Terrestrial Carbon Cycle Variability

Tropical ocean teleconnections with gross primary productivity of monsoon-Asia

The intricate oceanic climate interactions with terrestrial primary production of Asian ecosystems exert crucial social-economical-environmental repercussions. Yet, a holistic understanding of tropical sea surface temperature (SST) anomalies associated with the gross primary productivity (GPP) variations of monsoon-Asia remains constrained. This study provides a statistical framework demonstrating how SST perturbations in the tropics influence GPP fluctuations in monsoon-Asia by modulating hydrothermal conditions of different climate system components. Observation evidence explicitly illustrated the characteristic anomalous SST signatures of positive and negative GPP anomalies in South and Southeast Asia during June-August. The SST anomalies of the central-eastern tropical Pacific showed a robust negative impact on the GPP variability of South-Asia. The GPP alterations in maritime-Southeast-Asia exhibited strong connections with SST anomalies of the western Pacific (positive) and eastern equatorial Pacific (negative). The oceanic signals in the GPP variability of South-Asia and maritime-Southeast-Asia mirrored canonical El Niño and La Niña patterns. The detected SST-GPP link is feasible through large-scale atmospheric circulation variability and the consequent regional modulation of heat and moisture fluxes. The anomalous strengthening (weakening) of Walker cell enhances (reduces) water availability to plants for photosynthesis during the La Niña (El Niño) phase of the ENSO cycle and thus elevates (lowers) GPP in South-Asia and Maritime-southeast-Asia. In contrast, the enhanced GPP anomaly in mainland-Southeast-Asia depicts signs of canonical La Niña and Indian Ocean subtropical dipole (IOSD) teleconnections. The positive impact of IOSD was through the modulation of the Mascarene High and the consequent impact on the monsoon. Meanwhile, decreased GPP bears the imprint of El Niño Modoki and warm tropical Indian Ocean SSTs. The atmospheric teleconnections demonstrated the delayed impact of El Niño Modoki on GPP variability through the Indian Ocean capacitor effect. Our findings could be instrumental in forecasting the probable effects on vegetation growth in monsoon-Asia associated with high-frequency tropical oceanic changes.

Vegetation clumping modulates global photosynthesis through adjusting canopy light environment

The spatial dispersion of photoelements within a vegetation canopy, quantified by the clumping index (CI), directly regulates the within-canopy light environment and photosynthesis rate, but is not commonly implemented in terrestrial biosphere models to estimate the ecosystem carbon cycle. A few global CI products have been developed recently with remote sensing measurements, making it possible to examine the global impacts of CI. This study deployed CI in the radiative transfer scheme of the Community Land Model version 5 (CLM5) and used the revised CLM5 to quantitatively evaluate the extent to which CI can affect canopy absorbed radiation and gross primary production (GPP), and for the first time, considering the uncertainty and seasonal variation of CI with multiple remote sensing products. Compared to the results without considering the CI impact, the revised CLM5 estimated that sunlit canopy absorbed up to 9%-15% and 23%-34% less direct and diffuse radiation, respectively, while shaded canopy absorbed 3%-18% more diffuse radiation across different biome types. The CI impacts on canopy light conditions included changes in canopy light absorption, and sunlit-shaded leaf area fraction related to nitrogen distribution and thus the maximum rate of Rubisco carboxylase activity (V_cmax ), which together decreased photosynthesis in sunlit canopy by 5.9-7.2 PgC year^-1 while enhanced photosynthesis by 6.9-8.2 PgC year^-1 in shaded canopy. With higher light use efficiency of shaded leaves, shaded canopy increased photosynthesis compensated and exceeded the lost photosynthesis in sunlit canopy, resulting in 1.0 ± 0.12 PgC year^-1 net increase in GPP. The uncertainty of GPP due to the different input CI datasets was much larger than that caused by CI seasonal variations, and was up to 50% of the magnitude of GPP interannual variations in the tropical regions. This study highlights the necessity of considering the impacts of CI and its uncertainty in terrestrial biosphere models.

A data-driven approach for discovering the most probable transition pathway for a stochastic carbon cycle system

Many natural systems exhibit tipping points where changing environmental conditions spark a sudden shift to a new and sometimes quite different state. Global climate change is often associated with the stability of marine carbon stocks. We consider a stochastic carbonate system of the upper ocean to capture such transition phenomena. Based on the Onsager-Machlup action functional theory, we calculate the most probable transition pathway between the metastable and oscillatory states via a neural shooting method. Furthermore, we explore the effects of external random carbon input rates on the most probable transition pathway, which provides a basis to recognize naturally occurring tipping points. Particularly, we investigate the transition pathway's dependence on the transition time and further compute the optimal transition time using a physics-informed neural network, toward the maximum carbonate concentration state in the oscillatory regimes. This work may offer some insights into the effects of noise-affected carbon input rates on transition phenomena in stochastic models.

Adaptation to climate change in agricultural sector: A proposal for rational management measures

Agriculture, as one of the most important branches of economy, depends on climate conditions and has a significant contribution to climatic changes process, primarily by releasing greenhouse gases (GHG). It is estimated that agriculture directly emits about 9% of the total amount of GHG, of which 5% originates from soil and about 4% from livestock production (ruminants). Emissions of carbon dioxide into the atmosphere from cultivated soil are 27% to 90% higher compared to natural grasslands. For greater climate neutrality of agriculture, two-way action is necessary: towards the reduction of GHG and towards the sequestration of carbon in the soil. Recommended measures and practices in the management of organic carbon content in soil include a wide range of agronomic, biological, technical and technological procedures, management and structural practices on agricultural soil. By encouraging organic plant production, which should contribute to maintaining and increasing the natural fertility of the soil, as well as preserving and improving biodiversity and stabilizing the structure of the soil, it can contribute to mitigating climate change.

Biases in open-path carbon dioxide flux measurements: Roles of instrument surface heat exchange and analyzer temperature sensitivity

Eddy covariance (EC) measurements of ecosystem-atmosphere carbon dioxide (CO₂) exchange provide the most direct assessment of the terrestrial carbon cycle. Measurement biases for open-path (OP) CO₂ concentration and flux measurements have been reported for over 30 years, but their origin and appropriate correction approach remain unresolved. Here, we quantify the impacts of OP biases on carbon and radiative forcing budgets for a sub-boreal wetland. Comparison with a reference closed-path (CP) system indicates that a systematic OP flux bias (0.54 μmol m^-2 s^-1) persists for all seasons leading to a 110% overestimate of the ecosystem CO₂ sink (cumulative error of 78 gC m^-2). Two potential OP bias sources are considered: Sensor-path heat exchange (SPHE) and analyzer temperature sensitivity. We examined potential OP correction approaches including: i) Fast temperature measurements within the measurement path and sensor surfaces; ii) Previously published parameterizations; and iii) Optimization algorithms. The measurements revealed year-round average temperature and heat flux gradients of 2.9 °C and 16 W m^-2 between the bottom sensor surfaces and atmosphere, indicating SPHE-induced OP bias. However, measured SPHE correlated poorly with the observed differences between OP and CP CO₂ fluxes. While previously proposed nominally universal corrections for SPHE reduced the cumulative OP bias, they led to either systematic under-correction (by 38.1 gC m^-2) or to systematic over-correction (by 17-37 gC m^-2). The resulting budget errors exceeded CP random uncertainty and change the sign of the overall carbon and radiative forcing budgets. Analysis of OP calibration residuals as a function of temperature revealed a sensitivity of 5 μmol m^-3 K^-1. This temperature sensitivity causes CO₂ calibration errors proportional to sample air fluctuations that can offset the observed growing season flux bias by 50%. Consequently, we call for a new OP correction framework that characterizes SPHE- and temperature-induced CO₂ measurement errors.

Plant-based CO2 drawdown and storage as SiC

This study demonstrates how integration of plants into an artificial carbon cycle is capable of harmoniously operating with Earth's natural cycles as one means to recycle atmospheric CO₂ for economically lucrative green materials.

Assessment of Human-Related Driving Forces for Reduced Carbon Uptake Using Neighborhood Analysis and Geographically Weighted Regression: A Case Study in the Grassland of Inner Mongolia, China

The ever-rising concentration of atmospheric carbon is viewed as the primary cause for global warming. To discontinue this trend, it is of urgent importance to either cut down human carbon emissions or remove more carbon from the atmosphere. Grassland ecosystems occupy the largest part of the global land area but maintain a relatively low carbon sequestration flux. While numerous studies have confirmed the impacts on grassland vegetation growth from climate changes and human activities, little work has been done to understand the driving forces for a reduced carbon uptake (RCU)—a loss in vegetation carbon sequestration because of inappropriate grassland management. This work focused on assessing RCU in the grassland of Inner Mongolia and understanding the influential patterns of the selected variables (including grazing intensity, road network, population, and vegetation productivity) related to RCU. Neighborhood analysis was proposed to locate optimized grassland management practices from historical data and to map RCU. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were applied to explore the driving forces for RCU. The results indicated that the human-related factors, including stock grazing intensity, population density, and road network were likely to present a spatially varied impact on RCU, which accounted for more than 1/4 of the total carbon sequestration.

An optimality-based model explains seasonal variation in C3 plant photosynthetic capacity

The maximum rate of carboxylation (V_cmax ) is an essential leaf trait determining the photosynthetic capacity of plants. Existing approaches for estimating V_cmax at large scale mainly rely on empirical relationships with proxies such as leaf nitrogen/chlorophyll content or hyperspectral reflectance, or on complicated inverse models from gross primary production or solar-induced fluorescence. A novel mechanistic approach based on the assumption that plants optimize resource investment coordinating with environment and growth has been shown to accurately predict C3 plant V_cmax based on mean growing season environmental conditions. However, the ability of optimality theory to explain seasonal variation in V_cmax has not been fully investigated. Here, we adapt an optimality-based model to simulate daily V_cmax,25C (V_cmax at a standardized temperature of 25°C) by incorporating the effects of antecedent environment, which affects current plant functioning, and dynamic light absorption, which coordinates with plant functioning. We then use seasonal V_cmax,25C field measurements from 10 sites across diverse ecosystems to evaluate model performance. Overall, the model explains about 83% of the seasonal variation in C3 plant V_cmax,25C across the 10 sites, with a medium root mean square error of 12.3 μmol m^-2  s^-1 , which suggests that seasonal changes in V_cmax,25C are consistent with optimal plant function. We show that failing to account for acclimation to antecedent environment or coordination with dynamic light absorption dramatically decreases estimation accuracy. Our results show that optimality-based approach can accurately reproduce seasonal variation in canopy photosynthetic potential, and suggest that incorporating such theory into next-generation trait-based terrestrial biosphere models would improve predictions of global photosynthesis.

Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East-West Divide of Temperate North America

Across temperate North America, interannual variability (IAV) in gross primary production (GPP) and net ecosystem exchange (NEE) and their relationship with environmental drivers are poorly understood. Here, we examine IAV in GPP and NEE and their relationship to environmental drivers using two state-of-the-science flux products: NEE constrained by surface and space-based atmospheric CO2 measurements over 2010-2015 and satellite up-scaled GPP from FluxSat over 2001-2017. We show that the arid western half of temperate North America provides a larger contribution to IAV in GPP (104% of east) and NEE (127% of east) than the eastern half, in spite of smaller magnitude of annual mean GPP and NEE. This occurs because anomalies in western ecosystems are temporally coherent across the growing season leading to an amplification of GPP and NEE. In contrast, IAV in GPP and NEE in eastern ecosystems is dominated by seasonal compensation effects, associated with opposite responses to temperature anomalies in spring and summer. Terrestrial biosphere models in the MsTMIP ensemble generally capture these differences between eastern and western temperate North America, although there is considerable spread between models.

Higher than expected CO2 fertilization inferred from leaf to global observations

Several lines of evidence point to an increase in the activity of the terrestrial biosphere over recent decades, impacting the global net land carbon sink (NLS) and its control on the growth of atmospheric carbon dioxide (ca ). Global terrestrial gross primary production (GPP)-the rate of carbon fixation by photosynthesis-is estimated to have risen by (31 ± 5)% since 1900, but the relative contributions of different putative drivers to this increase are not well known. Here we identify the rising atmospheric CO2 concentration as the dominant driver. We reconcile leaf-level and global atmospheric constraints on trends in modeled biospheric activity to reveal a global CO2 fertilization effect on photosynthesis of 30% since 1900, or 47% for a doubling of ca above the pre-industrial level. Our historic value is nearly twice as high as current estimates (17 ± 4)% that do not use the full range of available constraints. Consequently, under a future low-emission scenario, we project a land carbon sink (174 PgC, 2006-2099) that is 57 PgC larger than if a lower CO2 fertilization effect comparable with current estimates is assumed. These findings suggest a larger beneficial role of the land carbon sink in modulating future excess anthropogenic CO2 consistent with the target of the Paris Agreement to stay below 2°C warming, and underscore the importance of preserving terrestrial carbon sinks.

Interannual variation of terrestrial carbon cycle: Issues and perspectives

With accumulation of carbon cycle observations and model developments over the past decades, exploring interannual variation (IAV) of terrestrial carbon cycle offers the opportunity to better understand climate-carbon cycle relationships. However, despite growing research interest, uncertainties remain on some fundamental issues, such as the contributions of different regions, constituent fluxes and climatic factors to carbon cycle IAV. Here we overviewed the literature on carbon cycle IAV about current understanding of these issues. Observations and models of the carbon cycle unanimously show the dominance of tropical land ecosystems to the signal of global carbon cycle IAV, where tropical semiarid ecosystems contribute as much as the combination of all other tropical ecosystems. Vegetation photosynthesis contributes more than ecosystem respiration to IAV of the global net land carbon flux, but large uncertainties remain on the contribution of fires and other disturbance fluxes. Climatic variations are the major drivers to the IAV of net land carbon flux. Although debate remains on whether the dominant driver is temperature or moisture variability, their interaction,that is, the dependence of carbon cycle sensitivity to temperature on moisture conditions, is emerging as key regulators of the carbon cycle IAV. On timescales from the interannual to the centennial, global carbon cycle variability will be increasingly contributed by northern land ecosystems and oceans. Therefore, both improving Earth system models (ESMs) with the progressive understanding on the fast processes manifested at interannual timescale and expanding carbon cycle observations at broader spatial and longer temporal scales are critical to better prediction on evolution of the carbon-climate system.

Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange

Terrestrial ecosystems contribute most of the interannual variability (IAV) in atmospheric carbon dioxide (CO₂ ) concentrations, but processes driving the IAV of net ecosystem CO₂ exchange (NEE) remain elusive. For a predictive understanding of the global C cycle, it is imperative to identify indicators associated with ecological processes that determine the IAV of NEE. Here, we decompose the annual NEE of global terrestrial ecosystems into their phenological and physiological components, namely maximum carbon uptake (MCU) and release (MCR), the carbon uptake period (CUP), and two parameters, α and β, that describe the ratio between actual versus hypothetical maximum C sink and source, respectively. Using long-term observed NEE from 66 eddy covariance sites and global products derived from FLUXNET observations, we found that the IAV of NEE is determined predominately by MCU at the global scale, which explains 48% of the IAV of NEE on average while α, CUP, β, and MCR explain 14%, 25%, 2%, and 8%, respectively. These patterns differ in water-limited ecosystems versus temperature- and radiation-limited ecosystems; 31% of the IAV of NEE is determined by the IAV of CUP in water-limited ecosystems, and 60% of the IAV of NEE is determined by the IAV of MCU in temperature- and radiation-limited ecosystems. The Lund-Potsdam-Jena (LPJ) model and the Multi-scale Synthesis and Terrestrial Model Inter-comparison Project (MsTMIP) models underestimate the contribution of MCU to the IAV of NEE by about 18% on average, and overestimate the contribution of CUP by about 25%. This study provides a new perspective on the proximate causes of the IAV of NEE, which suggest that capturing the variability of MCU is critical for modeling the IAV of NEE across most of the global land surface.

Improved estimates of global terrestrial photosynthesis using information on leaf chlorophyll content

The terrestrial biosphere plays a critical role in mitigating climate change by absorbing anthropogenic CO₂ emissions through photosynthesis. The rate of photosynthesis is determined jointly by environmental variables and the intrinsic photosynthetic capacity of plants (i.e. maximum carboxylation rate; Vcmax25 ). A lack of an effective means to derive spatially and temporally explicit Vcmax25 has long hampered efforts towards estimating global photosynthesis accurately. Recent work suggests that leaf chlorophyll content (Chl_leaf ) is strongly related to Vcmax25 , since Chl_leaf and Vcmax25 are both correlated with photosynthetic nitrogen content. We used medium resolution satellite images to derive spatially and temporally explicit Chl_leaf , which we then used to parameterize Vcmax25 within a terrestrial biosphere model. Modelled photosynthesis estimates were evaluated against measured photosynthesis at 124 eddy covariance sites. The inclusion of Chl_leaf in a terrestrial biosphere model improved the spatial and temporal variability of photosynthesis estimates, reducing biases at eddy covariance sites by 8% on average, with the largest improvements occurring for croplands (21% bias reduction) and deciduous forests (15% bias reduction). At the global scale, the inclusion of Chl_leaf reduced terrestrial photosynthesis estimates by 9 PgC/year and improved the correlations with a reconstructed solar-induced fluorescence product and a gridded photosynthesis product upscaled from tower measurements. We found positive impacts of Chl_leaf on modelled photosynthesis for deciduous forests, croplands, grasslands, savannas and wetlands, but mixed impacts for shrublands and evergreen broadleaf forests and negative impacts for evergreen needleleaf forests and mixed forests. Our results highlight the potential of Chl_leaf to reduce the uncertainty of global photosynthesis but identify challenges for incorporating Chl_leaf in future terrestrial biosphere models.

A high-throughput analytical tool for quantification of 15 metallic nanoparticles supported on carbon black

Metallic nanoparticles (NPs) have been widely used in different areas of science. Usually, they are immobilized on a low-cost support for catalysis purposes. However, there is a lack of studies for specific methods for analytical quantification since the extraction of these metallic NPs from the matrix is still a challenge. In this work, 15 metallic NPs were synthesized (Pt, Pd, Au, Ag, Rh, Ru, Nb, Mn, Co, Cu, Zr, Sn, Ce, Ni and W) supported on a commercial carbon black (Vulcan XC72). Then, six different methods were employed for sample preparation and further determination by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The results can be divided in three groups concerning the extraction of metallic NPs: the first group could be extracted from the matrix with nitric acid, for the second one it was necessary to employ a digestion at 25 °C (room temperature), and finally a third group which was found to be independent of acid and temperature. These findings can contribute to future research in the field of catalysis to improve their characterization regarding the metallic NPs.

Have Synergies Between Nitrogen Deposition and Atmospheric CO2 Driven the Recent Enhancement of the Terrestrial Carbon Sink?

The terrestrial carbon sink has increased since the turn of this century at a time of increased fossil fuel burning, yet the mechanisms enhancing this sink are not fully understood. Here we assess the hypothesis that regional increases in nitrogen deposition since the early 2000s has alleviated nitrogen limitation and worked in tandem with enhanced CO2 fertilization to increase ecosystem productivity and carbon sequestration, providing a causal link between the parallel increases in emissions and the global land carbon sink. We use the Community Land Model (CLM4.5-BGC) to estimate the influence of changes in atmospheric CO2, nitrogen deposition, climate, and their interactions to changes in net primary production and net biome production. We focus on two periods, 1901-2016 and 1990-2016, to estimate changes in land carbon fluxes relative to historical and contemporary baselines, respectively. We find that over the historical period, nitrogen deposition (14%) and carbon-nitrogen synergy (14%) were significant contributors to the current terrestrial carbon sink, suggesting that long-term increases in nitrogen deposition led to a substantial increase in CO2 fertilization. However, relative to the contemporary baseline, changes in nitrogen deposition and carbon-nitrogen synergy had no substantial contribution to the 21st century increase in global carbon uptake. Nonetheless, we find that increased nitrogen deposition in East Asia since the early 1990s contributed 50% to the overall increase in net biome production over this region, highlighting the importance of carbon-nitrogen interactions. Therefore, potential large-scale changes in nitrogen deposition could have a significant impact on terrestrial carbon cycling and future climate.

Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production

Carbon uptake by terrestrial ecosystems is increasing along with the rising of atmospheric CO₂ concentration. Embedded in this trend, recent studies suggested that the interannual variability (IAV) of global carbon fluxes may be dominated by semi-arid ecosystems, but the underlying mechanisms of this high variability in these specific regions are not well known. Here we derive an ensemble of gross primary production (GPP) estimates using the average of three data-driven models and eleven process-based models. These models are weighted by their spatial representativeness of the satellite-based solar-induced chlorophyll fluorescence (SIF). We then use this weighted GPP ensemble to investigate the GPP variability for different aridity regimes. We show that semi-arid regions contribute to 57% of the detrended IAV of global GPP. Moreover, in regions with higher GPP variability, GPP fluctuations are mostly controlled by precipitation and strongly coupled with evapotranspiration (ET). This higher GPP IAV in semi-arid regions is co-limited by supply (precipitation)-induced ET variability and GPP-ET coupling strength. Our results demonstrate the importance of semi-arid regions to the global terrestrial carbon cycle and posit that there will be larger GPP and ET variations in the future with changes in precipitation patterns and dryland expansion.