Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends

Modelling changes in vegetation productivity and carbon balance under future climate scenarios in southeastern Australia

Australia, characterized by extensive and heterogeneous terrestrial ecosystems, plays a critical role in the global carbon cycle and in efforts to mitigate climate change. Prior research has quantified vegetation productivity and carbon balance within the Australian context over preceding decades. Nonetheless, the responses of vegetation and carbon dynamics to the evolving phenomena of climate change and escalating concentrations of atmospheric carbon dioxide remain ambiguous within the Australian landscape. Here, we used LPJ-GUESS model to assess the impacts of climate change on Gross Primary Productivity (GPP) and Net Biome Productivity (NBP) of carbon for the state of New South Wales (NSW) in southeastern Australia. LPJ-GUESS simulations were driven by an ensemble of 27 global climate models under different emission scenarios. We investigated the change of GPP for different vegetation types and whether NSW ecosystems will be a net sink or source of carbon under climate change. We found that LPJ-GUESS successfully simulated GPP for the period 2003-2021, demonstrating a comparative performance with GPP derived from upscaled eddy covariance fluxes (R2 = 0.58, nRMSE = 14.2 %). The simulated NBP showed a larger interannual variation compared with flux data and other inversion products but could capture the timing of rainfall-driven carbon sink and source variations in 2015-2020. GPP would increase by 10.3-19.5 % under a medium emission scenario and 19.7-46.8 % under a high emission scenario. The mean probability of NSW acting as a carbon sink in the future showed a small decrease with a large uncertainty with >8 of the 27 climate models indicating an increased potential for carbon sink. These findings emphasize the significance of emission scenarios in shaping future carbon dynamics but also highlight considerable uncertainties stemming from different climate projections. Our study represents a baseline for understanding natural ecosystem dynamics and their key role in governing land carbon uptake and storage in Australia.

Projected decline in the strength of vegetation carbon sequestration under climate change in India

Tropical vegetation plays a critical role in terrestrial carbon budget and supply many ecological functions such as carbon sequestration. In recent decades, India has witnessed an increase in net primary productivity (NPP), an important measure of carbon sequestration. However, uncertainties persist regarding the sustainability of these land carbon sinks in the face of climate change. The enhanced NPP is driven by the strong CO2 fertilization effect (CFE), but the temporal patterns of this feedback remain unclear. Using the carbon flux data from the Earth System Models (ESMs), an increasing trend in NPP was observed, with projections of NPP to 2.00 ± 0.12 PgCyr-1 (25 % increase) during 2021-2049, 2.36 ± 0.12 PgCyr-1 (18 % increase) during 2050-2079, and 2.67 ± 0.07 PgCyr-1 (13 % increase) during 2080-2099 in Indian vegetation under SSP585 scenario. This suggests a significant decline in the NPP growth rate. To understand the feedback mechanisms driving NPP, the relative effects of CFE and warming were analyzed. Comparing simulations from the biogeochemically coupled model (BGC) with the fully coupled model, the BGC model projected a 74.7 % increase in NPP, significantly higher than the 55.9 % increase projected by the fully coupled model by the end of the century. This indicates that the consistent increase in NPP was associated with CO2 fertilization. More importantly, results reveal that the decrease in the NPP growth rate was due to the declining contribution of CFE at a rate of -0.62 % per 100 ppm CO2 increase. This decline could be attributed to factors such as nutrient limitations and high temperatures. Additionally, significant shifts in the strength of carbon sinks in offsetting the CO2 emissions were identified, decreasing at a rate of -1.15 % per decade. This decline in the strength of vegetation carbon sequestration may increase the societal dependence on mitigation measures to address climate change.

Carbon cycle responses to climate change across China's terrestrial ecosystem: Sensitivity and driving process

Investigations into the carbon cycle and how it responds to climate change at the national scale are important for a comprehensive understanding of terrestrial carbon cycle and global change issues. Contributions of carbon fluxes to the terrestrial sink and the effects on climate change are still not fully understood. In this study, we aimed to explore the relationship between ecosystem production (GPP/SIF/NDVI) and net ecosystem carbon exchange (NEE) and to investigate the sensitivity of carbon fluxes to climate change at different spatio-temporal scales. Furthermore, we sought to delve into the carbon cycle processes driven by climate stress in China since the beginning of the 21st century. To achieve these objectives, we employed correlation and sensitivity analysis techniques, utilizing a wide range of data sources including ground-based observations, remote sensing observations, atmospheric inversions, machine learning, and model simulations. Our findings indicate that NEE in most arid regions of China is primarily driven by ecosystem production. Climate variations have a greater influence on ecosystem production than respiration. Warming has negatively impacted ecosystem production in Northeast China, as well as in subtropical and tropical regions. Conversely, increased precipitation has strengthened the terrestrial carbon sink, particularly in the northern cool and dry areas. We also found that ecosystem respiration exhibits heightened sensitivity to warming in southern China. Moreover, our analysis revealed that the control of terrestrial carbon cycle by ecosystem production gradually weakens from cold/arid areas to warm/humid areas. We identified distinct temperature thresholds (ranging from 10.5 to 13.7 °C) and precipitation thresholds (approximately 1400 mm yr-1) for the transition from production-dominated to respiration-dominated processes. Our study provides valuable insights into the complex relationship between climate change and carbon cycle in China.

The interacting effect of climate change and herbivory can trigger large-scale transformations of European temperate forests

In many regions of Europe, large wild herbivores alter forest community composition through their foraging preferences, hinder the forest's natural adaptive responses to climate change, and reduce ecosystem resilience. We investigated a widespread European forest type, a mixed forest dominated by Picea abies, which has recently experienced an unprecedented level of disturbance across the continent. Using the forest landscape model iLand, we investigated the combined effect of climate change and herbivory on forest structure, composition, and carbon and identified conditions leading to ecosystem transitions on a 300-year timescale. Eight climate change scenarios, driven by Representative Concentration Pathways 4.5 and 8.5, combined with three levels of regeneration browsing, were tested. We found that the persistence of the current level of browsing pressure impedes adaptive changes in community composition and sustains the presence of the vulnerable yet less palatable P. abies. These development trajectories were tortuous, characterized by a high disturbance intensity. On the contrary, reduced herbivory initiated a transformation towards the naturally dominant broadleaved species that was associated with an increased forest carbon and a considerably reduced disturbance. The conditions of RCP4.5 combined with high and moderate browsing levels preserved the forest within its reference range of variability, defining the actual boundaries of resilience. The remaining combinations of browsing and climate change led to ecosystem transitions. Under RCP4.5 with browsing effects excluded, the new equilibrium conditions were achieved within 120 years, whereas the stabilization was delayed by 50-100 years under RCP8.5 with higher browsing intensities. We conclude that forests dominated by P. abies are prone to transitions driven by climate change. However, reducing herbivory can set the forest on a stable and predictable trajectory, whereas sustaining the current browsing levels can lead to heightened disturbance activity, extended transition times, and high variability in the target conditions.

Stronger increases but greater variability in global mangrove productivity compared to that of adjacent terrestrial forests

Mangrove forests are a highly productive ecosystem with important potential to offset anthropogenic greenhouse gas emissions. Mangroves are expected to respond differently to climate change compared to terrestrial forests owing to their location in the tidal environment and unique ecophysiological characteristics, but the magnitude of difference remains uncertain at the global scale. Here we use satellite observations to examine mean trends and interannual variability in the productivity of global mangrove forests and nearby terrestrial evergreen broadleaf forests from 2001 to 2020. Although both types of ecosystem experienced significant recent increases in productivity, mangroves exhibited a stronger increasing trend and greater interannual variability in productivity than evergreen broadleaf forests on three-quarters of their co-occurring coasts. The difference in productivity trends is attributed to the stronger CO2 fertilization effect on mangrove photosynthesis, while the discrepancy in interannual variability is attributed to the higher sensitivities to variations in precipitation and sea level. Our results indicate that mangroves will have a faster increase in productivity than terrestrial forests in a CO2-rich future but may suffer more from deficits in water availability, highlighting a key difference between terrestrial and tidal ecosystems in their responses to climate change.

Elevated CO2 and nitrogen addition enhance the symbiosis and functions of rhizosphere microorganisms under cadmium exposure

Soil microbes are fundamental to ecosystem health and productivity. How soil microbial communities are influenced by elevated atmospheric carbon dioxide (eCO2) concentration and nitrogen (N) deposition under heavy metal pollution remains uncertain, despite global exposure of terrestrial ecosystems to eCO2, high N deposition and heavy metal stress. Here, we conducted a four year's open-top chamber experiment to assess the effects of soil cadmium (Cd) treatment (10 kg hm-2 year-1) alone and combined treatments of Cd with eCO2 concentration (700 ppm) and/or N addition (100 kg hm-2 year-1) on tree growth and rhizosphere microbial community. Relative to Cd treatment alone, eCO2 concentration in Cd contaminated soil increased the complexity of microbial networks, including the number links, average degree and positive/negative ratios. The combined effect of eCO2 and N addition in Cd contaminated soil not only increased the complexity of microbial networks, but also enhanced the abundance of microbial urealysis related UreC and nitrifying related amoA1 and amoA2, and the richness of arbuscular mycorrhiza fungi (AMF), thereby improving the symbiotic functions between microorganisms and plants. Results from correlation analysis and structural equation model (SEM) further demonstrated that eCO2 concentration and N addition acted on functions and networks differently. Elevated CO2 positively regulated microbial networks and functions through phosphorus (P) and Cd concentration in roots, while N addition affected microbial functions through soil available N and soil organic carbon (SOC) concentration and microbial network through soil Cd concentration. Overall, our findings highlight that eCO2 concentration and N addition make microbial communities towards ecosystem health that may mitigate Cd stress, and provide new insights into the microbiology supporting phytoremediation for Cd contaminated sites in current and future global change scenarios.

Exploring carbon sequestration in broad-leaved Korean pine forests: Insights into photosynthetic and respiratory processes

A comprehensive understanding of carbon assimilation and sequestration in broad-leaved Korean pine forests is crucial for accurately estimating this significant aspect of temperate forests at a regional scale. In this study, we introduced a high-temporal resolution model designed for carbon assimilation insights at the plot scale, focusing on specific parameters such as leaf area dynamics, vertical leaf distribution, photosynthetically active radiation (PAR) fluctuations, and the photosynthetic traits of tree species. The findings reveal that most tree species in broad-leaved Korean pine forests exhibit an inverted U-shaped pattern in leaf area dynamics, with shorter leaf drop periods than leaf expansion events. Leaf distribution varies significantly among different canopy heights, with approximately 80 % of the leaves above 15 m. PAR decreases as canopy height decreases, with PAR at 25 m accounting for about 60 % of the PAR above the canopy. Our framework incorporates a leaf-scale light-response curve and empirical photosynthesis-temperature relationships to estimate forest carbon assimilation on daily and hourly scales accurately. Using the model, we assess the gross primary productivity (GPP), leaf net photosynthetic assimilation (LNPA), and carbon increment (ΔC) of broad-leaved Korean pine forests from 2017 to 2020. The results demonstrate GPP, LNPA, and ΔC values of 21.4 t·ha-1·a-1, 17.4 t·ha-1·a-1, and 4.0 t·ha-1·a-1, respectively. Regarding efficiency, GPP, LNPA, and ΔC per square meter of leaf per year are 179 g, 146 g, and 33 g, respectively. Notably, tree species in the canopy layer of the forest exhibit significantly higher efficiency than those in the understory layer. This research significantly contributes to our understanding of carbon cycling and the responses of forest ecosystems to climate change. Moreover, it provides a practical tool for forest management and the development of carbon sequestration strategies.

Satellite-observed increasing coupling between vegetation productivity and greenness in the semiarid Loess Plateau of China is not captured by process-based models

Global vegetation has experienced notable changes in greenness and productivity since the early 1980s. However, the changes in the relationship between productivity and greenness, i.e., the coupling, and its underlying mechanisms, are poorly understood. The Loess Plateau (LP) is one of China's most significant areas for vegetation greening. Yet, it remains poorly documented what changes in the coupling between productivity and greenness are and how environmental and anthropogenic factors affect this coupling in the LP over the past four decades. We investigated the interannual trend of coupling between Gross Primary Productivity (GPP) and Leaf Area Index (LAI), i.e., the GPP-LAI coupling, and its response to climate factors and afforestation in the LP using long-term remote-sensed LAI, GPP and Solar-induced Chlorophyll Fluorescence (SIF). We found a monotonically increasing trend in the GPP-LAI coupling in the LP from 1982 to 2018 (0.0043 yr-1, p < 0.05), in which the significant trend in the northwest LP was driven by increasing soil water and landcover change, e.g., increased grassland and afforestation. An ensemble of 11 state-of-the-art ecosystem models from the TRENDY project failed to capture the observed monotonically increasing trend of the GPP-LAI coupling in the LP. The consistent projection of a decreasing GPP-LAI coupling in LP during 2019-2100 by 22 Earth System Models (ESMs) under various future scenarios should be treated with caution due to the identified inherent uncertainties in the ecosystem component in ESMs and the notable biases in the simulation of future climate conditions. Our study highlights the need to enhance the key mechanisms that regulate the coupling relationships between photosynthesis and canopy structure in indigenized ecosystem models to accurately estimate the ecosystem change in drylands under global climate change.

Increased photosynthesis during spring drought in energy-limited ecosystems

Drought is often thought to reduce ecosystem photosynthesis. However, theory suggests there is potential for increased photosynthesis during meteorological drought, especially in energy-limited ecosystems. Here, we examine the response of photosynthesis (gross primary productivity, GPP) to meteorological drought across the water-energy limitation spectrum. We find a consistent increase in eddy covariance GPP during spring drought in energy-limited ecosystems (83% of the energy-limited sites). Half of spring GPP sensitivity to precipitation was predicted solely from the wetness index (R2 = 0.47, p < 0.001), with weaker relationships in summer and fall. Our results suggest GPP increases during spring drought for 55% of vegetated Northern Hemisphere lands ( >30° N). We then compare these results to terrestrial biosphere model outputs and remote sensing products. In contrast to trends detected in eddy covariance data, model mean GPP always declined under spring precipitation deficits after controlling for air temperature and light availability. While remote sensing products captured the observed negative spring GPP sensitivity in energy-limited ecosystems, terrestrial biosphere models proved insufficiently sensitive to spring precipitation deficits.

Benefits and trade-offs of optimizing global land use for food, water, and carbon

Current large-scale patterns of land use reflect history, local traditions, and production costs, much more so than they reflect biophysical potential or global supply and demand for food and freshwater, or-more recently-climate change mitigation. We quantified alternative land-use allocations that consider trade-offs for these demands by combining a dynamic vegetation model and an optimization algorithm to determine Pareto-optimal land-use allocations under changing climate conditions in 2090-2099 and alternatively in 2033-2042. These form the outer bounds of the option space for global land-use transformation. Results show a potential to increase all three indicators (+83% in crop production, +8% in available runoff, and +3% in carbon storage globally) compared to the current land-use configuration, with clear land-use priority areas: Tropical and boreal forests were preserved, crops were produced in temperate regions, and pastures were preferentially allocated in semiarid grasslands and savannas. Transformations toward optimal land-use patterns would imply extensive reconfigurations and changes in land management, but the required annual land-use changes were nevertheless of similar magnitude as those suggested by established land-use change scenarios. The optimization results clearly show that large benefits could be achieved when land use is reconsidered under a "global supply" perspective with a regional focus that differs across the world's regions in order to achieve the supply of key ecosystem services under the emerging global pressures.

Increasing riverine export of dissolved organic carbon from China

River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere-based and land-based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in-situ measurements and applied a random forest model, to quantify riverine DOC fluxes (FDOC ) and DOC concentrations (CDOC ) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine CDOC and FDOC , as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual-scale estimates and large rivers. Results show that over the period 2001-2015, the average CDOC was 2.25 ± 0.45 mg/L and average FDOC was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in FDOC (+0.044 Tg/year2 , p = .01), but little change in CDOC (-0.001 mg/L/year, p > .10). Although the trend in CDOC is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p < .05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (-0.043 and -0.014 mg/L/year, p = .01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio-temporal variability of FDOC and CDOC across China. However, and in contrast with other basins, the significant increase in CDOC in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving FDOC , the increase in FDOC is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate.

CO2 fertilization contributed more than half of the observed forest biomass increase in northern extra-tropical land

The existence of a large-biomass carbon (C) sink in Northern Hemisphere extra-tropical ecosystems (NHee) is well-established, but the relative contribution of different potential drivers remains highly uncertain. Here we isolated the historical role of carbon dioxide (CO2 ) fertilization by integrating estimates from 24 CO2 -enrichment experiments, an ensemble of 10 dynamic global vegetation models (DGVMs) and two observation-based biomass datasets. Application of the emergent constraint technique revealed that DGVMs underestimated the historical response of plant biomass to increasing [CO2 ] in forests (β Forest Mod ) but overestimated the response in grasslands (β Grass Mod ) since the 1850s. Combining the constrainedβ Forest Mod (0.86 ± 0.28 kg C m-2  [100 ppm]-1 ) with observed forest biomass changes derived from inventories and satellites, we identified that CO2 fertilization alone accounted for more than half (54 ± 18% and 64 ± 21%, respectively) of the increase in biomass C storage since the 1990s. Our results indicate that CO2 fertilization dominated the forest biomass C sink over the past decades, and provide an essential step toward better understanding the key role of forests in land-based policies for mitigating climate change.

Coarse spatial resolution remote sensing data with AVHRR and MODIS miss the greening area compared with the Landsat data in Chinese drylands

The warming-wetting climates in Chinese drylands, together with a series of ecological engineering projects, had caused apparent changes to vegetation therein. Regarding the vegetation greening trend, different remote sensing data had yielded distinct findings. It was critical to evaluate vegetation dynamics in Chinese drylands using a series of remote sensing data. By comparing the three most commonly used remote sensing datasets [i.e., MODIS, Advanced Very High Resolution Radiometer (AVHRR), and Landsat], this study comprehensively investigated vegetation dynamics for Chinse drylands. All three remote sensing datasets exhibited evident vegetation greening trends from 2000 to 2020 in Chinese drylands, especially in the Loess Plateau and Northeast China. However, Landsat identified the largest greening areas (89.8%), while AVHRR identified the smallest greening area (58%). The vegetation greening areas identified by Landsat comprise more small patches than those identified by MODIS and AVHRR. The MODIS data exhibited a higher consistency with Landsat than with AVHRR in terms of detecting vegetation greening areas. The three datasets exhibited high consistency in identifying vegetation greening in Northeast China, Loess Plateau, and Xinjiang. The percentage of inconsistent areas among the three datasets was 39.56%. The vegetation greening areas identified by Landsat comprised more small patches. Sensors and the atmospheric effect are the two main reasons responsible for the different outputs from each NDVI product. Ecological engineering projects had a great promotion effect on vegetation greening, which can be detected by the three NDVI datasets in Chinese drylands, thereby combating desertification and reducing dust storms.

Time Effects of Global Change on Forest Productivity in China from 2001 to 2017

With global warming, the concentrations of fine particulate matter (PM_2.5) and greenhouse gases, such as CO₂, are increasing. However, it is still unknown whether these increases will affect vegetation productivity. Exploring the impacts of global warming on net primary productivity (NPP) will help us understand how ecosystem function responds to climate change in China. Using the Carnegie-Ames-Stanford Approach (CASA) ecosystem model based on remote sensing, we investigated the spatiotemporal changes in NPP across 1137 sites in China from 2001 to 2017. Our results revealed that: (1) Mean Annual Temperature (MAT) and Mean Annual Precipitation (MAP) were significantly positively correlated with NPP (p < 0.01), while PM_2.5 concentration and CO₂ emissions were significantly negatively correlated with NPP (p < 0.01). (2) The positive correlation between temperature, rainfall and NPP gradually weakened over time, while the negative correlation between PM_2.5 concentration, CO₂ emissions and NPP gradually strengthened over time. (3) High levels of PM_2.5 concentration and CO₂ emissions had negative effects on NPP, while high levels of MAT and MAP had positive effects on NPP.

Tropical volcanic eruptions reduce vegetation net carbon uptake on the Qinghai-Tibet Plateau under background climate conditions

The vegetation carbon uptake plays an important role in the terrestrial carbon cycle on the Qinghai-Tibet Plateau (QTP), while it is extremely sensitive to the impact of natural external forcings. Until now, there is limited knowledge on the spatial-temporal patterns of vegetation net carbon uptake (VNCU) after the force that caused by tropical volcanic eruptions. Here, we conducted an exhaustive reconstruction of VNCU on the QTP over the last millennium, and used a superposed epoch analysis to characterize the VNCU response of the QTP after the tropical volcanic eruptions. We then further investigated the divergent changes of VNCU response across different elevation gradients and vegetation types, and the impact of teleconnection forcing on VNCU after volcanic eruptions. Within a climatic background, we found that VNCU of the QTP tends to decrease after large volcanic eruptions, lasting until about 3 years, with a maximum decrease value occurring in the following 1 year. The spatial and temporal patterns of the VNCU were mainly driven by the post-eruption climate and moderated by the negative phase trends of El Niño-Southern Oscillation and the Atlantic multidecadal oscillation. In addition, elevation and vegetation types were undeniable driving forces associated with VNCU on QTP. Different water-heat conditions and vegetation types contributed to significant differences in the response and recovery processes of VNCU. Our results emphasized the response and recovery processes of VNCU to volcanic eruptions without the strong anthropogenic forcings, while the influence mechanisms of natural forcing on VNCU should receive more attention.

New constraints of terrestrial and oceanic global gross primary productions from the triple oxygen isotopic composition of atmospheric CO2 and O2

Representations of the changing global carbon cycle under climatic and environmental perturbations require highly detailed accounting of all atmosphere and biosphere exchange. These fluxes remain unsatisfactory, as a consequence of only having data with limited spatiotemporal coverage and precision, which restrict accurate assessments. Through the nature of intimate coupling of global carbon and oxygen cycles via O₂ and CO₂ and their unique triple oxygen isotope compositions in the biosphere and atmosphere, greater insight is available. We report analysis of their isotopic compositions with the widest geographical and temporal coverage (123 new measurements for CO₂) and constrain, on an annual basis, the global CO₂ recycling time (1.5 ± 0.2 year) and gross primary productivities of terrestrial (~ 170-200 PgC/year) and oceanic (~ 90-120 PgC/year) biospheres. Observed inter-annual variations in CO₂ triple oxygen isotopic compositions were observed at a magnitude close to the largest contrast set by the terrestrial and oceanic biospheres. The seasonal cycles between the east and west Pacific Ocean were found to be drastically different. This intra-annual variability implies that the entire atmospheric CO₂ turnover time is not much longer than the tropospheric mixing time (less than ~ 5 months), verifying the derived recycling time. The new measurements, analyses, and incorporation of other global data sets allow development of an independent approach, providing a strong constraint to biogeochemical models.

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.

Climate change enhanced the positive contribution of human activities to net ecosystem productivity from 1983 to 2018

Introduction

Accurate assessment of the net ecosystem productivity (NEP) is very important for understanding the global carbon balance. However, it remains unknown whether climate change (CC) promoted or weakened the impact of human activities (HA) on the NEP from 1983 to 2018.

Methods

Here, we quantified the contribution of CC and HA to the global NEP under six different scenarios based on a boosted regression tree model and sensitivity analysis over the last 40 years.

Results and discussion

The results show that (1) a total of 69% of the areas showed an upward trend in the NEP, with HA and CC controlled 36.33 and 32.79% of the NEP growth, respectively. The contribution of HA (HA_con) far exceeded that of CC by 6.4 times. (2) The CO2 concentration had the largest positive contribution (37%) to NEP and the largest influence area (32.5%). It made the most significant contribution to the NEP trend in the range of 435–440 ppm. In more than 50% of the areas, the main loss factor was solar radiation (SR) in any control area of the climate factors. (3) Interestingly, CC enhanced the positive HA_con to the NEP in 44% of the world, and in 25% of the area, the effect was greater than 50%. Our results shed light on the optimal range of each climatic factor for enhancing the NEP and emphasize the important role of CC in enhancing the positive HA_con to the NEP found in previous studies.

Dynamic carbon-nitrogen coupling under global change

Carbon-nitrogen coupling is a fundamental principle in ecosystem ecology. However, how the coupling responds to global change has not yet been examined. Through a comprehensive and systematic literature review, we assessed how the dynamics of carbon processes change with increasing nitrogen input and how nitrogen processes change with increasing carbon input under global change. Our review shows that nitrogen input to the ecosystem mostly stimulates plant primary productivity but inconsistently decreases microbial activities or increases soil carbon sequestration, with nitrogen leaching and nitrogenous gas emission rapidly increasing. Nitrogen fixation increases and nitrogen leaching decreases to improve soil nitrogen availability and support plant growth and ecosystem carbon sequestration under elevated CO₂ and temperature or along ecosystem succession. We conclude that soil nitrogen cycle processes continually adjust to change in response to either overload under nitrogen addition or deficiency under CO₂ enrichment and ecosystem succession to couple with carbon cycling. Indeed, processes of both carbon and nitrogen cycles continually adjust under global change, leading to dynamic coupling in carbon and nitrogen cycles. The dynamic coupling framework reconciles previous debates on the "uncoupling" or "decoupling" of ecosystem carbon and nitrogen cycles under global change. Ecosystem models failing to simulate these dynamic adjustments cannot simulate carbon-nitrogen coupling nor predict ecosystem carbon sequestration well.

Trends in drought and effects on carbon sequestration over the Chinese mainland

Recently, drought events have occurred frequently and have profoundly altered the carbon sequestration in terrestrial ecosystems. How drought affects carbon sequestration is an important issue which may assist in understanding and confronting the challenges of extreme climate change. Nevertheless, drought-induced carbon-cycle effects remain scarce from the perspective of drought indices. In this study, we quantified the impacts of potential evapotranspiration (PET), standardized precipitation evapotranspiration index (SPEI), downward short-wave radiation flux (SWDown), and soil water (Soil_w) on net ecosystem productivity (NEP). We showed that the spatiotemporal heterogeneity of drought was extremely significant, and the hot spots of aridification were mainly distributed in the southwestern Yungui Plateau (YG) and Northwest China (NW). Moreover, the "pan evaporation paradox" appeared across the Chinese mainland before the 1990s and subsequently disappeared. Similarly, in contrast to the moderate NEP fluctuation between 1981 and 1999, since the beginning of the 21st century, NEP has increased significantly across Chinese mainland, YG, the plains region of Changjiang (CJ), and Southeast China (SE). Meanwhile, there are obvious directional, temporal, and spatial differences in the effects of the drought indices on NEP. Specifically, a higher SPEI value results in a more obvious promoting effect on NEP in SE, North China (NN), and northeastern YG. An increase in SWDown can promote an increase in NEP, especially in the northeastern YG and central SE. The increase in Soil_w in parts of the Qinghai-Tibetan Plateau, Xinjiang Region (XJ), southeastern NW, NN, and Northeast China with poor water conditions can promote carbon sinks. The inhibition effect is particularly obvious in some areas of CJ, where water resources are abundant. The fluctuation in PET has a relatively low influence on NEP. This study provides a comprehensive assessment of drought change and its impact on carbon sequestration and may help in formulating appropriate policies for carbon management and ecological security.

Neglecting acclimation of photosynthesis under drought can cause significant errors in predicting leaf photosynthesis in wheat

Extreme climatic events, such as heat waves, cold snaps and drought spells, related to global climate change, have become more frequent and intense in recent years. Acclimation of plant physiological processes to changes in environmental conditions is a key component of plant adaptation to climate change. We assessed the temperature response of leaf photosynthetic parameters in wheat grown under contrasting water regimes and growth temperatures (T_growth ). Two independent experiments were conducted under controlled conditions. In Experiment 1, two wheat genotypes were subjected to well-watered or drought-stressed treatments; in Experiment 2, the two water regimes combined with high, medium and low T_growth were imposed on one genotype. Parameters of a biochemical C₃ -photosynthesis model were estimated at six leaf temperatures for each factor combination. Photosynthesis acclimated more to drought than to T_growth . Drought affected photosynthesis by lowering its optimum temperature (T_opt ) and the values at T_opt of light-saturated net photosynthesis, stomatal conductance, mesophyll conductance, the maximum rate of electron transport (J_max ) and the maximum rate of carboxylation by Rubisco (V_cmax ). T_opt for V_cmax was up to 40°C under well-watered conditions but 24-34°C under drought. The decrease in photosynthesis under drought varied among T_growth but was similar between genotypes. The temperature response of photosynthetic quantum yield under drought was partly attributed to photorespiration but more to alternative electron transport. All these changes in biochemical parameters could not be fully explained by the changed leaf nitrogen content. Further model analysis showed that both diffusional and biochemical parameters of photosynthesis and their thermal sensitivity acclimate little to T_growth , but acclimate considerably to drought and the combination of drought and T_growth . The commonly used modelling approaches, which typically consider the response of diffusional parameters, but ignore acclimation responses of biochemical parameters to drought and T_growth , strongly overestimate leaf photosynthesis under variable temperature and drought.

Using functional indicators to detect state changes in terrestrial ecosystems

Indicators to predict ecosystem state change are urgently needed to cope with the degradation of ecosystem services caused by global change. With the development of new technologies for measuring ecosystem function with fine spatiotemporal resolution over broad areas, we are in the era of 'big data'. However, it is unclear how large, emerging datasets can be used to anticipate ecosystem state change. We propose the construction of indicators based on functional variables (flows) and state variables (pools) to predict future ecosystem state changes. The indicators identified here may be useful signals for doing so. In addition, functional indicators have explicit ecological meanings that can identify the ecological mechanism that is causing state changes, and can thus be used to improve ecosystem models.

Using the atmospheric CO2 growth rate to constrain the CO2 flux from land use and land cover change since 1900

We explore the ability of the atmospheric CO₂ record since 1900 to constrain the source of CO₂ from land use and land cover change (hereafter "land use"), taking account of uncertainties in other terms in the global carbon budget. We find that the atmospheric constraint favors land use CO₂ flux estimates with lower decadal variability and can identify potentially erroneous features, such as emission peaks around 1960 and after 2000, in some published estimates. Furthermore, we resolve an offset in the global carbon budget that is most plausibly attributed to the land use flux. This correction shifts the mean land use flux since 1900 across 20 published estimates down by 0.35 PgC year^-1 to 1.04 ± 0.57 PgC year^-1 , which is within the range but at the low end of these estimates. We show that the atmospheric CO₂ record can provide insights into the time history of the land use flux that may reduce uncertainty in this term and improve current understanding and projections of the global carbon cycle.

Photosynthetic capacity dominates the interannual variation of annual gross primary productivity in the Northern Hemisphere

Annual gross primary productivity (AGPP) of terrestrial ecosystems is the largest carbon flux component in ecosystems; however, it's unclear whether photosynthetic capacity or phenology dominates interannual variation of AGPP, and a better understanding of this could contribute to estimation of carbon sinks and their interactions with climate change. In this study, observed GPP data of 494 site-years from 39 eddy covariance sites in Northern Hemisphere were used to investigate mechanisms of interannual variation of AGPP. This study first decomposed AGPP into three seasonal dynamic attribute parameters (growing season length (CUP), maximum daily GPP (GPP_max), and the ratio of mean daily GPP to GPP_max (α_GPP)), and then decomposed AGPP into mean leaf area index (LAI_m) and annual photosynthetic capacity per leaf area (AGPP_lm). Furthermore, GPP_max was decomposed into leaf area index of DOY_max (the day when GPP_max appeared) (LAI_max) and photosynthesis per leaf area of DOY_max (GPP_lmax). Relative contributions of parameters to AGPP and GPP_max were then calculated. Finally, environmental variables of DOY_max were extracted to analyze factors influencing interannual variation of GPP_lmax. Trends of AGPP in 39 ecosystems varied from -65.23 to 53.05 g C m^-2 yr^-2, with the mean value of 6.32 g C m^-2 yr^-2. Photosynthetic capacity (GPP_max and AGPP_lm), not CUP or LAI, was the main factor dominating interannual variation of AGPP. GPP_lmax determined the interannual variation of GPP_max, and temperature, water, and radiation conditions of DOY_max affected the interannual variation of GPP_lmax. This study used the cascade relationship of "environmental variables-GPP_lmax-GPP_max-AGPP" to explain the mechanism of interannual variation of AGPP, which can provide new ideas for the AGPP estimation based on seasonal dynamic of GPP.

Carbon sinks/sources' spatiotemporal evolution in China and its response to built-up land expansion

Terrestrial ecosystem carbon sink examination in China still faces great uncertainties. Determinant analysis has focused on climate change but ignored the influence of fast urban expansion. Using remote sensing images, climate variable data, and high-resolution land use data, this research improved net ecosystem productivity (NEP) simulation model based on a large number of field observations, and investigated spatial-temporal changes of NEP. This research calculated the NEP loss caused by built-up land expansion and used geographically weighted regression (GWR) model to explore the spatial heterogeneity of the relationship between NEP growth and built-up land expansion. The results showed that China contributed a carbon sink of 0.33 Pg C per year from 2000 to 2020. Southern China had a greater capacity to sequester carbon than northern China. The carbon sink capacity of most Chinese regions increased. Built-up land expansion caused 4.95 Tg C of carbon sink loss per year, which was mainly concentrated in eastern China. In GWR model, 50.8% of regions showed negative correlations between NEP growth and built-up land expansion. These two variables were mostly positively correlated in the northwest and negatively correlated in the southeast. Consequently, this study suggests that maintaining the capacity of carbon sinks in southern provinces is important for China to meet its carbon neutrality goal.

Quantitative assessment of the relative contributions of climate change and human activities to NPP changes in the Southwest Karst area of China

Net primary production (NPP) is an essential component of the terrestrial carbon cycle and an essential factor of ecological processes. In global change research, it was the core content to study the driving forces of NPP change. In this paper, we focused on the Southwest Karst area of China and analyzed the response mechanisms of NPP to topography, land-use types, climatic change, and human activities. Our results showed that (1) changes in elevation and slope lead to significant differences in the spatial distribution of NPP. With the increase of elevation and slope, NPP first increased and then decreased, their critical values were 2000 m and 15°, respectively. (2) NPP varied significantly among different land-use types. The average NPP of the forest was the highest, and the average NPP of cultivated land increased fastest. (3) Temperature and precipitation had the most substantial influence on NPP, both of them promoted the increase of NPP, and the effect of temperature was more obvious in the Southwest Karst area. (4) Ecological engineering significantly promoted the change of NPP, while animal husbandry significantly inhibited the change of NPP. (5) There were significant spatial differences in the driving effects and corresponding contributions of climatic change and human activities; both of them promoted the increase of NPP in the Southwest Karst area of China. Under climatic change and human activities, NPP increased by 1.24 gC·m^-2·year^-1 and 2.29 gC·m^-2·year^-1, respectively. The contributions rates of climatic change and human activities separately accounted for 35% and 65%. The contribution of human activities on NPP was much higher than that of climatic change in the Southwest Karst area, and the results suggested that we should focus on the role of human activities on NPP change.

Spatiotemporal changes and driving factors of vegetation in 14 different climatic regions in the global from 1981 to 2018

Climate change affects the change of vegetation, and the analysis of vegetation change and its drivers in different globe climate zones is important for ecological conservation, energy balances, and climate change in different global climate zones. Based on the vegetation leaf area index (LAI) and climate factor datasets, this paper uses an integrated empirical model decomposition, sensitivity rate, contribution rate, and geographic detector analysis method to study the vegetation drivers and their changes in 14 different climate zones around the globe from 1981 to 2018. The results showed that (1) Vegetation changes were sensitive to precipitation and evapotranspiration in arid climate zones and to temperature and soil temperature in cold climate zones. In the tundra climate zone, the sensitivity of vegetation change to temperature was higher than that to precipitation and evapotranspiration. (2) Soil moisture has the highest contribution to vegetation change, and the areas with absolute contribution rates over 60% account for 50.26% of the total area of global vegetation cover. The areas with high contributions of temperature and soil temperature to the LAI are mainly distributed in the Northern Hemisphere, which indicates that temperature has a high contribution to vegetation change in low-temperature environments. (3) The areas with significant increasing trends for the global vegetation LAIs accounted for approximately 15.32% of the total global vegetation cover (slope ≥ 0.01), which are mainly located in equatorial savannahs with dry winters, warm temperate climates with dry winters, and warm temperate climates with fully humid climatic zones. (4) The LAIs were dominated by medium-high fluctuations and sustainable increasing changes, which accounted for 61.27% and 69.34% of the total global vegetation cover area, respectively. (5) Globally, the driving factors influencing LAI changes are specific humidity, temperature, soil temperature, evapotranspiration, precipitation, and soil moisture in descending order, with the largest interaction effect of specific humidity and soil moisture on LAI changes. This research provides a scientific basis for vegetation change monitoring, driving mechanisms, and ecological protection in different climate regions around the globe.

Spatiotemporal Changes and Driver Analysis of Ecosystem Respiration in the Tibetan and Inner Mongolian Grasslands

Ecosystem respiration (RE) plays a critical role in terrestrial carbon cycles, and quantification of RE is important for understanding the interaction between climate change and carbon dynamics. We used a multi-level attention network, Geoman, to identify the relative importance of environmental factors and to simulate spatiotemporal changes in RE in northern China’s grasslands during 2001–2015, based on 18 flux sites and multi-source spatial data. Results indicate that Geoman performed well (R2 = 0.87, RMSE = 0.39 g C m−2 d−1, MAE = 0.28 g C m−2 d−1), and that grassland type and soil texture are the two most important environmental variables for RE estimation. RE in alpine grasslands showed a decreasing gradient from southeast to northwest, and that of temperate grasslands showed a decreasing gradient from northeast to southwest. This can be explained by the enhanced vegetation index (EVI), and soil factors including soil organic carbon density and soil texture. RE in northern China’s grasslands showed a significant increase (1.81 g C m−2 yr−1) during 2001–2015. The increase rate of RE in alpine grassland (2.36 g C m−2 yr−1) was greater than that in temperate grassland (1.28 g C m−2 yr−1). Temperature and EVI contributed to the interannual change of RE in alpine grassland, and precipitation and EVI were the main contributors in temperate grassland. This study provides a key reference for the application of advanced deep learning models in carbon cycle simulation, to reduce uncertainties and improve understanding of the effects of biotic and climatic factors on spatiotemporal changes in RE.

Regional Contributions and Climate Attributions to Interannual Variation of Global Net Ecosystems Production by an ECOSYSTEM Processed Model Driven by Remote Sensing Data over the Past 35 Years

Global climate change has significantly affected terrestrial carbon sinks. Net ecosystem production (NEP) plays a critical role in the global carbon cycle. However, interannual variability (IAV) of the NEP and its regional contributions and climate attributions are not well-understood on a global scale. This study used a diagnostic model driven by remote sensing leaf area index (LAI) to investigate the NEP IAV and analyze regional and climate contributions on a global scale from 1982 to 2016. We found large NEP IAV during the study period, with the NEP detrended anomaly ranging from −2.3 Pg C in 1998 to 1.6 Pg C in 2013 at a global scale. Furthermore, 63.7% and 34.1% of the areas showed positive and negative contributions to NEP IAVs globally, respectively. Evergreen broadleaf forest (EBF) contributed the most (31.1%) to NEP IAV, followed by cropland (21.7%) and grassland (20.8%). Temperature played the most critical roles in the global NEP IAV, with a contribution of 45.5%. However, the partial correlation between NEP and temperature was negative, and the correlation with precipitation was positive in most areas of the globe, indicating that global warming is not conducive to the global carbon sink, but abundant rainfall is important for the global carbon cycle. This study suggests that, to increase the global carbon sink, we should pay more attention to tropical forests (EBFs) and highlight the importance of water availability.

Terrestrial carbon sinks in China and around the world and their contribution to carbon neutrality

Enhancing the terrestrial ecosystem carbon sink (referred to as terrestrial C sink) is an important way to slow down the continuous increase in atmospheric carbon dioxide (CO₂) concentration and to achieve carbon neutrality target. To better understand the characteristics of terrestrial C sinks and their contribution to carbon neutrality, this review summarizes major progress in terrestrial C budget researches during the past decades, clarifies spatial patterns and drivers of terrestrial C sources and sinks in China and around the world, and examines the role of terrestrial C sinks in achieving carbon neutrality target. According to recent studies, the global terrestrial C sink has been increasing from a source of (-0.2±0.9) Pg C yr^-1 (1 Pg=10¹⁵ g) in the 1960s to a sink of (1.9±1.1) Pg C yr^-1 in the 2010s. By synthesizing the published data, we estimate terrestrial C sink of 0.20-0.25 Pg C yr^-1 in China during the past decades, and predict it to be 0.15-0.52 Pg C yr^-1 by 2060. The terrestrial C sinks are mainly located in the mid- and high latitudes of the Northern Hemisphere, while tropical regions act as a weak C sink or source. The C balance differs much among ecosystem types: forest is the major C sink; shrubland, wetland and farmland soil act as C sinks; and whether the grassland functions as C sink or source remains unclear. Desert might be a C sink, but the magnitude and the associated mechanisms are still controversial. Elevated atmospheric CO₂ concentration, nitrogen deposition, climate change, and land cover change are the main drivers of terrestrial C sinks, while other factors such as fires and aerosols would also affect ecosystem C balance. The driving factors of terrestrial C sink differ among regions. Elevated CO₂ concentration and climate change are major drivers of the C sinks in North America and Europe, while afforestation and ecological restoration are additionally important forcing factors of terrestrial C sinks in China. For future studies, we recommend the necessity for intensive and long term ecosystem C monitoring over broad geographic scale to improve terrestrial biosphere models for accurately evaluating terrestrial C budget and its dynamics under various climate change and policy scenarios.

Field-based tree mortality constraint reduces estimates of model-projected forest carbon sinks

Considerable uncertainty and debate exist in projecting the future capacity of forests to sequester atmospheric CO₂. Here we estimate spatially explicit patterns of biomass loss by tree mortality (LOSS) from largely unmanaged forest plots to constrain projected (2015–2099) net primary productivity (NPP), heterotrophic respiration (HR) and net carbon sink in six dynamic global vegetation models (DGVMs) across continents. This approach relies on a strong relationship among LOSS, NPP, and HR at continental or biome scales. The DGVMs overestimated historical LOSS, particularly in tropical regions and eastern North America by as much as 5 Mg ha⁻¹ y⁻¹. The modeled spread of DGVM-projected NPP and HR uncertainties was substantially reduced in tropical regions after incorporating the field-based mortality constraint. The observation-constrained models show a decrease in the tropical forest carbon sink by the end of the century, particularly across South America (from 2 to 1.4 PgC y⁻¹), and an increase in the sink in North America (from 0.8 to 1.1 PgC y⁻¹). These results highlight the feasibility of using forest demographic data to empirically constrain forest carbon sink projections and the potential overestimation of projected tropical forest carbon sinks.

Here the authors use broad-scale tree mortality data to estimate biomass loss, constraining uncertainty of projected forest net primary productivity in 6 models, finding weaker tropical forest carbon sinks with climate change.

Estimation of China’s Contribution to Global Greening over the Past Three Decades

China’s contribution to global greening is regulated by increasing atmospheric CO2 concentrations, climate change, and land use. Based on TRENDY project data, this study identified that the shifts in China’s contribution to the global leaf area index (LAI) trend strongly reduced during the warming hiatus, translating from 13.42 ± 26.45% during 1982–1998 into 7.91 ± 25.45% during 1999–2012. First, significant negative sensitivities of LAI to enhanced vapor pressure deficit (VPD), when only considering the climate effect derived from TRENDY models in China, were found to have shifted substantially after the late 1990s. However, globally, LAI had positive rather than negative responses to enhanced VPD. These opposing shifts in the response of LAI to enhanced VPD reduced the national contribution to global vegetation greening. Second, shifts in land-use change and their effects on the LAI trends in the two periods in China were accompanied by major changes in land cover and land management intensity, including forestry. Consequently, the contribution of land use in China reduced by −47.68% during the warming hiatus period, as compared with the warming period. Such a shift in the impact of land-use change on LAI simulated by ecosystem models might result from the models’ lack of consideration of conserving and expanding forests with the goal of mitigating climate change for China. Our results highlight the need for ecosystem models to reproduce the enhanced negative impact on global LAI and consider the shifts in man-made adaptation policies (e.g., forest management) to improve terrestrial ecosystem models in the future.

Spatiotemporal dynamics of vegetation in China from 1981 to 2100 from the perspective of hydrothermal factor analysis

The increased growth of vegetation has the potential to slow global climate warming. Therefore, analyzing and predicting the response assessment of Chinese vegetation to climate change is of great significance to studies of global warming. In this paper, we examine the spatiotemporal dynamics of vegetation leaf area index (LAI) values in China from 1981 to 2017 and their correlations with meteorological (hydrothermal) factors based on trend analysis and correlation analysis. We further construct an LAI prediction model based on hydrothermal conditions. The climate data obtained under different scenarios in the CMIP5 and CMIP6 climate models were used to predict the dynamic change trend of vegetation LAI from 2021 to 2100. The results show that most areas of China (72.82%) showed an improving trend in vegetation LAI from 1981 to 2017, during which the annual average LAI value increased at a rate of 0.0029 year-1. Vegetation LAI in China was significantly correlated with climatic factors (temperature, precipitation, and evapotranspiration), and the LAI prediction model constructed based on hydrothermal conditions had a high accuracy (Pearson's Cor value is 0.9729). From 2021 to 2100, approximately 2/3 of China's vegetation LAI area showed an improvement trend, and the impact of climate change on vegetation LAI predictions under the high emission scenario was greater than that under the low emission scenario. This research can provide a basis for studies on the climatic drivers of vegetation change and the global vegetation dynamic model.

Biota-mediated carbon cycling-A synthesis of biotic-interaction controls on blue carbon

Research into biotic interactions has been a core theme of ecology for over a century. However, despite the obvious role that biota play in the global carbon cycle, the effects of biotic interactions on carbon pools and fluxes are poorly understood. Here we develop a conceptual framework that illustrates the importance of biotic interactions in regulating carbon cycling based on a literature review and a quantitative synthesis by means of meta-analysis. Our study focuses on blue carbon ecosystems-vegetated coastal ecosystems that function as the most effective long-term CO₂ sinks of the biosphere. We demonstrate that a multitude of mutualistic, competitive and consumer-resource interactions between plants, animals and microbiota exert strong effects on carbon cycling across various spatial scales ranging from the rhizosphere to the landscape scale. Climate change-sensitive abiotic factors modulate the strength of biotic-interaction effects on carbon fluxes, suggesting that the importance of biota-mediated carbon cycling will change under future climatic conditions. Strong effects of biotic interactions on carbon cycling imply that biosphere-climate feedbacks may not be sufficiently represented in current Earth system models. Inclusion of new functional groups in these models, and new approaches to simplify species interactions, may thus improve the predictions of biotic effects on the global climate.

Is photosynthetic enhancement sustained through three years of elevated CO2 exposure in 175-year-old Quercus robur?

Current carbon cycle models attribute rising atmospheric CO2 as the major driver of the increased terrestrial carbon sink, but with substantial uncertainties. The photosynthetic response of trees to elevated atmospheric CO2 is a necessary step, but not the only one, for sustaining the terrestrial carbon uptake, but can vary diurnally, seasonally and with duration of CO2 exposure. Hence, we sought to quantify the photosynthetic response of the canopy-dominant species, Quercus robur, in a mature deciduous forest to elevated CO2 (eCO2) (+150 μmol mol-1 CO2) over the first 3 years of a long-term free air CO2 enrichment facility at the Birmingham Institute of Forest Research in central England (BIFoR FACE). Over 3000 measurements of leaf gas exchange and related biochemical parameters were conducted in the upper canopy to assess the diurnal and seasonal responses of photosynthesis during the 2nd and 3rd year of eCO2 exposure. Measurements of photosynthetic capacity via biochemical parameters, derived from CO2 response curves, (Vcmax and Jmax) together with leaf nitrogen concentrations from the pre-treatment year to the 3rd year of eCO2 exposure, were examined. We hypothesized an initial enhancement in light-saturated net photosynthetic rates (Asat) with CO2 enrichment of ≈37% based on theory but also expected photosynthetic capacity would fall over the duration of the study. Over the 3-year period, Asat of upper-canopy leaves was 33 ± 8% higher (mean and standard error) in trees grown in eCO2 compared with ambient CO2 (aCO2), and photosynthetic enhancement decreased with decreasing light. There were no significant effects of CO2 treatment on Vcmax or Jmax, nor leaf nitrogen. Our results suggest that mature Q. robur may exhibit a sustained, positive response to eCO2 without photosynthetic downregulation, suggesting that, with adequate nutrients, there will be sustained enhancement in C assimilated by these mature trees. Further research will be required to understand the location and role of the additionally assimilated carbon.

Global maps and factors driving forest foliar elemental composition: the importance of evolutionary history

Consistent information on the current elemental composition of vegetation at global scale and the variables that determine it is lacking. To fill this gap, we gathered a total of 30 912 georeferenced records on woody plants foliar concentrations of nitrogen (N), phosphorus (P) and potassium (K) from published databases, and produced global maps of foliar N, P and K concentrations for woody plants using neural networks at a resolution of 1 km² . We used data for climate, atmospheric deposition, soil and morphoclimatic groups to train the neural networks. Foliar N, P and K do not follow clear global latitudinal patterns but are consistent with the hypothesis of soil substrate age. We additionally built generalized linear mixed models to investigate the evolutionary history effect together with the effects of environmental effects. In this comparison, evolutionary history effects explained most of the variability in all cases (mostly > 60%). These results emphasize the determinant role of evolutionary history in foliar elemental composition, which should be incorporated in upcoming dynamic global vegetation models.

Temperature acclimation of leaf respiration differs between marsh and mangrove vegetation in a coastal wetland ecotone

Temperature acclimation of leaf respiration (R) is an important determinant of ecosystem responses to temperature and the magnitude of temperature-CO₂ feedbacks as climate warms. Yet, the extent to which temperature acclimation of R exhibits a common pattern across different growth conditions, ecosystems, and plant functional types remains unclear. Here, we measured the short-term temperature response of R at six time points over a 10-month period in two coastal wetland species (Avicennia germinans [C₃ mangrove] and Spartina alterniflora [C₄ marsh grass]) growing under ambient and experimentally warmed temperatures at two sites in a marsh-mangrove ecotone. Leaf nitrogen (N) was determined on a subsample of leaves to explore potential coupling of R and N. We hypothesized that both species would reduce R at 25°C (R²⁵ ) and the short-term temperature sensitivity of R (Q₁₀ ) as air temperature (T_air ) increased across seasons, but the decline would be stronger in Avicennia than in Spartina. For each species, we hypothesized that seasonal temperature acclimation of R would be equivalent in plants grown under ambient and warmed temperatures, demonstrating convergent acclimation. Surprisingly, Avicennia generally increased R²⁵ with increasing growth temperature, although the Q₁₀ declined as seasonal temperatures increased and did so consistently across sites and treatments. Weak temperature acclimation resulted in reduced homeostasis of R in Avicennia. Spartina reduced R²⁵ and the Q₁₀ as seasonal temperatures increased. In Spartina, seasonal temperature acclimation was largely consistent across sites and treatments resulting in greater respiratory homeostasis. We conclude that co-occurring coastal wetland species may show contrasting patterns of respiratory temperature acclimation. Nonetheless, leaf N scaled positively with R²⁵ in both species, highlighting the importance of leaf N in predicting respiratory capacity across a range of growth temperatures. The patterns of respiratory temperature acclimation shown here may improve the predictions of temperature controls of CO₂ fluxes in coastal wetlands.

A constraint on historic growth in global photosynthesis due to increasing CO2

The global terrestrial carbon sink is increasing^1-3, offsetting roughly a third of anthropogenic CO₂ released into the atmosphere each decade¹, and thus serving to slow⁴ the growth of atmospheric CO₂. It has been suggested that a CO₂-induced long-term increase in global photosynthesis, a process known as CO₂ fertilization, is responsible for a large proportion of the current terrestrial carbon sink^4-7. The estimated magnitude of the historic increase in photosynthesis as result of increasing atmospheric CO₂ concentrations, however, differs by an order of magnitude between long-term proxies and terrestrial biosphere models^7-13. Here we quantify the historic effect of CO₂ on global photosynthesis by identifying an emergent constraint^14-16 that combines terrestrial biosphere models with global carbon budget estimates. Our analysis suggests that CO₂ fertilization increased global annual photosynthesis by 11.85 ± 1.4%, or 13.98 ± 1.63 petagrams carbon (mean ± 95% confidence interval) between 1981 and 2020. Our results help resolve conflicting estimates of the historic sensitivity of global photosynthesis to CO₂, and highlight the large impact anthropogenic emissions have had on ecosystems worldwide.

A bibliometric analysis of carbon exchange in global drylands

Drylands refer to regions with an aridity index lower than 0.65, and billions of people depend on services provided by the critically important ecosystems in these areas. How ecosystem carbon exchange in global drylands (CED) occurs and how climate change affects CED are critical to the global carbon cycle. Here, we performed a comprehensive bibliometric study on the fields of annual publications, marked journals, marked institutions, marked countries, popular keywords, and their temporal evolution to understand the temporal trends of CED research over the past 30 a (1991-2020). We found that the annual scientific publications on CED research increased significantly at an average growth rate of 7.93%. Agricultural Water Management ranked first among all journals and had the most citations. The ten most productive institutions were centered on drylands in America, China, and Australia that had the largest number and most citations of publications on CED research. "Climate change" and climate-related (such as "drought", "precipitation", "temperature", and "rainfall") research were found to be the most popular study areas. Keywords were classified into five clusters, indicating the five main research focuses on CED studies: hydrological cycle, effects of climate change, carbon and water balance, productivity, and carbon-nitrogen-phosphorous coupling cycles. The temporal evolution of keywords further showed that the areas of focus on CED studies were transformed from classical pedology and agricultural research to applied ecology and then to global change ecological research over the past 30 a. In future CED studies, basic themes (such as "water", "yield", and "salinity") and motor themes (such as "climate change", "sustainability", and "remote sensing") will be the focus of research on CED. In particular, multiple integrated methods to understand climate change and ecosystem sustainability are potential new research trends and hotspots.

Changes in carbon and nitrogen metabolism during seawater-induced mortality of Picea sitchensis trees

Increasing seawater exposure is causing mortality of coastal forests, yet the physiological response associated with seawater-induced tree mortality, particularly in non-halophytes, is poorly understood. We investigated the shifts in carbon and nitrogen (N) metabolism of mature Sitka-spruce trees that were dying after an ecosystem-scale manipulation of tidal seawater exposure. Soil porewater salinity and foliar ion concentrations increased after seawater exposure and were strongly correlated with the percentage of live foliated crown (PLFC; e.g., crown 'greenness', a measure of progression to death). Co-occurring with decreasing PLFC was decreasing photosynthetic capacity, N-investment into photosynthesis, N-resorption efficiency and non-structural carbohydrate (soluble sugars and starch) concentrations, with the starch reserves depleted to near zero when PLFC dropped below 5%. Combined with declining PLFC, these changes subsequently decreased total carbon gain and thus exacerbated the carbon starvation process. This study suggests that an impairment in carbon and N metabolism during the mortality process after seawater exposure is associated with the process of carbon starvation, and provides critical knowledge necessary to predict sea-level rise impacts on coastal forests.

A decreasing carbon allocation to belowground autotrophic respiration in global forest ecosystems

Belowground autotrophic respiration (RA_soil) depends on carbohydrates from photosynthesis flowing to roots and rhizospheres, and is one of the most important but least understood components in forest carbon cycling. Carbon allocation plays an important role in forest carbon cycling and reflects forest adaptation to changing environmental conditions. However, carbon allocation to RA_soil has not been fully examined at the global scale. To fill this knowledge gap, we first used a Random Forest algorithm to predict the spatio-temporal patterns of RA_soil from 1981 to 2017 based on the most updated Global Soil Respiration Database (v5) with global environmental variables; calculated carbon allocation from photosynthesis to RA_soil (CA_B) as a fraction of gross primary production; and assessed its temporal and spatial patterns in global forest ecosystems. Globally, mean RA_soil from forests was 8.9 ± 0.08 Pg C yr^-1 (mean ± standard deviation) from 1981 to 2017 and increased significantly at a rate of 0.006 Pg C yr^-2, paralleling broader soil respiration changes and suggesting increasing carbon respired by roots. Mean CA_B was 0.243 ± 0.016 and decreased over time. The temporal trend of CA_B varied greatly in space, reflecting uneven responses of CA_B to environmental changes. Combined with carbon use efficiency, our CA_B results offer a completely independent approach to quantify global aboveground autotropic respiration spatially and temporally, and could provide crucial insights into carbon flux partitioning and global carbon cycling under climate change.

Satellite-Observed Effects from Ozone Pollution and Climate Change on Growing-Season Vegetation Activity over China during 1982–2020

Remote sensing vegetation index data contain important information about the effects of ozone pollution, climate change and other factors on vegetation growth. However, the absence of long-term observational data on surface ozone pollution and neglected air pollution-induced effects on vegetation growth have made it difficult to conduct in-depth studies on the long-term, large-scale ozone pollution effects on vegetation health. In this study, a multiple linear regression model was developed, based on normalized difference vegetation index (NDVI) data, ozone mass mixing ratio (OMR) data at 1000 hPa, and temperature (T), precipitation (P) and surface net radiation (SSR) data during 1982–2020 to quantitatively assess the impact of ozone pollution and climate change on vegetation growth in China on growing season. The OMR data showed an increasing trend in 99.9% of regions in China over the last 39 years, and both NDVI values showed increasing trends on a spatial basis with different ozone pollution levels. Additionally, the significant correlations between NDVI and OMR, temperature and SSR indicate that vegetation activity is closely related to ozone pollution and climate change. Ozone pollution affected 12.5% of NDVI, and climate change affected 26.7% of NDVI. Furthermore, the effects from ozone pollution and climate change on forest, shrub, grass and crop vegetation were evaluated. Notably, the impact of ozone pollution on vegetation growth was 0.47 times that of climate change, indicating that the impact of ozone pollution on vegetation growth cannot be ignored. This study not only deepens the understanding of the effects of ozone pollution and climate change on vegetation growth but also provides a research framework for the large-scale monitoring of air pollution on vegetation health using remote sensing vegetation data.

Comparing Three Remotely Sensed Approaches for Simulating Gross Primary Productivity over Mountainous Watersheds: A Case Study in the Wanglang National Nature Reserve, China

Light Use Efficiency (LUE), Vegetation Index (VI)-based, and process-based models are the main approaches for spatially continuous gross primary productivity (GPP) estimation. However, most current GPP models overlook the effects of topography on the vegetation photosynthesis process. Based on the structures of a two-leaf LUE model (TL-LUE), a VI-based model (temperature and greenness, TG), and a process-based model (Boreal Ecosystem Productivity Simulator, BEPS), three models, named mountain TL-LUE (MTL-LUE), mountain TG (MTG), and BEPS-TerrainLab, have been proposed to improve GPP estimation over mountainous areas. The GPP estimates from the three mountain models have been proven to align more closely with tower-based GPP than those from the original models at the site scale, but their abilities to characterize the spatial variation of GPP at the watershed scale are not yet known. In this work, the GPP estimates from three LUE models (i.e., MOD17, TL-LUE, and MTL-LUE), two VI-based models (i.e., TG and MTG), and two process-based models (i.e., BEPS and BEPS-TerrainLab) were compared for a mountainous watershed. At the watershed scale, the annual GPP estimates from MTL-LUE, MTG, and BTL were found to have a higher spatial variation than those from the original models (increasing the spatial coefficient of variation by 6%, 8%, and 22%), highlighting that incorporating topographic information into GPP models might improve understanding of the high spatial heterogeneity of the vegetation photosynthesis process over mountainous areas. Obvious discrepancies were also observed in the GPP estimates from MTL-LUE, MTG, and BTL, with determination coefficients ranging from 0.02–0.29 and root mean square errors ranging from 399–821 gC m−2yr−1. These GPP discrepancies mainly stem from the different (1) structures of original LUE, VI, and process models, (2) assumptions associated with the effects of topography on photosynthesis, (3) input data, and (4) values of sensitive parameters. Our study highlights the importance of considering surface topography when modeling GPP over mountainous areas, and suggests that more attention should be given to the discrepancy of GPP estimates from different models.

Would the obtainable gross primary productivity (GPP) products stand up? A critical assessment of 45 global GPP products

Gross primary productivity (GPP) is a vital variable of the global carbon cycle, but the quantification of global GPP is subject to significant uncertainty due to the lack of direct observations at a global scale. Here, we evaluated and compared 45 GPP products in terms of their applicability to different vegetation types at various spatiotemporal scales. The results show that 44 GPP products and obsGPP (Model Tree Ensemble GPP derived from observations and named obsGPP) have similar global patterns with correlation coefficients greater than 0.8 except for NGT, where GOSIF, RS, and BESS are prominent. GPP products have the greatest variation in Suriname, with a mean 75th and 25th percentile difference value of 0.4748 (normalized), and we recommend RS, SDGVM and LPJ-wsl as they provide GPP estimates close to the average GPP. In terms of seasonal estimations, considerable disagreement occurs among the GPP products in winter, with a range from 118.76 to 314.95 gC/m²/season, among which JULES has the closest GPP value to the average GPP estimation. For studies concerning vegetation types preference is given to the LUE average GPP. The 45 GPP products are more consistent on grasslands but, have obvious differences for savannas. All GPP products have their own specific spatiotemporal scales, such as global or national scales or different seasons and different vegetation types (forest, grasslands, etc.). This study provides guidelines for selecting GPP products.

Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask?

Estimates of Amazon rainforest gross primary productivity (GPP) differ by a factor of 2 across a suite of three statistical and 18 process models. This wide spread contributes uncertainty to predictions of future climate. We compare the mean and variance of GPP from these models to that of GPP at six eddy covariance (EC) towers. Only one model's mean GPP across all sites falls within a 99% confidence interval for EC GPP, and only one model matches EC variance. The strength of model response to climate drivers is related to model ability to match the seasonal pattern of the EC GPP. Models with stronger seasonal swings in GPP have stronger responses to rain, light, and temperature than does EC GPP. The model to data comparison illustrates a trade-off inherent to deterministic models between accurate simulation of a mean (average) and accurate responsiveness to drivers. The trade-off exists because all deterministic models simplify processes and lack at least some consequential driver or interaction. If a model's sensitivities to included drivers and their interactions are accurate, then deterministically predicted outcomes have less variability than is realistic. If a GPP model has stronger responses to climate drivers than found in data, model predictions may match the observed variance and seasonal pattern but are likely to overpredict GPP response to climate change. High or realistic variability of model estimates relative to reference data indicate that the model is hypersensitive to one or more drivers.

Recent leveling off of vegetation greenness and primary production reveals the increasing soil water limitations on the greening Earth

Global vegetation photosynthesis and productivity have increased substantially since the 1980s, but this trend is heterogeneous in both time and space. Here, we categorize the secular trend in global vegetation greenness into sustained greening, sustained browning and greening-to-browning. We found that by 2016, increased global vegetation greenness had begun to level off, with the area of browning increasing in the last decade, reaching 39.0 million km² (35.9% of the world's vegetated area). This area is larger than the area with sustained increasing growth (27.8 million km², 26.4%); thus, 12.0% ± 3.1% (0.019 ± 0.004 NDVI a^-1) of the previous earlier increase has been offset since 2010 (2010-2016, P < 0.05). Global gross primary production also leveled off, following the trend in vegetation greenness in time and space. This leveling off was caused by increasing soil water limitations due to the spatial expansion of drought, whose impact dominated over the impacts of temperature and solar radiation. This response of global gross primary production to soil water limitation was not identified by land submodels within Earth system models. Our results provide empirical evidence that global vegetation greenness and primary production are offset by water stress and suggest that as global warming continues, land submodels may overestimate the world's capacity to take up carbon with global vegetation greening.

Disentangling the Impacts of Anthropogenic Aerosols on Terrestrial Carbon Cycle During 1850-2014

Aerosols have a dimming and cooling effect and change hydrological regimes, thus affecting carbon fluxes, which are sensitive to climate. Aerosols also scatter sunlight, which increases the fraction of diffuse radiation, increasing photosynthesis. There remains no clear conclusion whether the impact of aerosols on land carbon fluxes is larger through diffuse radiation change than through changes in other climate variables. In this study, we quantified the overall physical impacts of anthropogenic aerosols on land C fluxes and explored the contribution from each factor using a set of factorial simulations driven by climate and aerosol data from the IPSL-CM6A-LR experiments during 1850-2014. A newly developed land surface model which distinguishes diffuse and direct radiation in canopy radiation transmission, ORCHIDEE_DF, was used. Specifically, a subgrid scheme was developed to distinguish the cloudy and clear sky conditions. We found that anthropogenic aerosol emissions since 1850 cumulatively enhanced the land C sink by 22.6 PgC. Seventy-eight percent of this C sink enhancement is contributed by aerosol-induced increase in the diffuse radiation fraction, much larger than the effect of the aerosol-induced dimming. The cooling of anthropogenic aerosols has different impacts in different latitudes but overall increases the global land C sink. The dominant role of diffuse radiation changes found in this study implies that future aerosol emissions may have a much stronger impacts on the C cycle through changing radiation quality than through changing climate alone. Earth system models need to consider the diffuse radiation fertilization effect to better evaluate the impacts of climate change mitigation scenarios.