Carbon-climate Feedbacks Research Articles

Evidence for the acclimation of ecosystem photosynthesis to soil moisture.

Ecosystem gross primary productivity (GPP) is the largest carbon flux between the atmosphere and biosphere and is strongly influenced by soil moisture. However, the response and acclimation of GPP to soil moisture remain poorly understood, leading to large uncertainties in characterizing the impact of soil moisture on GPP in Earth system models. Here we analyze the GPP-soil moisture response curves at 143 sites from the global FLUXNET. We find that GPP at 108 sites exhibits hump-shaped response curves with increasing soil moisture, and an apparent optimum soil moisture ( , at which GPP reaches the maximum) exists widely with large variability among sites and biomes around the globe. Variation in is mostly explained by local water availability, with drier ecosystems having lower than wetter ecosystems, reflecting the water acclimation of . This acclimation is further supported by a field experiment that only manipulates water and keeps other factors constant, which shows a downward shift in after long-term water deficit, and thus a lower soil water requirement to maximize GPP. These results provide compelling evidence for the widespread and its acclimation, shedding new light on understanding and predicting carbon-climate feedbacks.

Terrestrial photosynthesis inferred from plant carbonyl sulfide uptake.

Terrestrial photosynthesis, or gross primary production (GPP), is the largest carbon flux in the biosphere, but its global magnitude and spatiotemporal dynamics remain uncertain1. The global annual mean GPP is historically thought to be around 120 PgC yr-1 (refs. 2-6), which is about 30-50 PgC yr-1 lower than GPP inferred from the oxygen-18 (18O) isotope7 and soil respiration8. This disparity is a source of uncertainty in predicting climate-carbon cycle feedbacks9,10. Here we infer GPP from carbonyl sulfide, an innovative tracer for CO2 diffusion from ambient air to leaf chloroplasts through stomata and mesophyll layers. We demonstrate that explicitly representing mesophyll diffusion is important for accurately quantifying the spatiotemporal dynamics of carbonyl sulfide uptake by plants. From the estimate of carbonyl sulfide uptake by plants, we infer a global contemporary GPP of 157 (±8.5) PgC yr-1, which is consistent with estimates from 18O (150-175 PgC yr-1) and soil respiration ( PgC yr-1), but with an improved confidence level. Our global GPP is higher than satellite optical observation-driven estimates (120-140 PgC yr-1) that are used for Earth system model benchmarking. This difference predominantly occurs in the pan-tropical rainforests and is corroborated by ground measurements11, suggesting a more productive tropics than satellite-based GPP products indicated. As GPP is a primary determinant of terrestrial carbon sinks and may shape climate trajectories9,10, our findings lay a physiological foundation on which the understanding and prediction of carbon-climate feedbacks can be advanced.

Climate feedback from plant physiological responses to increasing atmospheric CO2 in Earth system models.

Plant physiological responses to increasing atmospheric CO2 concentration (iCO2), including enhanced photosynthesis and reduced stomatal conductance, impact regional and global climate. Here, I describe recent advances in understanding these effects through Earth system models (ESMs). Idealized simulations of a 1% annual iCO2 show that despite fertilization, CO2 physiological forcing contributes to 10% of warming and at least 30% of future precipitation decline in Amazonia. This reduces aboveground vegetation carbon storage and triggers positive carbon-climate feedback. ESM simulations indicate that reduced transpiration and increased heat stress from iCO2 could amplify meteorological drought and wildfire risks. Understanding these climate feedbacks is essential for improving carbon accounting in natural climate solutions, such as avoiding deforestation and reforestation, as iCO2 complicates assessing their climate benefits.

Direct Evidence for Microbial Regulation of the Temperature Sensitivity of Soil Carbon Decomposition.

Soil physicochemical protection, substrates, and microorganisms are thought to modulate the temperature sensitivity of soil carbon decomposition (Q10), but their regulatory roles have yet to be distinguished because of the confounding effects of concurrent changes of them. Here, we sought to differentiate these effects through microorganism reciprocal transplant and aggregate disruption experiments using soils collected from seven sites along a 5000-km latitudinal transect encompassing a wide range of climatic conditions and from a 4-year laboratory incubation experiment. We found direct microbial regulation of Q10, with a higher Q10 being associated with greater fungal:bacterial ratios. However, no significant direct effects of physicochemical protection and substrate were observed on the variation in Q10 along the latitudinal transect or among different incubation time points. These findings highlight that we should move forward from physicochemical protection and substrate to microbial mechanisms regulating soil carbon decomposition temperature sensitivity to understand and better predict soil carbon-climate feedback.

Nutrient Addition Enhances the Temperature Sensitivity of Soil Carbon Decomposition Across Forest Ecosystems.

Atmospheric nitrogen (N) and phosphorus (P) depositions have been shown to alter nutrient availability in terrestrial ecosystems and thus largely influence soil carbon cycling processes. However, the general pattern of nutrient-induced changes in the temperature response of soil carbon decomposition is unknown. Yet, understanding this pattern is crucial in terms of its effect on soil carbon-climate feedback. Here, we report that N and P additions significantly increase the temperature sensitivity of soil organic carbon decomposition (Q10) by sampling soils from 36 sites across China's forests. We found that N, P, and their co-addition (NP) significantly increased the Q10 by 11.3%, 11.5%, and 23.9%, respectively. The enhancement effect of nutrient addition on Q10 was more evident in soils from warm regions than in those from cold regions. Moreover, we found that nutrient-induced changes in substrate availability and initial substrate and nutrient availability mainly regulated nutrient addition effects. Our findings highlight that N and P deposition enhances the temperature response of soil carbon decomposition, suggesting that N and P deposition should be incorporated into Earth system models to improve the projections of soil carbon feedback to climate change.

The Sunda Region in maritime Southeast Asia: A tropical window into past global carbon-climate feedbacks

The Sunda Region in maritime Southeast Asia: A tropical window into past global carbon-climate feedbacks

Deciphering the Intricate Control of Minerals on Deep Soil Carbon Stability and Persistence in Alaskan Permafrost.

Understanding the fate of organic carbon in thawed permafrost is crucial for predicting climate feedback. While minerals and microbial necromass are known to play crucial roles in the long-term stability of organic carbon in subsoils, their exact influence on carbon persistence in Arctic permafrost remains uncertain. Our study, combining radiocarbon dating and biomarker analyses, showed that soil organic carbon in Alaskan permafrost had millennial-scale radiocarbon ages and contained only 10%-15% microbial necromass carbon, significantly lower than the global average of ~30%-60%. This ancient carbon exhibited a weak correlation with reactive minerals but a stronger correlation with mineral weathering (reactive iron to total iron ratio). Peroxidase activity displayed a high correlation coefficient (p < 10-6) with Δ14C and δ13C, indicating its strong predictive power for carbon persistence. Further, a positive correlation between peroxidase activity and polysaccharides indicates that increased peroxidase activity may promote the protection of plant residues, potentially by fostering the formation of mineral-organic associations. This protective role of mineral surfaces on biopolymers was further supported by examining 1451 synchrotron radiation infrared spectra from soil aggregates, which revealed a strong correlation between mineral OH groups and organic functional groups at the submicron scale. An incubation experiment revealed that increased moisture contents, particularly within the 0%-40% range, significantly elevated peroxidase activity, suggesting that ancient carbon in permafrost soils is vulnerable to moisture-induced destabilization. Collectively, this study offers mechanistic insights into the persistence of carbon in thawed permafrost soils, essential for refining permafrost carbon-climate feedbacks.

Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model

Abstract. Coral reef development is intricately linked to both climate and the concentration of atmospheric CO2, specifically through temperature and carbonate chemistry in the upper ocean. In turn, the calcification of corals modifies the concentration of dissolved inorganic carbon (DIC) and total alkalinity in the ocean, impacting air–sea gas exchange, atmospheric CO2 concentration, and ultimately the climate. This feedback between atmospheric conditions and coral biogeochemistry can only be accounted for with a coupled coral–carbon–climate model. Here we present the implementation of a coral reef calcification module into an Earth system model. Simulated coral reef production of the calcium carbonate mineral aragonite depends on photosynthetically active radiation, nutrient concentrations, salinity, temperature, and the aragonite saturation state. An ensemble of 210 parameter perturbation simulations was performed to identify carbonate production parameter values that optimize the simulated distribution of coral reefs and associated carbonate production. The tuned model simulates the presence of coral reefs and regional-to-global carbonate production values in good agreement with data-based estimates, despite some limitations due to the imperfect simulation of climatic and biogeochemical fields driving the simulation of coral reef development. When used in association with methods accounting for bathymetry changes resulting from different sea levels, the model enables assessment of past and future coral–climate coupling on seasonal to millennial timescales, highlighting how climatic trends and variability may affect reef development and the resulting climate–carbon feedback.

Bacteria-Like Gaiella Accelerate Soil Carbon Loss by Decomposing Organic Matter of Grazing Soils in Alpine Meadows on the Qinghai–Tibet Plateau

The alpine meadows of the Qinghai–Tibet Plateau have significant potential for storing soil carbon, which is important to global carbon sequestration. Grazing is a major threat to its potential for carbon sequestration. However, grazing poses a major threat to this potential by speeding up the breakdown of organic matter in the soil and releasing carbon, which may further lead to positive carbon-climate change feedback and threaten ecological security. Therefore, in order to accurately explore the driving mechanism and regulatory factors of soil organic matter decomposition in grazing alpine meadows on the Qinghai–Tibet Plateau, we took the grazing sample plots of typical alpine meadows as the research object and set up grazing intensities of different life cycles, aiming to explore the relationship and main regulatory factors of grazing on soil organic matter decomposition and soil microorganisms. The results show the following: (1) soil microorganisms, especially Acidobacteria and Acidobacteria, drove the decomposition of organic matter in the soil, thereby accelerating the release of soil carbon, which was not conducive to soil carbon sequestration in grassland; (2) the grazing triggering effect formed a positive feedback with soil microbial carbon release, accelerating the decomposition of organic matter and soil carbon loss; and (3) the grazing ban and light grazing were more conducive to slowing down soil organic matter decomposition and increasing soil carbon sequestration.

Thermal sensitivity of soil microbial carbon use efficiency across forest biomes

Understanding the large-scale pattern of soil microbial carbon use efficiency (CUE) and its temperature sensitivity (CUET) is critical for understanding soil carbon–climate feedback. We used the 18O-H2O tracer method to quantify CUE and CUET along a north-south forest transect. Climate was the primary factor that affected CUE and CUET, predominantly through direct pathways, then by altering soil properties, carbon fractions, microbial structure and functions. Negative CUET (CUE decreases with measuring temperature) in cold forests (mean annual temperature lower than 10 °C) and positive CUET (CUE increases with measuring temperature) in warm forests (mean annual temperature greater than 10 °C) suggest that microbial CUE optimally operates at their adapted temperature. Overall, the plasticity of microbial CUE and its temperature sensitivity alter the feedback of soil carbon to climate warming; that is, a climate-adaptive microbial community has the capacity to reduce carbon loss from soil matrices under corresponding favorable climate conditions.

No constraint on long-term tropical land carbon-climate feedback uncertainties from interannual variability

Unraveling drivers of the interannual variability of tropical land carbon cycle is critical for understanding land carbon-climate feedbacks. Here we utilize two generations of factorial model experiments to show that interannual variability of tropical land carbon uptake under both present and future climate is consistently dominated by terrestrial water availability variations in Earth system models. The magnitude of this interannual sensitivity of tropical land carbon uptake to water availability variations under future climate shows a large spread across the latest 16 models (2.3 ± 1.5 PgC/yr/Tt H2O), which is constrained to 1.3 ± 0.8 PgC/yr/Tt H2O using observations and the emergent constraint methodology. However, the long-term tropical land carbon-climate feedback uncertainties in the latest models can no longer be directly constrained by interannual variability compared with previous models, given that additional important processes are not well reflected in interannual variability but could determine long-term land carbon storage. Our results highlight the limited implication of interannual variability for long-term tropical land carbon-climate feedbacks and help isolate remaining uncertainties with respect to water limitations on tropical land carbon sink in Earth system models.

Snow cover duration delays spring green-up in the northern hemisphere the most for grasslands

Snow is an important factor controlling vegetation functions in high latitudes/altitudes. However, due to the lack of reliable in-situ measurements, the effects of snow on vegetation phenology remains poorly understood. Here, we examine the effects of snow cover duration (SCD) on the start of growing season (SOS) for different vegetation types. SOS and SCD were extracted from in-situ carbon flux and albedo data, respectively, at 51 eddy covariance flux sites in the northern mid-high latitudes. The effects of SCD on SOS vary substantially among different vegetation types. For grassland, preseason SCD outperforms other factors controlling grassland SOS. However, for forests and cropland, the preseason air temperature is the dominant factor in controlling SOS. Preseason SCD mainly influences the SOS by regulating preseason air and soil temperature rather than soil moisture. The CMIP6 Earth system models (ESMs) fail to capture the effect of SCD on SOS. Thus, Random Forest (RF) models were established to predict future SOS changing trends considering the effect of SCD. For grassland and evergreen needleleaf forest, the projected SOS advance rate is slower when SCD is considered. These findings can help us better understand impacts of snow on vegetation phenology and carbon-climate feedbacks in the warming world.

Intrinsic microbial temperature sensitivity and soil organic carbon decomposition in response to climate change.

Soil microbes are essential for regulating carbon stocks under climate change. However, the uncertainty surrounding how microbial temperature responses control carbon losses under warming conditions highlights a significant gap in our climate change models. To address this issue, we conducted a fine-scale analysis of soil organic carbon composition under different temperature gradients and characterized the corresponding microbial growth and physiology across various paddy soils spanning 4000 km in China. Our results showed that warming altered the composition of organic matter, resulting in a reduction in carbohydrates of approximately 0.026% to 0.030% from humid subtropical regions to humid continental regions. These changes were attributed to a decrease in the proportion of cold-preferring bacteria, leading to significant soil carbon losses. Our findings suggest that intrinsic microbial temperature sensitivity plays a crucial role in determining the rate of soil organic carbon decomposition, providing insights into the temperature limitations faced by microbial activities and their impact on soil carbon-climate feedback.

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.

Environmental drivers of increased ecosystem respiration in a warming tundra.

Arctic and alpine tundra ecosystems are large reservoirs of organic carbon1,2. Climate warming may stimulate ecosystem respiration and release carbon into the atmosphere3,4. The magnitude and persistency of this stimulation and the environmental mechanisms that drive its variation remain uncertain5-7. This hampers the accuracy of global land carbon-climate feedback projections7,8. Here we synthesize 136 datasets from 56 open-top chamber in situ warming experiments located at 28 arctic and alpine tundra sites which have been running for less than 1 year up to 25 years. We show that a mean rise of 1.4 °C [confidence interval (CI) 0.9-2.0 °C] in air and 0.4 °C [CI 0.2-0.7 °C] in soil temperature results in an increase in growing season ecosystem respiration by 30% [CI 22-38%] (n = 136). Our findings indicate that the stimulation of ecosystem respiration was due to increases in both plant-related and microbial respiration (n = 9) and continued for at least 25 years (n = 136). The magnitude of the warming effects on respiration was driven by variation in warming-induced changes in local soil conditions, that is, changes in total nitrogen concentration and pH and by context-dependent spatial variation in these conditions, in particular total nitrogen concentration and the carbon:nitrogen ratio. Tundra sites with stronger nitrogen limitations and sites in which warming had stimulated plant and microbial nutrient turnover seemed particularly sensitive in their respiration response to warming. The results highlight the importance of local soil conditions and warming-induced changes therein for future climatic impacts on respiration.

Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)

Abstract. Understanding carbon exchange processes between land reservoirs and the atmosphere is essential for predicting carbon–climate feedbacks. Still, considerable uncertainty remains in the representation of the terrestrial carbon cycle in Earth system models. An emerging strategy to constrain these uncertainties is to include the role of different microbial groups explicitly. Following this approach, we extend the framework of the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with additional mycorrhizal groups and a nitrogen cycle that includes a novel representation of inorganic nitrogen sorption to particles via a Langmuir isotherm. MIMICS+ v1.0 is designed to capture and quantify relationships between soil microorganisms and their environment, with a particular emphasis on boreal ecosystems. We evaluated MIMICS+ against podzolic soil profiles in Norwegian forests as well as the conventional Community Land Model (CLM). MIMICS+ matched observed carbon stocks better than CLM and gave a broader range of C:N ratios, more in line with observations. This is mainly explained by a higher directly plant-derived fraction into the soil organic matter (SOM) pools. The model produces microbial biomass estimates in line with numbers reported in the literature. MIMICS+ also showed better representation of climate gradients than CLM, especially in terms of temperature. To investigate responses to changes in nutrient availability, we performed an N enrichment experiment and found that nitrogen sorbed to particles through the sorption algorithm served as a long-term storage of nutrients for the microbes. Furthermore, although the microbial groups responded considerably to the nitrogen enrichment, we only saw minor responses for carbon storage and respiration. Together, our results present MIMICS+ as an attractive tool for further investigations of interactions between microbial functioning and their (changing) environment.

Microbial evolution-An under-appreciated driver of soil carbon cycling.

Although substantial advances in predicting the ecological impacts of global change have been made, predictions of the evolutionary impacts have lagged behind. In soil ecosystems, microbes act as the primary energetic drivers of carbon cycling; however, microbes are also capable of evolving on timescales comparable to rates of global change. Given the importance of soil ecosystems in global carbon cycling, we assess the potential impact of microbial evolution on carbon-climate feedbacks in this system. We begin by reviewing the current state of knowledge concerning microbial evolution in response to global change and its specific effect on soil carbon dynamics. Through this integration, we synthesize a roadmap detailing how to integrate microbial evolution into ecosystem biogeochemical models. Specifically, we highlight the importance of microscale mechanistic soil carbon models, including choosing an appropriate evolutionary model (e.g., adaptive dynamics, quantitative genetics), validating model predictions with 'omics' and experimental data, scaling microbial adaptations to ecosystem level processes, and validating with ecosystem-scale measurements. The proposed steps will require significant investment of scientific resources and might require 10-20 years to be fully implemented. However, through the application of multi-scale integrated approaches, we will advance the integration of microbial evolution into predictive understanding of ecosystems, providing clarity on its role and impact within the broader context of environmental change.

The potential of urban irrigation for counteracting carbon-climate feedback

Global climate changes, especially the rise of global mean temperature due to the increased carbon dioxide (CO2) concentration, can, in turn, result in higher anthropogenic and biogenic greenhouse gas emissions. This potentially leads to a positive loop of climate–carbon feedback in the Earth’s climate system, which calls for sustainable environmental strategies that can mitigate both heat and carbon emissions, such as urban greening. In this study, we investigate the impact of urban irrigation over green spaces on ambient temperatures and CO2 exchange across major cities in the contiguous United States. Our modeling results indicate that the carbon release from urban ecosystem respiration is reduced by evaporative cooling in humid climate, but promoted in arid/semi-arid regions due to increased soil moisture. The irrigation-induced environmental co-benefit in heat and carbon mitigation is, in general, positively correlated with urban greening fraction and has the potential to help counteract climate–carbon feedback in the built environment.

Microbial mediation of soil carbon loss at the potential climax of alpine grassland under warming

Soil in high latitude and altitude cold regions contains over half of soil organic carbon (SOC) globally, so the decomposition of these SOCs under climate warming could release huge amounts of carbon dioxide to the atmosphere, amplifying climate warming. However, it is still unclear how the SOC storages will change when the ecosystem reaches the final and stable stage (i.e., the climax) under long-term warming. This is mainly because the turnover times of SOC in cold regions exceeds hundreds or even thousands of years, much longer than the periods of simulated warming experiments. Herein we used natural geothermal warming gradients in a Tibetan alpine grassland to determine SOC changes and underlying plant and microbial mechanisms at the potential climax. SOC concentrations were significantly decreased by 21.4%–30.6% under high-level soil warming (+4∼+6 °C), but remained unchanged under low-level soil warming (+2 °C). The losses of SOC were primarily from mineral-associated organic carbon, rather than unprotected particulate organic carbon. The shifts of microbial communities and associated decline of microbial carbon use efficiency, rather than plant-driven carbon fluxes, substantially contributed to the SOC changes. This observed SOC losses at the climax of alpine grassland by high-level warming provide strong empirical support for the positive soil carbon-climate feedback in cold regions, which could not be concluded from short-term experiments or only based on ecosystem carbon fluxes alone. The divergent responses of SOC to different degrees of warming suggest that models must account for these heterogeneous carbon dynamics for projecting future climate warming scenarios.

Multiscale assessment of North American terrestrial carbon balance

Abstract. Comparisons of carbon uptake estimates from bottom-up terrestrial biosphere models (TBMs) to top-down atmospheric inversions help assess how well we understand carbon dioxide (CO2) exchange between the atmosphere and terrestrial biosphere. Previous comparisons have shown varying levels of agreement between bottom-up and top-down approaches, but they have almost exclusively focused on large, aggregated scales (e.g., global or continental), providing limited insights into reasons for the mismatches. Here we explore how consistency, defined as the spread in net ecosystem exchange (NEE) estimates within an ensemble of TBMs or inversions, varies with at finer spatial scales ranging from 1∘×1∘ to the continent of North America. We also evaluate how well consistency informs accuracy in overall NEE estimates by filtering models based on their agreement with the variability, magnitude, and seasonality in observed atmospheric CO2 drawdowns or enhancements. We find that TBMs produce more consistent estimates of NEE for most regions and at most scales relative to inversions. Filtering models using atmospheric CO2 metrics causes ensemble spread to decrease substantially for TBMs, but not for inversions. This suggests that ensemble spread is likely not a reliable measure of the uncertainty associated with the North American carbon balance at any spatial scale. Promisingly, applying atmospheric CO2 metrics leads to a set of models with converging flux estimates across TBMs and inversions. Overall, we show that multiscale assessment of the agreement between bottom-up and top-down NEE estimates, aided by regional-scale observational constraints is a promising path towards identifying fine-scale sources of uncertainty and improving both ensemble consistency and accuracy. These findings help refine our understanding of biospheric carbon balance, particularly at scales relevant for informing regional carbon-climate feedbacks.