Microbial carbon use efficiency promotes global soil carbon storage.

Soils store more carbon than other terrestrial ecosystems1,2. How soil organic carbon (SOC) forms and persists remains uncertain1,3, which makes it challenging to understand how it will respond to climatic change3,4. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss5-7. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways4,6,8-11, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes12,13. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved7,14,15. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.

Extreme drought impacts have been underestimated in grasslands and shrublands globally.

Climate change is increasing the frequency and severity of short-term (~1 y) drought events-the most common duration of drought-globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function-aboveground net primary production (ANPP)-was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

A meta-analysis highlights globally widespread potassium limitation in terrestrial ecosystems.

Potassium (K+ ) is the most abundant inorganic cation in plant cells, playing a critical role in various plant functions. However, the impacts of K on natural terrestrial ecosystems have been less studied compared with nitrogen (N) and phosphorus (P). Here, we present a global meta-analysis aimed at quantifying the response of aboveground production to K addition. This analysis is based on 144 field K fertilization experiments. We also investigate the influences of climate, soil properties, ecosystem types, and fertilizer regimes on the responses of aboveground production. We find that: K addition significantly increases aboveground production by 12.3% (95% CI: 7.4-17.5%), suggesting a widespread occurrence of K limitation across terrestrial ecosystems; K limitation is more prominent in regions with humid climates, acidic soils, or weathered soils; the effect size of K addition varies among climate zones/regions, and is influenced by multiple factors; and previous N : K and K : P thresholds utilized to detect K limitation in wetlands cannot be applied to other biomes. Our findings emphasize the role of K in limiting terrestrial productivity, which should be integrated into future terrestrial ecosystems models.

Global evidence for joint effects of multiple natural and anthropogenic drivers on soil nitrogen cycling.

Global soil nitrogen (N) cycling remains poorly understood due to its complex driving mechanisms. Here, we present a comprehensive analysis of global soil δ15N, a stable isotopic signature indicative of the N input-output balance, using a machine-learning approach on 10,676 observations from 2670 sites. Our findings reveal prevalent joint effects of climatic conditions, plant N-use strategies, soil properties, and other natural and anthropogenic forcings on global soil δ15N. The joint effects of multiple drivers govern the latitudinal distribution of soil δ15N, with more rapid N cycling at lower latitudes than at higher latitudes. In contrast to previous climate-focused models, our data-driven model more accurately simulates spatial changes in global soil δ15N, highlighting the need to consider the joint effects of multiple drivers to estimate the Earth's N budget. These insights contribute to the reconciliation of discordances among empirical, theoretical, and modeling studies on soil N cycling, as well as sustainable N management.

Convergence in simulating global soil organic carbon by structurally different models after data assimilation.

Current biogeochemical models produce carbon-climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first-order or Michaelis-Menten kinetics at the global scale. Nevertheless, a wider range of data with high-quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics-function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

Shifts in soil ammonia-oxidizing community maintain the nitrogen stimulation of nitrification across climatic conditions.

Anthropogenic nitrogen (N) loading alters soil ammonia-oxidizing archaea (AOA) and bacteria (AOB) abundances, likely leading to substantial changes in soil nitrification. However, the factors and mechanisms determining the responses of soil AOA:AOB and nitrification to N loading are still unclear, making it difficult to predict future changes in soil nitrification. Herein, we synthesize 68 field studies around the world to evaluate the impacts of N loading on soil ammonia oxidizers and nitrification. Across a wide range of biotic and abiotic factors, climate is the most important driver of the responses of AOA:AOB to N loading. Climate does not directly affect the N-stimulation of nitrification, but does so via climate-related shifts in AOA:AOB. Specifically, climate modulates the responses of AOA:AOB to N loading by affecting soil pH, N-availability and moisture. AOB play a dominant role in affecting nitrification in dry climates, while the impacts from AOA can exceed AOB in humid climates. Together, these results suggest that climate-related shifts in soil ammonia-oxidizing community maintain the N-stimulation of nitrification, highlighting the importance of microbial community composition in mediating the responses of the soil N cycle to N loading.

A stoichiometric approach to estimate sources of mineral-associated soil organic matter.

Mineral-associated soil organic matter (MAOM) is the largest, slowest cycling pool of carbon (C) in the terrestrial biosphere. MAOM is primarily derived from plant and microbial sources, yet the relative contributions of these two sources to MAOM remain unresolved. Resolving this issue is essential for managing and modeling soil carbon responses to environmental change. Microbial biomarkers, particularly amino sugars, are the primary method used to estimate microbial versus plant contributions to MAOM, despite systematic biases associated with these estimates. There is a clear need for independent lines of evidence to help determine the relative importance of plant versus microbial contributions to MAOM. Here, we synthesized 288 datasets of C/N ratios for MAOM, particulate organic matter (POM), and microbial biomass across the soils of forests, grasslands, and croplands. Microbial biomass is the source of microbial residues that form MAOM, whereas the POM pool is the direct precursor of plant residues that form MAOM. We then used a stoichiometric approach-based on two-pool, isotope-mixing models-to estimate the proportional contribution of plant residue (POM) versus microbial sources to the MAOM pool. Depending on the assumptions underlying our approach, microbial inputs accounted for between 34% and 47% of the MAOM pool, whereas plant residues contributed 53%-66%. Our results therefore challenge the existing hypothesis that microbial contributions are the dominant constituents of MAOM. We conclude that biogeochemical theory and models should account for multiple pathways of MAOM formation, and that multiple independent lines of evidence are required to resolve where and when plant versus microbial contributions are dominant in MAOM formation.

Quantitative evaluation of morphological and functional changes in meibomian glands and lipid layer thickness in patients with and without keratoconus.

PURPOSE: To quantitatively evaluate the morphological parameters of meibomian glands (MGs) and lipid layer thickness (LLT) in patients with keratoconus (KC). METHODS: In this prospective, cross-sectional study, 164 eyes of 164 keratoconus patients and 64 eyes of 64 age-matched control subjects were included. An advanced automatic MG analyzer was used to quantitatively measure the morphological and functional parameters of MGs. Morphological and functional parameters of MGs, LLT, and other ocular surface parameters were compared between the control and KC groups. RESULTS: The mean meibomian gland diameter, length, square, and gland area ratio (GA) were all significantly decreased in the KC group (all P < 0.05), while no significant difference was observed in the gland tortuosity index (TI) and gland signal index (SI) between the KC and control groups (all P > 0.05). There was no significant difference in the number of total and incomplete blinking among patients with different stages of keratoconus (all P > 0.05). The gland diameter, square, and TI were all negatively associated with KC severity (all P < 0.05), while no significant difference was observed among all stages of KC in gland length, GA, and SI (all P > 0.05). Moreover, the LLTs were positively correlated with the gland diameter, square, GA, and TI and negatively correlated with anterior corneal curvature or KC severity (all P < 0.05). CONCLUSIONS: Atrophic morphological changes in the meibomian glands were closely correlated with the severity of keratoconus. Gland diameter may be a sensitive functional morphology metric of meibomian glands in patients with keratoconus.

Nitrogen deposition accelerates soil carbon sequestration in tropical forests.

Terrestrial ecosystem carbon (C) sequestration plays an important role in ameliorating global climate change. While tropical forests exert a disproportionately large influence on global C cycling, there remains an open question on changes in below-ground soil C stocks with global increases in nitrogen (N) deposition, because N supply often does not constrain the growth of tropical forests. We quantified soil C sequestration through more than a decade of continuous N addition experiment in an N-rich primary tropical forest. Results showed that long-term N additions increased soil C stocks by 7 to 21%, mainly arising from decreased C output fluxes and physical protection mechanisms without changes in the chemical composition of organic matter. A meta-analysis further verified that soil C sequestration induced by excess N inputs is a general phenomenon in tropical forests. Notably, soil N sequestration can keep pace with soil C, based on consistent C/N ratios under N additions. These findings provide empirical evidence that below-ground C sequestration can be stimulated in mature tropical forests under excess N deposition, which has important implications for predicting future terrestrial sinks for both elevated anthropogenic CO2 and N deposition. We further developed a conceptual model hypothesis depicting how soil C sequestration happens under chronic N deposition in N-limited and N-rich ecosystems, suggesting a direction to incorporate N deposition and N cycling into terrestrial C cycle models to improve the predictability on C sink strength as enhanced N deposition spreads from temperate into tropical systems.

Nitrogen use strategy drives interspecific differences in plant photosynthetic CO2 acclimation.

Rising atmospheric CO2 concentration triggers an emergent phenomenon called plant photosynthetic acclimation to elevated CO2 (PAC). PAC is often characterized by a reduction in leaf photosynthetic capacity (Asat ), which varies dramatically along the continuum of plant phylogeny. However, it remains unclear whether the mechanisms responsible for PAC are also different across plant phylogeny, especially between gymnosperms and angiosperms. Here, by compiling a dataset of 73 species, we found that although leaf Asat increased significantly from gymnosperms to angiosperms, there was no phylogenetic signal in the PAC magnitude along the phylogenetic continuum. Physio-morphologically, leaf nitrogen concentration (Nm ), photosynthetic nitrogen-use efficiency (PNUE), and leaf mass per area (LMA) dominated PAC for 36, 29, and 8 species, respectively. However, there was no apparent difference in PAC mechanisms across major evolutionary clades, with 75% of gymnosperms and 92% of angiosperms regulated by the combination of Nm and PNUE. There was a trade-off between Nm and PNUE in driving PAC across species, and PNUE dominated the long-term changes and inter-specific differences in Asat under elevated CO2 . These findings indicate that nitrogen-use strategy drives the acclimation of leaf photosynthetic capacity to elevated CO2 across terrestrial plant species.

Do not ignore the effects of phosphorus and potassium addition on microbial carbon use efficiency.

P or PK addition significantly affected microbial CUE. No significant linear correlation between respiration rates and microbial CUE under N addition when NP and NPK addition were excluded.

Dryness limits vegetation pace to cope with temperature change in warm regions.

Climate change leads to increasing temperature and more extreme hot and drought events. Ecosystem capability to cope with climate warming depends on vegetation's adjusting pace with temperature change. How environmental stresses impair such a vegetation pace has not been carefully investigated. Here we show that dryness substantially dampens vegetation pace in warm regions to adjust the optimal temperature of gross primary production (GPP) ( T opt GPP ) in response to change in temperature over space and time. T opt GPP spatially converges to an increase of 1.01°C (95% CI: 0.97, 1.05) per 1°C increase in the yearly maximum temperature (Tmax ) across humid or cold sites worldwide (37o S-79o N) but only 0.59°C (95% CI: 0.46, 0.74) per 1°C increase in Tmax across dry and warm sites. T opt GPP temporally changes by 0.81°C (95% CI: 0.75, 0.87) per 1°C interannual variation in Tmax at humid or cold sites and 0.42°C (95% CI: 0.17, 0.66) at dry and warm sites. Regardless of the water limitation, the maximum GPP (GPPmax ) similarly increases by 0.23 g C m-2 day-1 per 1°C increase in T opt GPP in either humid or dry areas. Our results indicate that the future climate warming likely stimulates vegetation productivity more substantially in humid than water-limited regions.

Across-model spread and shrinking in predicting peatland carbon dynamics under global change.

Large across-model spread in simulating land carbon (C) dynamics has been ubiquitously demonstrated in model intercomparison projects (MIPs), and became a major impediment in advancing climate change prediction. Thus, it is imperative to identify underlying sources of the spread. Here, we used a novel matrix approach to analytically pin down the sources of across-model spread in transient peatland C dynamics in response to a factorial combination of two atmospheric CO2 levels and five temperature levels. We developed a matrix-based MIP by converting the C cycle module of eight land models (i.e., TEM, CENTURY4, DALEC2, TECO, FBDC, CASA, CLM4.5 and ORCHIDEE) into eight matrix models. While the model average of ecosystem C storage was comparable to the measurement, the simulation differed largely among models, mainly due to inter-model difference in baseline C residence time. Models generally overestimated net ecosystem production (NEP), with a large spread that was mainly attributed to inter-model difference in environmental scalar. Based on the sources of spreads identified, we sequentially standardized model parameters to shrink simulated ecosystem C storage and NEP to almost none. Models generally captured the observed negative response of NEP to warming, but differed largely in the magnitude of response, due to differences in baseline C residence time and temperature sensitivity of decomposition. While there was a lack of response of NEP to elevated CO2 (eCO2 ) concentrations in the measurements, simulated NEP responded positively to eCO2 concentrations in most models, due to the positive responses of simulated net primary production. Our study used one case study in Minnesota peatland to demonstrate that the sources of across-model spreads in simulating transient C dynamics can be precisely traced to model structures and parameters, regardless of their complexity, given the protocol that all the matrix models were driven by the same gross primary production and environmental variables.

Accounting for herbaceous communities in process-based models will advance our understanding of "grassy" ecosystems.

Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

Vacuum-deposited Rb3CeI6 for deep-blue-light-emitting diodes.

Recently, perovskite light-emitting diodes (PeLEDs) have exhibited outstanding performance in next-generation high-definition display applications. However, compared with green and red PeLEDs, the development of efficient and stable blue PeLEDs to meet the requirement for a wide color gamut has been a challenge. Herein, we vacuum thermally deposited a film of the lead-free rare earth halide Rb3CeI6, which shows deep blue emission with peaks at 427 nm and 468 nm. Due to the parity-allowed 5d-4f transition of Ce(III), the excited-state lifetime is as short as 22.3 ns (427 nm) and 25 ns (468 nm), respectively. The photoluminescence quantum yield (PLQY) is optimized to 51% by regulating the nucleation and growth of Rb3CeI6 grains. In a prototype rare earth light-emitting diode (ReLED) device, a thin insulating Al2O3 layer (5 nm) is inserted between the electron transport layer (ETL) and the emitting layer (EML, Rb3CeI6) to balance the carriers and reduce the dark current. The device shows a maximum luminance and EQE of 98 cd m-2 and 0.67%, respectively, and the electroluminescence (EL) spectrum maintains stability with changes in the operating voltage. In addition, the corresponding CIE coordinate is (0.15, 0.06), which closely matches the Rec. 2020 standard (0.131, 0.046).

Resolving the Dust Bowl paradox of grassland responses to extreme drought.

During the 1930s Dust Bowl drought in the central United States, species with the C3 photosynthetic pathway expanded throughout C4-dominated grasslands. This widespread increase in C3 grasses during a decade of low rainfall and high temperatures is inconsistent with well-known traits of C3 vs. C4 pathways. Indeed, water use efficiency is generally lower, and photosynthesis is more sensitive to high temperatures in C3 than C4 species, consistent with the predominant distribution of C3 grasslands in cooler environments and at higher latitudes globally. We experimentally imposed extreme drought for 4 y in mixed C3/C4 grasslands in Kansas and Wyoming and, similar to Dust Bowl observations, also documented three- to fivefold increases in C3/C4 biomass ratios. To explain these paradoxical responses, we first analyzed long-term climate records to show that under nominal conditions in the central United States, C4 grasses dominate where precipitation and air temperature are strongly related (warmest months are wettest months). In contrast, C3 grasses flourish where precipitation inputs are less strongly coupled to warm temperatures. We then show that during extreme drought years, precipitation-temperature relationships weaken, and the proportion of precipitation falling during cooler months increases. This shift in precipitation seasonality provides a mechanism for C3 grasses to respond positively to multiyear drought, resolving the Dust Bowl paradox. Grasslands are globally important biomes and increasingly vulnerable to direct effects of climate extremes. Our findings highlight how extreme drought can indirectly alter precipitation seasonality and shift ecosystem phenology, affecting function in ways not predictable from key traits of C3 and C4 species.

Stimulation of ammonia oxidizer and denitrifier abundances by nitrogen loading: Poor predictability for increased soil N2 O emission.

Unprecedented nitrogen (N) inputs into terrestrial ecosystems have profoundly altered soil N cycling. Ammonia oxidizers and denitrifiers are the main producers of nitrous oxide (N2 O), but it remains unclear how ammonia oxidizer and denitrifier abundances will respond to N loading and whether their responses can predict N-induced changes in soil N2 O emission. By synthesizing 101 field studies worldwide, we showed that N loading significantly increased ammonia oxidizer abundance by 107% and denitrifier abundance by 45%. The increases in both ammonia oxidizer and denitrifier abundances were primarily explained by N loading form, and more specifically, organic N loading had stronger effects on their abundances than mineral N loading. Nitrogen loading increased soil N2 O emission by 261%, whereas there was no clear relationship between changes in soil N2 O emission and shifts in ammonia oxidizer and denitrifier abundances. Our field-based results challenge the laboratory-based hypothesis that increased ammonia oxidizer and denitrifier abundances by N loading would directly cause higher soil N2 O emission. Instead, key abiotic factors (mean annual precipitation, soil pH, soil C:N ratio, and ecosystem type) explained N-induced changes in soil N2 O emission. Altogether, these findings highlight the need for considering the roles of key abiotic factors in regulating soil N transformations under N loading to better understand the microbially mediated soil N2 O emission.

Variations and controlling factors of soil denitrification rate.

The denitrification process profoundly affects soil nitrogen (N) availability and generates its byproduct, nitrous oxide, as a potent greenhouse gas. There are large uncertainties in predicting global denitrification because its controlling factors remain elusive. In this study, we compiled 4301 observations of denitrification rates across a variety of terrestrial ecosystems from 214 papers published in the literature. The averaged denitrification rate was 3516.3 ± 91.1 µg N kg-1  soil day-1 . The highest denitrification rate was 4242.3 ± 152.3 µg N kg-1  soil day-1 under humid subtropical climates, and the lowest was 965.8 ± 150.4 µg N kg-1 under dry climates. The denitrification rate increased with temperature, precipitation, soil carbon and N contents, as well as microbial biomass carbon and N, but decreased with soil clay contents. The variables related to soil N contents (e.g., nitrate, ammonium, and total N) explained the variation of denitrification more than climatic and edaphic variables (e.g., mean annual temperature (MAT), soil moisture, soil pH, and clay content) according to structural equation models. Soil microbial biomass carbon, which was influenced by soil nitrate, ammonium, and total N, also strongly influenced denitrification at a global scale. Collectively, soil N contents, microbial biomass, pH, texture, moisture, and MAT accounted for 60% of the variation in global denitrification rates. The findings suggest that soil N contents and microbial biomass are strong predictors of denitrification at the global scale.

Responses of tundra soil microbial communities to half a decade of experimental warming at two critical depths.

Northern-latitude tundra soils harbor substantial carbon (C) stocks that are highly susceptible to microbial degradation with rising global temperatures. Understanding the magnitude and direction (e.g., C release or sequestration) of the microbial responses to warming is necessary to accurately model climate change. In this study, Alaskan tundra soils were subjected to experimental in situ warming by ∼1.1 °C above ambient temperature, and the microbial communities were evaluated using metagenomics after 4.5 years, at 2 depths: 15 to 25 cm (active layer at outset of the experiment) and 45 to 55 cm (transition zone at the permafrost/active layer boundary at the outset of the experiment). In contrast to small or insignificant shifts after 1.5 years of warming, 4.5 years of warming resulted in significant changes to the abundances of functional traits and the corresponding taxa relative to control plots (no warming), and microbial shifts differed qualitatively between the two soil depths. At 15 to 25 cm, increased abundances of carbohydrate utilization genes were observed that correlated with (increased) measured ecosystem carbon respiration. At the 45- to 55-cm layer, increased methanogenesis potential was observed, which corresponded with a 3-fold increase in abundance of a single archaeal clade of the Methanosarcinales order, increased annual thaw duration (45.3 vs. 79.3 days), and increased CH4 emissions. Collectively, these data demonstrate that the microbial responses to warming in tundra soil are rapid and markedly different between the 2 critical soil layers evaluated, and identify potential biomarkers for the corresponding microbial processes that could be important in modeling.