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.

Strong isoprene emission response to temperature in tundra vegetation.

Emissions of biogenic volatile organic compounds (BVOCs) are a crucial component of biosphere-atmosphere interactions. In northern latitudes, climate change is amplified by feedback processes in which BVOCs have a recognized, yet poorly quantified role, mainly due to a lack of measurements and concomitant modeling gaps. Hence, current Earth system models mostly rely on temperature responses measured on vegetation from lower latitudes, rendering their predictions highly uncertain. Here, we show how tundra isoprene emissions respond vigorously to temperature increases, compared to model results. Our unique dataset of direct eddy covariance ecosystem-level isoprene measurements in two contrasting ecosystems exhibited Q10 (the factor by which the emission rate increases with a 10 °C rise in temperature) temperature coefficients of up to 20.8, that is, 3.5 times the Q10 of 5.9 derived from the equivalent model calculations. Crude estimates using the observed temperature responses indicate that tundra vegetation could enhance their isoprene emissions by up to 41% (87%)-that is, 46% (55%) more than estimated by models-with a 2 °C (4 °C) warming. Our results demonstrate that tundra vegetation possesses the potential to substantially boost its isoprene emissions in response to future rising temperatures, at rates that exceed the current Earth system model predictions.

Shedding light on the increased carbon uptake by a boreal forest under diffuse solar radiation across multiple scales.

Solar radiation is scattered by cloud cover, aerosols and other particles in the atmosphere, all of which are affected by global changes. Furthermore, the diffuse fraction of solar radiation is increased by more frequent forest fires and likewise would be if climate interventions such as stratospheric aerosol injection were adopted. Forest ecosystem studies predict that an increase in diffuse radiation would result in higher productivity, but ecophysiological data are required to identify the processes responsible within the forest canopy. In our study, the response of a boreal forest to direct, diffuse and heterogeneous solar radiation conditions was examined during the daytime in the growing season to determine how carbon uptake is affected by radiation conditions at different scales. A 10-year data set of ecosystem, shoot and forest floor vegetation carbon and water-flux data was examined. Ecosystem-level carbon assimilation was higher under diffuse radiation conditions in comparison with direct radiation conditions at equivalent total photosynthetically active radiation (PAR). This was driven by both an increase in shoot and forest floor vegetation photosynthetic rate. Most notably, ecosystem-scale productivity was strongly related to the absolute amount of diffuse PAR, since it integrates both changes in total PAR and diffuse fraction. This finding provides a gateway to explore the processes by which absolute diffuse PAR enhances productivity, and the long-term persistence of this effect under scenarios of higher global diffuse radiation.

Methane fluxes in tidal marshes of the conterminous United States.

Methane (CH4) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre-industrial times. Wetlands account for a large share of global CH4 emissions, yet the magnitude and factors controlling CH4 fluxes in tidal wetlands remain uncertain. We synthesized CH4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH4 emissions. This effort included creating an open-source database of chamber-based GHG fluxes (https://doi.org/10.25573/serc.14227085). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH4 m-2 year-1, with a median of 3.9 g CH4 m-2 year-1, and only 25% of sites exceeding 18 g CH4 m-2 year-1. The highest fluxes were observed at fresh-oligohaline sites with daily maximum temperature normals (MATmax) above 25.6°C. These were followed by frequently inundated low and mid-fresh-oligohaline marshes with MATmax ≤25.6°C, and mesohaline sites with MATmax >19°C. Quantile regressions of paired chamber CH4 flux and porewater biogeochemistry revealed that the 90th percentile of fluxes fell below 5 ± 3 nmol m-2 s-1 at sulfate concentrations >4.7 ± 0.6 mM, porewater salinity >21 ± 2 psu, or surface water salinity >15 ± 3 psu. Across sites, salinity was the dominant predictor of annual CH4 fluxes, while within sites, temperature, gross primary productivity (GPP), and tidal height controlled variability at diel and seasonal scales. At the diel scale, GPP preceded temperature in importance for predicting CH4 flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH4 fluxes, with pulsed releases of stored CH4 at low to rising tide. This study provides data and methods to improve tidal marsh CH4 emission estimates, support blue carbon assessments, and refine national and global GHG inventories.

Decoding autumn phenology: Unraveling the link between observation methods and detected environmental cues.

Leaf coloring and fall mark the end of the growing season (EOS), playing essential roles in nutrient cycling, resource allocation, ecological interactions, and as climate change indicators. However, understanding future changes in autumn phenology is challenging due to the multitude of likely environmental cues and substantial variations in timing caused by different derivation methods. Yet, it remains unclear whether these two factors are independent or if methodological uncertainties influence the environmental cues determined. We derived start of growing season (SOS) and EOS at a mixed beech forest in Central Germany for the period 2000-2020 based on four different derivation methods using a unique long-term data set of in-situ data, canopy imagery, eddy covariance measurements, and satellite remote sensing data and determined their influence on a predictor analysis of leaf senescence. Both SOS and EOS exhibited substantial ranges in mean onset dates (39.5 and 28.6 days, respectively) across the different methods, although inter-annual variations and advancing SOS trends were similar across methods. Depending on the data, EOS trends were advanced or delayed, but inter-annual patterns correlated well (mean r = .46). Overall, warm, dry, and less photosynthetically productive growing seasons were more likely to be associated with a delayed EOS, while colder, wetter, and more photosynthetically productive vegetation periods resulted in an earlier EOS. In addition, contrary to recent results, no clear influence of pre-solstice vegetation activity on the timing of senescence was detected. However, most notable were the large differences in sign and strength of potential drivers both in the univariate and multivariate analyses when comparing derivation methodologies. The results suggest that an ensemble analysis of all available phenological data sources and derivation methods is needed for general statements on autumn phenology and its influencing variables and correct implementation of the senescence process in ecosystem models.

Aerodynamic effects cause higher forest evapotranspiration and water yield reductions after wildfires in tall forests.

Wildfires are increasing in frequency, intensity, and extent globally due to climate change and they can alter forest composition, structure, and function. The destruction and subsequent regrowth of young vegetation can modify the ecosystem evapotranspiration and downstream water availability. However, the response of forest recovery on hydrology is not well known with even the sign of evapotranspiration and water yield changes following forest fires being uncertain across the globe. Here, we quantify the effects of forest regrowth after catastrophic wildfires on evapotranspiration and runoff in the world's tallest angiosperm forest (Eucalyptus regnans) in Australia. We combine eddy covariance measurements including pre- and post-fire periods, mechanistic ecohydrological modeling and then extend the analysis spatially to multiple fires in eucalypt-dominated forests in south-eastern Australia by utilizing remote sensing. We find a fast recovery of evapotranspiration which reaches and exceeds pre-fire values within 2 years after the bushfire, a result confirmed by eddy covariance data, remote sensing, and modeling. Such a fast evapotranspiration recovery is likely generalizable to tall eucalypt forests in south-eastern Australia as shown by remote sensing. Once climate variability is discounted, ecohydrological modeling shows evapotranspiration rates from the recovering forest which reach peak values of +20% evapotranspiration 3 years post-fire. As a result, modeled runoff decreases substantially. Contrary to previous research, we find that the increase in modeled evapotranspiration is largely caused by the aerodynamic effects of a much shorter forest height leading to higher surface temperature, higher humidity gradients and therefore increased transpiration. However, increases in evapotranspiration as well as decreases in runoff caused by the young forest are constrained by energy and water limitations. Our result of an increase in evapotranspiration due to aerodynamic warming in a shorter forest after wildfires could occur in many parts of the world experiencing forest disturbances.

Nitrogen availability and summer drought, but not N:P imbalance, drive carbon use efficiency of a Mediterranean tree-grass ecosystem.

All ecosystems contain both sources and sinks for atmospheric carbon (C). A change in their balance of net and gross ecosystem carbon uptake, ecosystem-scale carbon use efficiency (CUEECO), is a change in their ability to buffer climate change. However, anthropogenic nitrogen (N) deposition is increasing N availability, potentially shifting terrestrial ecosystem stoichiometry towards phosphorus (P) limitation. Depending on how gross primary production (GPP, plants alone) and ecosystem respiration (RECO, plants and heterotrophs) are limited by N, P or associated changes in other biogeochemical cycles, CUEECO may change. Seasonally, CUEECO also varies as the multiple processes that control GPP and respiration and their limitations shift in time. We worked in a Mediterranean tree-grass ecosystem (locally called 'dehesa') characterized by mild, wet winters and summer droughts. We examined CUEECO from eddy covariance fluxes over 6 years under control, +N and + NP fertilized treatments on three timescales: annual, seasonal (determined by vegetation phenological phases) and 14-day aggregations. Finer aggregation allowed consideration of responses to specific patterns in vegetation activity and meteorological conditions. We predicted that CUEECO should be increased by wetter conditions, and successively by N and NP fertilization. Milder and wetter years with proportionally longer growing seasons increased CUEECO, as did N fertilization, regardless of whether P was added. Using a generalized additive model, whole ecosystem phenological status and water deficit indicators, which both varied with treatment, were the main determinants of 14-day differences in CUEECO. The direction of water effects depended on the timescale considered and occurred alongside treatment-dependent water depletion. Overall, future regional trends of longer dry summers may push these systems towards lower CUEECO.

Plant uptake of CO2 outpaces losses from permafrost and plant respiration on the Tibetan Plateau.

High-latitude and high-altitude regions contain vast stores of permafrost carbon. Climate warming may result in the release of CO2 from both the thawing of permafrost and accelerated autotrophic respiration, but it may also increase the fixation of CO2 by plants, which could relieve or even offset the CO2 losses. The Tibetan Plateau contains the largest area of alpine permafrost on Earth. However, the current status of the net CO2 balance and feedbacks to warming remain unclear, given that the region has recently experienced an atmospheric warming rate of over 0.3 °C decade-1 We examined 32 eddy covariance sites and found an unexpected net CO2 sink during 2002 to 2020 (26 of the sites yielded a net CO2 sink) that was four times the amount previously estimated. The CO2 sink peaked at an altitude of roughly 4,000 m, with the sink at lower and higher altitudes limited by a low carbon use efficiency and a cold, dry climate, respectively. The fixation of CO2 in summer is more dependent on temperature than the loss of CO2 than it is in the winter months, especially at higher altitudes. Consistently, 16 manipulative experiments and 18 model simulations showed that the fixation of CO2 by plants will outpace the loss of CO2 under a wetting-warming climate until the 2090s (178 to 318 Tg C y-1). We therefore suggest that there is a plant-dominated negative feedback to climate warming on the Tibetan Plateau.

Components explain, but do eddy fluxes constrain? Carbon budget of a nitrogen-fertilized boreal Scots pine forest.

Nitrogen (N) fertilization increases biomass and soil organic carbon (SOC) accumulation in boreal pine forests, but the underlying mechanisms remain uncertain. At two Scots pine sites, one undergoing annual N fertilization and the other a reference, we sought to explain these responses. We measured component fluxes, including biomass production, SOC accumulation, and respiration, and summed them into carbon budgets. We compared the resulting summations to ecosystem fluxes measured by eddy covariance. N fertilization increased most component fluxes (P < 0.05), especially SOC accumulation (20×). Only fine-root, mycorrhiza, and exudate production decreased, by 237 (SD = 28) g C m-2 yr-1 . Stemwood production increases were ascribed to this partitioning shift, gross primary production (GPP), and carbon-use efficiency, in that order. The methods agreed in their estimates of GPP in both stands (P > 0.05), but the components detected an increase in net ecosystem production (NEP) (190 (54) g C m-2 yr-1 ; P < 0.01) that eddy covariance did not (19 (62) g C m-2 yr-1 ; ns). The pairing of plots, the simplicity of the sites, and the strength of response provide a compelling description of N effects on the C budget. However, the disagreement between methods calls for further paired tests of N fertilization effects in simple forest ecosystems.

Estimating intraseasonal intrinsic water-use efficiency from high-resolution tree-ring δ13 C data in boreal Scots pine forests.

Intrinsic water-use efficiency (iWUE), a key index for carbon and water balance, has been widely estimated from tree-ring δ13 C at annual resolution, but rarely at high-resolution intraseasonal scale. We estimated high-resolution iWUE from laser-ablation δ13 C analysis of tree-rings (iWUEiso ) and compared it with iWUE derived from gas exchange (iWUEgas ) and eddy covariance (iWUEEC ) data for two Pinus sylvestris forests from 2002 to 2019. By carefully timing iWUEiso via modeled tree-ring growth, iWUEiso aligned well with iWUEgas and iWUEEC at intraseasonal scale. However, year-to-year patterns of iWUEgas , iWUEiso , and iWUEEC were different, possibly due to distinct environmental drivers on iWUE across leaf, tree, and ecosystem scales. We quantified the modification of iWUEiso by postphotosynthetic δ13 C enrichment from leaf sucrose to tree rings and by nonexplicit inclusion of mesophyll and photorespiration terms in photosynthetic discrimination model, which resulted in overestimation of iWUEiso by up to 11% and 14%, respectively. We thus extended the application of tree-ring δ13 C for iWUE estimates to high-resolution intraseasonal scale. The comparison of iWUEgas , iWUEiso , and iWUEEC provides important insights into physiological acclimation of trees across leaf, tree, and ecosystem scales under climate change and improves the upscaling of ecological models.

Quantifying effects of cold acclimation and delayed springtime photosynthesis resumption in northern ecosystems.

Land carbon dynamics in temperate and boreal ecosystems are sensitive to environmental change. Accurately simulating gross primary productivity (GPP) and its seasonality is key for reliable carbon cycle projections. However, significant biases have been found in early spring GPP simulations of northern forests, where observations often suggest a later resumption of photosynthetic activity than predicted by models. Here, we used eddy covariance-based GPP estimates from 39 forest sites that differ by their climate and dominant plant functional types. We used a mechanistic and an empirical light use efficiency (LUE) model to investigate the magnitude and environmental controls of delayed springtime photosynthesis resumption (DSPR) across sites. We found DSPR reduced ecosystem LUE by 30-70% at many, but not all site-years during spring. A significant depression of LUE was found not only in coniferous but also at deciduous forests and was related to combined high radiation and low minimum temperatures. By embedding cold-acclimation effects on LUE that considers the delayed effects of minimum temperatures, initial model bias in simulated springtime GPP was effectively resolved. This provides an approach to improve GPP estimates by considering physiological acclimation and enables more reliable simulations of photosynthesis in northern forests and projections in a warming climate.

The ecosystem wilting point defines drought response and recovery of a Quercus-Carya forest.

Soil and atmospheric droughts increasingly threaten plant survival and productivity around the world. Yet, conceptual gaps constrain our ability to predict ecosystem-scale drought impacts under climate change. Here, we introduce the ecosystem wilting point (ΨEWP ), a property that integrates the drought response of an ecosystem's plant community across the soil-plant-atmosphere continuum. Specifically, ΨEWP defines a threshold below which the capacity of the root system to extract soil water and the ability of the leaves to maintain stomatal function are strongly diminished. We combined ecosystem flux and leaf water potential measurements to derive the ΨEWP of a Quercus-Carya forest from an "ecosystem pressure-volume (PV) curve," which is analogous to the tissue-level technique. When community predawn leaf water potential (Ψpd ) was above ΨEWP (=-2.0 MPa), the forest was highly responsive to environmental dynamics. When Ψpd fell below ΨEWP , the forest became insensitive to environmental variation and was a net source of carbon dioxide for nearly 2 months. Thus, ΨEWP is a threshold defining marked shifts in ecosystem functional state. Though there was rainfall-induced recovery of ecosystem gas exchange following soaking rains, a legacy of structural and physiological damage inhibited canopy photosynthetic capacity. Although over 16 growing seasons, only 10% of Ψpd observations fell below ΨEWP , the forest is commonly only 2-4 weeks of intense drought away from reaching ΨEWP , and thus highly reliant on frequent rainfall to replenish the soil water supply. We propose, based on a bottom-up analysis of root density profiles and soil moisture characteristic curves, that soil water acquisition capacity is the major determinant of ΨEWP , and species in an ecosystem require compatible leaf-level traits such as turgor loss point so that leaf wilting is coordinated with the inability to extract further water from the soil.

Long-term changes in forest response to extreme atmospheric dryness.

Atmospheric dryness, as indicated by vapor pressure deficit (VPD), has a strong influence on forest greenhouse gas exchange with the atmosphere. In this study, we used long-term (10-30 years) net ecosystem productivity (NEP) measurements from 60 forest sites across the world (1003 site-years) to quantify long-term changes in forest NEP resistance and NEP recovery in response to extreme atmospheric dryness. We tested two hypotheses: first, across sites differences in NEP resistance and NEP recovery of forests will depend on both the biophysical characteristics (i.e., leaf area index [LAI] and forest type) of the forest as well as on the local meteorological conditions of the site (i.e., mean VPD of the site), and second, forests experiencing an increasing trend in frequency and intensity of extreme dryness will show an increasing trend in NEP resistance and NEP recovery over time due to emergence of long-term ecological stress memory. We used a data-driven statistical learning approach to quantify NEP resistance and NEP recovery over multiple years. Our results showed that forest types, LAI, and median local VPD conditions explained over 50% of variance in both NEP resistance and NEP recovery, with drier sites showing higher NEP resistance and NEP recovery compared to sites with less atmospheric dryness. The impact of extreme atmospheric dryness events on NEP lasted for up to 3 days following most severe extreme events in most forests, indicated by an NEP recovery of less than 100%. We rejected our second hypothesis as we found no consistent relationship between trends of extreme VPD with trends in NEP resistance and NEP recovery across different forest sites, thus an increase in atmospheric dryness as it is predicted might not increase the resistance or recovery of forests in terms of NEP.

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates.

The recent rise in atmospheric methane (CH4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year-1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.

Environmental controls on the light use efficiency of terrestrial gross primary production.

Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf-level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy-level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C3 species; however, additional assumptions are required to "scale up" from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed-effects model. The same model design was fitted to site-based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple "goodness of fit" comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

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.

Asymmetric response of Amazon forest water and energy fluxes to wet and dry hydrological extremes reveals onset of a local drought-induced tipping point.

Understanding the effects of intensification of Amazon basin hydrological cycling-manifest as increasingly frequent floods and droughts-on water and energy cycles of tropical forests is essential to meeting the challenge of predicting ecosystem responses to climate change, including forest "tipping points". Here, we investigated the impacts of hydrological extremes on forest function using 12+ years of observations (between 2001-2020) of water and energy fluxes from eddy covariance, along with associated ecological dynamics from biometry, at the Tapajós National Forest. Measurements encompass the strong 2015-2016 El Niño drought and La Niña 2008-2009 wet events. We found that the forest responded strongly to El Niño-Southern Oscillation (ENSO): Drought reduced water availability for evapotranspiration (ET) leading to large increases in sensible heat fluxes (H). Partitioning ET by an approach that assumes transpiration (T) is proportional to photosynthesis, we found that water stress-induced reductions in canopy conductance (Gs ) drove T declines partly compensated by higher evaporation (E). By contrast, the abnormally wet La Niña period gave higher T and lower E, with little change in seasonal ET. Both El Niño-Southern Oscillation (ENSO) events resulted in changes in forest structure, manifested as lower wet-season leaf area index. However, only during El Niño 2015-2016, we observed a breakdown in the strong meteorological control of transpiration fluxes (via energy availability and atmospheric demand) because of slowing vegetation functions (via shutdown of Gs and significant leaf shedding). Drought-reduced T and Gs , higher H and E, amplified by feedbacks with higher temperatures and vapor pressure deficits, signaled that forest function had crossed a threshold, from which it recovered slowly, with delay, post-drought. Identifying such tipping point onsets (beyond which future irreversible processes may occur) at local scale is crucial for predicting basin-scale threshold-crossing changes in forest energy and water cycling, leading to slow-down in forest function, potentially resulting in Amazon forests shifting into alternate degraded states.

Improved net carbon budgets in the US Midwest through direct measured impacts of enhanced weathering.

Terrestrial enhanced weathering (EW) through the application of Mg- or Ca-rich rock dust to soil is a negative emission technology with the potential to address impacts of climate change. The effectiveness of EW was tested over 4 years by spreading ground basalt (50 t ha-1 year-1 ) on maize/soybean and miscanthus cropping systems in the Midwest US. The major elements of the carbon budget were quantified through measurements of eddy covariance, soil carbon flux, and biomass. The movement of Mg and Ca to deep soil, released by weathering, balanced by a corresponding alkalinity flux, was used to measure the drawdown of CO2 , where the release of cations from basalt was measured as the ratio of rare earth elements to base cations in the applied rock dust and in the surface soil. Basalt application stimulated peak biomass and net primary production in both cropping systems and caused a small but significant stimulation of soil respiration. Net ecosystem carbon balance (NECB) was strongly negative for maize/soybean (-199 to -453 g C m-2 year-1 ) indicating this system was losing carbon to the atmosphere. Average EW (102 g C m-2 year-1 ) offset carbon loss in the maize/soybean by 23%-42%. NECB of miscanthus was positive (63-129 g C m-2 year-1 ), indicating carbon gain in the system, and EW greatly increased inorganic carbon storage by an additional 234 g C m-2 year-1 . Our analysis indicates a co-deployment of a perennial biofuel crop (miscanthus) with EW leads to major wins-increased harvested yields of 29%-42% with additional carbon dioxide removal (CDR) of 8.6 t CO2 ha-1 year-1 . EW applied to maize/soybean drives a CDR of 3.7 t CO2 ha-1 year-1 , which partially offsets well-established carbon losses from soil from this crop rotation. EW applied in the US Midwest creates measurable improvements to the carbon budgets perennial bioenergy crops and conventional row crops.

Methane Emissions from Dairy Operations in California's San Joaquin Valley Evaluated Using Airborne Flux Measurements.

State inventories indicate that dairy operations account for nearly half of California's methane budget. Recent analyses suggest, however, that these emissions may be underestimated, complicating efforts to develop emission reduction strategies. Here, we report estimates of dairy methane emissions in the southern San Joaquin Valley (SJV) of California in June 2021 using airborne flux measurements. We find average dairy methane fluxes of 512 ± 178 mg m-2 h-1 from a region of 300+ dairies near Visalia, CA using a combination of eddy covariance and mass balance-based techniques, corresponding to 118 ± 41 kg dairy-1 h-1. These values estimated during our June campaign are 39 ± 48% larger than annual average estimates from the recently developed VISTA-CA inventory. We observed notable increases in emissions with temperature. Our estimates align well with inventory predictions when parametrizations for the temperature dependence of emissions are applied. Our measurements further demonstrate that the VISTA-CA emission inventory is considerably more accurate than the EPA GHG-I inventory in this region. Source apportionment analyses confirm that dairy operations produce the majority of methane emissions in the southern SJV (∼65%). Fugitive oil and gas (O&G) sources account for the remaining ∼35%. Our results support the accuracy of the process-based models used to develop dairy emission inventories and highlight the need for additional investigation of the meteorological dependence of these emissions.

Revisiting particle dry deposition and its role in radiative effect estimates.

Wet and dry deposition remove aerosols from the atmosphere, and these processes control aerosol lifetime and thus impact climate and air quality. Dry deposition is a significant source of aerosol uncertainty in global chemical transport and climate models. Dry deposition parameterizations in most global models were developed when few particle deposition measurements were available. However, new measurement techniques have enabled more size-resolved particle flux observations. We combined literature measurements with data that we collected over a grassland in Oklahoma and a pine forest in Colorado to develop a dry deposition parameterization. We find that relative to observations, previous parameterizations overestimated deposition of the accumulation and Aitken mode particles, and underestimated in the coarse mode. These systematic differences in observed and modeled accumulation mode particle deposition velocities are as large as an order of magnitude over terrestrial ecosystems. As accumulation mode particles form most of the cloud condensation nuclei (CCN) that influence the indirect radiative effect, this model-measurement discrepancy in dry deposition alters modeled CCN and radiative forcing. We present a revised observationally driven parameterization for regional and global aerosol models. Using this revised dry deposition scheme in the Goddard Earth Observing System (GEOS)-Chem chemical transport model, we find that global surface accumulation-mode number concentrations increase by 62% and enhance the global combined anthropogenic and natural aerosol indirect effect by -0.63 W m-2 Our observationally constrained approach should reduce the uncertainty of particle dry deposition in global chemical transport models.