atmospheric CH4.