Artificial intelligence for geoscience: Progress, challenges, and perspectives

This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth's complexities and uncertainties pose challenges in optimization and real-world applicability. In contrast, contemporary data-driven models, particularly those utilizing machine learning (ML) and deep learning (DL), leverage extensive geoscience data to glean insights without requiring exhaustive theoretical knowledge. ML techniques have shown promise in addressing Earth science-related questions. Nevertheless, challenges such as data scarcity, computational demands, data privacy concerns, and the "black-box" nature of AI models hinder their seamless integration into geoscience. The integration of physics-based and data-driven methodologies into hybrid models presents an alternative paradigm. These models, which incorporate domain knowledge to guide AI methodologies, demonstrate enhanced efficiency and performance with reduced training data requirements. This review provides a comprehensive overview of geoscientific research paradigms, emphasizing untapped opportunities at the intersection of advanced AI techniques and geoscience. It examines major methodologies, showcases advances in large-scale models, and discusses the challenges and prospects that will shape the future landscape of AI in geoscience. The paper outlines a dynamic field ripe with possibilities, poised to unlock new understandings of Earth's complexities and further advance geoscience exploration.

Warming-Induced Vegetation Greening May Aggravate Soil Mercury Levels Worldwide

Mercury, a neurotoxic substance, circulates globally, significantly stored in soils through atmospheric deposition and plant decay. Despite being deposited, mercury can be remobilized and released into the atmosphere and water, enhancing its global cycle. Recent research suggests that climate warming may amplify the remobilization of soil mercury, facilitating its incorporation into food webs that humans exploit. However, the potential geospatial feedback of soil mercury levels in response to warming remains unclear. By leveraging up-to-date soil measurements and observation-driven models, we determined the amount of mercury stored in global 0-100 cm soils to be 4.3 Tg (interquartile range: 2.5-6.3 Tg). Furthermore, our analysis indicates that warming likely aggravates global soil mercury levels, particularly in many temperate areas in East Asia, North Europe, and North America (>20 ng g-1 increase by 2100) due to warming-induced vegetation greening. Critically, observation-driven models raise the possibility that implementing ambitious mercury-emission-control schemes alone may be insufficient to counterbalance the positive feedback of soil mercury concentration, while process-based biogeochemical modeling demonstrates consistent patterns that reinforce this concern. These findings hold broad implications; for example, such feedback may catalyze mercury remobilization in land-ocean continuums and exacerbate human risks, stressing the necessity for continued reductions in greenhouse gas and mercury emissions.

Long-term trend and interannual variation in evapotranspiration of a young temperate Douglas-fir stand over 2002-2022 reveals the impacts of climate change

The shortage of decades-long continuous measurements of ecosystem processes limits our understanding of how changing climate impacts forest ecosystems. We used continuous eddy-covariance and hydrometeorological data over 2002-2022 from a young Douglas-fir stand on Vancouver Island, Canada to assess the long-term trend and interannual variability in evapotranspiration (ET) and transpiration (T). Collectively, annual T displayed a decreasing trend over the 21 years with a rate of 1% yr-1, which is attributed to the stomatal downregulation induced by rising atmospheric CO2 concentration. Similarly, annual ET also showed a decreasing trend since evaporation stayed relatively constant. Variability in detrended annual ET was mostly controlled by the average soil water storage during the growing season (May-October). Though the duration and intensity of the drought did not increase, the drought-induced decreases in T and ET showed an increasing trend. This pattern may reflect the changes in forest structure, related to the decline in the deciduous understory cover during the stand development. These results suggest that the water-saving effect of stomatal regulation and water-related factors mostly determined the trend and variability in ET, respectively. This may also imply an increase in the limitation of water availability on ET in young forests, associated with the structural and compositional changes related to forest growth.

A shift in transitional forests of the North American boreal will persist through 2100

High northern latitude changes with Arctic amplification across a latitudinal forest gradient suggest a shift towards an increased presence of trees and shrubs. The persistence of change may depend on the future scenarios of climate and on the current state, and site history, of forest structure. Here, we explore the persistence of a gradient-based shift in the boreal by connecting current forest patterns to recent tree cover trends and future modeled estimates of canopy height through 2100. Results show variation in the predicted potential height changes across the structural gradient from the boreal forest through the taiga-tundra ecotone. Positive potential changes in height are concentrated in transitional forests, where recent positive changes in cover prevail, while potential change in boreal forest is highly variable. Results are consistent across climate scenarios, revealing a persistent biome shift through 2100 in North America concentrated in transitional landscapes regardless of climate scenario.

Analysis of taiga and tundra lake browning trends from 2002 to 2021 using MODIS data

Lakes in taiga and tundra regions may be silently undergoing changes due to global warming. One of those changes is browning in lake color. The browning interacts with the carbon cycle, ecosystem dynamics, and water quality in freshwater systems. However, spatiotemporal variabilities of browning in these regions have not been well documented. Using MODIS remote sensing reflectance at near ultraviolet wavelengths from 2002 to 2021 on the Google Earth Engine platform, we quantified long-term browning trends across 7616 lakes (larger than 10 km2) in taiga and tundra biomes. These lakes showed an overall decreased trend in browning (Theil-Sen Slope = 0.00015), with ∼36% of these lakes showing browning trends, and ∼1% of these lakes showing statistically significant (p-value <0.05) browning trends. The browning trends more likely occurred in small lakes in high latitude, low ground ice content regions, where air temperature increased and precipitation decreased. While temperature is projected to increase in response to climate change, our results provide one means to understand how biogeochemical cycles and ecological dynamics respond to climate change.

Warming affects leaf light use efficiency and functional traits in alpine plants: evidence from a 4-year in-situ field experiment

Introduction

Light use efficiency (LUE) is a crucial determinant of plant productivity, while leaf functional traits directly affect ecosystem functions. However, it remains unclear how climate warming affects LUE and leaf functional traits of dominant species in alpine meadows.

Methods

We conducted a 4-year in-situ field warming experiment to investigate the eco-physiological characteristics for a dominant species (Elymus nutans) and a common species (Potentilla anserina) on the Tibetan Plateau. The leaf traits, photosynthesis and fluorescence characteristics were measured, along with the soil physical-chemical properties associated with the two species.

Results and discussions

Experimental warming increased the leaf LUE, maximum photochemical efficiency, non-photochemical quenching, relative water content and specific leaf area for both species. However, there was a decrease in leaf and soil element content. Different species exhibit varying adaptability to warming. Increasing temperature significantly increased the photosynthetic rate, stomatal conductance, transpiration rate, total water content, and specific leaf volume of E. nutans; however, all these traits exhibited an opposite trend in P. anserina. Warming has a direct negative impact on leaf LUE and an indirectly enhances LUE through its effects on leaf traits. The impact of warming on plant photosynthetic capacity is primarily mediated by soil nutrients and leaf traits. These results indicate that the two different species employ distinct adaptive strategies in response to climate change, which are related to their species-specific variations. Such changes can confer an adaptive advantage for plant to cope with environmental change and potentially lead to alterations to ecosystem structure and functioning.

An emergent constraint on the thermal sensitivity of photosynthesis and greenness in the high latitude northern forests

Despite the general consensus that the warming over the high latitudes northern forests (HLNF) has led to enhanced photosynthetic activity and contributed to the greening trend, isolating the impact of temperature increase on photosynthesis and greenness has been difficult due to the concurring influence of the CO2 fertilization effect. Here, using an ensemble of simulations from biogeochemical models that have contributed to the Trends in Net Land Atmosphere Carbon Exchange project (TRENDY), we identify an emergent relationship between the simulation of the climate-driven temporal changes in both gross primary productivity (GPP) and greenness (Leaf Area Index, LAI) and the model's spatial sensitivity of these quantities to growing-season (GS) temperature. Combined with spatially-resolved observations of LAI and GPP, we estimate that GS-LAI and GS-GPP increase by 17.0 ± 2.4% and 24.0 ± 3.0% per degree of warming, respectively. The observationally-derived sensitivities of LAI and GPP to temperature are about 40% and 71% higher, respectively, than the mean of the ensemble of simulations from TRENDY, primarily due to the model underestimation of the sensitivity of light use efficiency to temperature. We estimate that the regional mean GS-GPP increased 28.2 ± 5.1% between 1983-1986 and 2013-2016, much larger than the 5.8 ± 1.4% increase from the CO2 fertilization effect implied by Wenzel et al. This suggests that warming, not CO2 fertilization, is primarily responsible for the observed dramatic changes in the HLNF biosphere over the last century.

Diminishing carryover benefits of earlier spring vegetation growth

Spring vegetation growth can benefit summer growth by increasing foliage area and carbon sequestration potential, or impair it by consuming additional resources needed for sustaining subsequent growth. However, the prevalent driving mechanism and its temporal changes remain unknown. Using satellite observations and long-term atmospheric CO2 records, here we show a weakening trend of the linkage between spring and summer vegetation growth/productivity in the Northern Hemisphere during 1982-2021. This weakening is driven by warmer and more extreme hot weather that becomes unfavourable for peak-season growth, shifting peak plant functioning away from earlier periods. This is further exacerbated by seasonally growing ecosystem water stress due to reduced water supply and enhanced water demand. Our finding suggests that beneficial carryover effects of spring growth on summer growth are diminishing or even reversing, acting as an early warning sign of the ongoing shift of climatic effects from stimulating to suppressing plant photosynthesis during the early to peak seasons.

Cu-Based Materials for Enhanced C2+ Product Selectivity in Photo-/Electro-Catalytic CO2 Reduction: Challenges and Prospects

Carbon dioxide conversion into valuable products using photocatalysis and electrocatalysis is an effective approach to mitigate global environmental issues and the energy shortages. Among the materials utilized for catalytic reduction of CO2, Cu-based materials are highly advantageous owing to their widespread availability, cost-effectiveness, and environmental sustainability. Furthermore, Cu-based materials demonstrate interesting abilities in the adsorption and activation of carbon dioxide, allowing the formation of C2+ compounds through C-C coupling process. Herein, the basic principles of photocatalytic CO2 reduction reactions (PCO2RR) and electrocatalytic CO2 reduction reaction (ECO2RR) and the pathways for the generation C2+ products are introduced. This review categorizes Cu-based materials into different groups including Cu metal, Cu oxides, Cu alloys, and Cu SACs, Cu heterojunctions based on their catalytic applications. The relationship between the Cu surfaces and their efficiency in both PCO2RR and ECO2RR is emphasized. Through a review of recent studies on PCO2RR and ECO2RR using Cu-based catalysts, the focus is on understanding the underlying reasons for the enhanced selectivity toward C2+ products. Finally, the opportunities and challenges associated with Cu-based materials in the CO2 catalytic reduction applications are presented, along with research directions that can guide for the design of highly active and selective Cu-based materials for CO2 reduction processes in the future.

Wildfire-induced increases in photosynthesis in boreal forest ecosystems of North America

Observations of the annual cycle of atmospheric CO2 in high northern latitudes provide evidence for an increase in terrestrial metabolism in Arctic tundra and boreal forest ecosystems. However, the mechanisms driving these changes are not yet fully understood. One proposed hypothesis is that ecological change from disturbance, such as wildfire, could increase the magnitude and change the phase of net ecosystem exchange through shifts in plant community composition. Yet, little quantitative work has evaluated this potential mechanism at a regional scale. Here we investigate how fire disturbance influences landscape-level patterns of photosynthesis across western boreal North America. We use Alaska and Canadian large fire databases to identify the perimeters of wildfires, a Landsat-derived land cover time series to characterize plant functional types (PFTs), and solar-induced fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) as a proxy for photosynthesis. We analyze these datasets to characterize post-fire changes in plant succession and photosynthetic activity using a space-for-time approach. We find that increases in herbaceous and sparse vegetation, shrub, and deciduous broadleaf forest PFTs during mid-succession yield enhancements in SIF by 8-40% during June and July for 2- to 59-year stands relative to pre-fire controls. From the analysis of post-fire land cover changes within individual ecoregions and modeling, we identify two mechanisms by which fires contribute to long-term trends in SIF. First, increases in annual burning are shifting the stand age distribution, leading to increases in the abundance of shrubs and deciduous broadleaf forests that have considerably higher SIF during early- and mid-summer. Second, fire appears to facilitate a long-term shift from evergreen conifer to broadleaf deciduous forest in the Boreal Plain ecoregion. These findings suggest that increasing fire can contribute substantially to positive trends in seasonal CO2 exchange without a close coupling to long-term increases in carbon storage.

Temperature dependence of spring carbon uptake in northern high latitudes during the past four decades

In the northern high latitudes, warmer spring temperatures generally lead to earlier leaf onsets, higher vegetation production, and enhanced spring carbon uptake. Yet, whether this positive linkage has diminished under climate change remains debated. Here, we used atmospheric CO2 measurements at Barrow (Alaska) during 1979-2020 to investigate the strength of temperature dependence of spring carbon uptake reflected by two indicators, spring zero-crossing date (SZC) and CO2 drawdown (SCC). We found a fall and rise in the interannual correlation of temperature with SZC and SCC (RSZC-T and RSCC-T ), showing a recent reversal of the previously reported weakening trend of RSZC-T and RSCC-T . We used a terrestrial biosphere model coupled with an atmospheric transport model to reproduce this fall and rise phenomenon and conducted factorial simulations to explore its potential causes. We found that a strong-weak-strong spatial synchrony of spring temperature anomalies per se has contributed to the fall and rise trend in RSZC-T and RSCC-T , despite an overall unbroken temperature control on net ecosystem CO2 fluxes at local scale. Our results provide an alternative explanation for the apparent drop of RSZC-T and RSCC-T during the late 1990s and 2000s, and suggest a continued positive linkage between spring carbon uptake and temperature during the past four decades. We thus caution the interpretation of apparent climate sensitivities of carbon cycle retrieved from spatially aggregated signals.

Greening of human-dominated ecosystems in India

Satellite data show the Earth has been greening and identify croplands in India as one of the most prominent greening hotspots. Though India's agriculture has been dependent on irrigation enhancement to reduce crop water stress and increase production, the spatiotemporal dynamics of how irrigation influenced the satellite observed greenness remains unclear. Here, we use satellite-derived leaf area data and survey-based agricultural statistics together with results from state-of-the-art Land Surface Models (LSM) to investigate the role of irrigation in the greening of India's croplands. We find that satellite observations provide multiple lines of evidence showing strong contributions of irrigation to significant greening during dry season and in drier environments. The national statistics support irrigation-driven yield enhancement and increased dry season cropping intensity. These suggest a continuous shift in India's agriculture toward an irrigation-driven dry season cropping system and confirm the importance of land management in the greening phenomenon. However, the LSMs identify CO2 fertilization as a primary driver of greening whereas land use and management have marginal impacts on the simulated leaf area changes. This finding urges a closer collaboration of the modeling, Earth observation, and land system science communities to improve representation of land management in the Earth system modeling.

Higher global gross primary productivity under future climate with more advanced representations of photosynthesis

Gross primary productivity (GPP) is the key determinant of land carbon uptake, but its representation in terrestrial biosphere models (TBMs) does not reflect our latest physiological understanding. We implemented three empirically well supported but often omitted mechanisms into the TBM CABLE-POP: photosynthetic temperature acclimation, explicit mesophyll conductance, and photosynthetic optimization through redistribution of leaf nitrogen. We used the RCP8.5 climate scenario to conduct factorial model simulations characterizing the individual and combined effects of the three mechanisms on projections of GPP. Simulated global GPP increased more strongly (up to 20% by 2070-2099) in more comprehensive representations of photosynthesis compared to the model lacking the three mechanisms. The experiments revealed non-additive interactions among the mechanisms as combined effects were stronger than the sum of the individual effects. The modeled responses are explained by changes in the photosynthetic sensitivity to temperature and CO2 caused by the added mechanisms. Our results suggest that current TBMs underestimate GPP responses to future CO2 and climate conditions.

Raman spectral characteristics of 12CO2/13CO2 and quantitative measurements of carbon isotopic compositions from 50 to 450 °C and 50 to 400 bar

The carbon isotopic composition of CO₂ is traced to its different origins and widely used in the fields of geology, biology, and chemistry. Raman spectroscopy can be performed in situ, is nondestructive, and requires no sample preparation; these characteristics enable Raman spectroscopy to be considered a new alternative method to measure the carbon isotopic composition of CO₂. In this work, Raman spectra of high-purity ¹³CO₂, ¹²CO₂, and six ¹²CO₂-¹³CO₂ binary mixtures with known mixing ratios were collected using a High Pressure Optical Cell (HPOC) at 50-450 °C and 50-400 bar. The results showed that the characteristic peak positions of both ¹³CO₂ and ¹²CO₂ shift to lower wavenumbers with increasing temperature and decreasing pressure, but the peak positions of ¹³CO₂ show a larger shift. The peak position difference of the corresponding characteristic peaks between ¹³CO₂ and ¹²CO₂ is greater than 15 cm^-1 under the above temperatures and pressures, and the peaks can be distinguished. However, ν_-¹³ overlays ν_H.B.¹² near 1265 cm^-1, ν₊¹² overlaps ν_H.B.¹³ near 1288 cm^-1. The existence of ¹³CO₂ can cause a change in the Fermi diad splitting of ¹²CO₂ and affect the establishment of CO₂ Raman densimeters. The positive correlation obtained between the peak intensity ratio and the content ratio is affected by temperature, pressure, and ¹³CO₂ content. I₊¹³/I₊¹² and I_-¹³/I_-¹² were selected as the quantitative indices to establish Raman quantitative analysis models for the determination of the carbon isotopic composition of CO₂, which can be applied to in-situ measurements of high-temperature and high-pressure systems.

From remotely-sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II-Harnessing data

Although our observing capabilities of solar-induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in-situ SIF observing capability especially in "data desert" regions, improving cross-instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.

Increasing temperature regulates the advance of peak photosynthesis timing in the boreal ecosystem

The shift in vegetation phenology is an essential indicator of global climate change. Numerous researches based on reflectance-based vegetation index data have explored the changes in the start (SOS) and end (EOS) of vegetation life events at long time scales, while a huge discrepancy existed between the phenological metrics of vegetation structure and function. The peak photosynthesis timing (PPT), which is crucial in regulating terrestrial ecosystem carbon balance, has not received much attention. Using two global reconstructed solar-induced chlorophyll fluorescence data (CSIF and GOSIF) directly associated with vegetation photosynthesis, the spatio-temporal dynamics in PPT as well as the key environmental controls across the boreal ecosystem during 2001-2019 were systematically explored. Multi-year mean pattern showed that PPT mainly appeared in the first half of July. Compared to the northern Eurasia, later PPT appeared in the northern North America continent for about 4-5 days. Meanwhile, spatial trend in PPT exhibited an advanced trend during the last two decades. Especially, shrubland and grassland were obvious among all biomes. Spatial partial correlation analysis revealed that preseason temperature was the dominant environmental driver of PPT trends, occupying 81.32% and 78.04% of the total pixels of PPT_CSIF and PPT_GOSIF, respectively. Attribution analysis by ridge regression again emphasized the largest contribution of temperature to PPT dynamics in the boreal ecosystem by 52.22% (PPT_CSIF) and 46.59% (PPT_GOSIF), followed by radiation (PPT_CSIF: 24.44%; PPT_GOSIF: 28.66%) and precipitation (PPT_CSIF: 23.34%; PPT_GOSIF: 24.75%). These results have significant implications for deepening our understanding between vegetation photosynthetic phenology and carbon cycling with respect to future climate change in the boreal ecosystem.

Advanced Photocatalysts for CO2 Conversion by Severe Plastic Deformation (SPD)

Excessive CO2 emission from fossil fuel usage has resulted in global warming and environmental crises. To solve this problem, the photocatalytic conversion of CO2 to CO or useful components is a new strategy that has received significant attention. The main challenge in this regard is exploring photocatalysts with high efficiency for CO2 photoreduction. Severe plastic deformation (SPD) through the high-pressure torsion (HPT) process has been effectively used in recent years to develop novel active catalysts for CO2 conversion. These active photocatalysts have been designed based on four main strategies: (i) oxygen vacancy and strain engineering, (ii) stabilization of high-pressure phases, (iii) synthesis of defective high-entropy oxides, and (iv) synthesis of low-bandgap high-entropy oxynitrides. These strategies can enhance the photocatalytic efficiency compared with conventional and benchmark photocatalysts by improving CO2 adsorption, increasing light absorbance, aligning the band structure, narrowing the bandgap, accelerating the charge carrier migration, suppressing the recombination rate of electrons and holes, and providing active sites for photocatalytic reactions. This article reviews recent progress in the application of SPD to develop functional ceramics for photocatalytic CO2 conversion.

Engineering the Charge Density on an In2.77S4/Porous Organic Polymer Hybrid Photocatalyst for CO2-to-Ethylene Conversion Reaction

The development of an efficient photocatalyst for C2 product formation from CO₂ is of urgent importance toward the deployment of solar-fuel production. Here, we report a template-free, cost-effective synthetic strategy to develop a carbazole-derived porous organic polymer (POP)-based composite catalyst. The composite catalyst is comprised of In_2.77S₄ and porous organic polymer (POP) and is held together by induced-polarity-driven electrostatic interaction. Utilizing the synergy of the catalytically active In centers and light-harvesting POPs, the catalyst showed 98.9% selectivity toward the generation of C₂H₄, with a formation rate of 67.65 μmol g^-1 h^-1. Two different oxidation states of the In_2.77S₄ spinel were exploited for the C-C coupling process, and this was investigated by X-ray photoelectron spectroscopy (XPS), X-ray absorption spectroscopy (XAS), and density functional theory (DFT) calculations. The role of POP was elucidated via several photophysical and photoelectrochemical studies. The electron transfer was mapped by several correlated approaches, which assisted in establishing the Z-scheme mechanism. Furthermore, the mechanism of C₂H₄ formation was extensively investigated using density functional theory (DFT) calculations from multiple possible pathways.

Enhance seasonal amplitude of atmospheric CO2 by the changing Southern Ocean carbon sink

The enhanced seasonal amplitude of atmospheric CO₂ has been viewed so far primarily as a Northern Hemisphere phenomenon. Yet, analyses of atmospheric CO₂ records from 49 stations between 1980 and 2018 reveal substantial trends and variations in this amplitude globally. While no significant trends can be discerned before 2000 in most places, strong positive trends emerge after 2000 in the southern high latitudes. Using factorial simulations with an atmospheric transport model and analyses of surface ocean Pco₂ observations, we show that the increase is best explained by the onset of increasing seasonality of air-sea CO₂ exchange over the Southern Ocean around 2000. Underlying these changes is the long-term ocean acidification trend that tends to enhance the seasonality of the air-sea fluxes, but this trend is modified by the decadal variability of the Southern Ocean carbon sink. The seasonal variations of atmospheric CO₂ thus emerge as a sensitive recorder of the variations of the Southern Ocean carbon sink.

Respiratory loss during late-growing season determines the net carbon dioxide sink in northern permafrost regions

Warming of northern high latitude regions (NHL, > 50 °N) has increased both photosynthesis and respiration which results in considerable uncertainty regarding the net carbon dioxide (CO₂) balance of NHL ecosystems. Using estimates constrained from atmospheric observations from 1980 to 2017, we find that the increasing trends of net CO₂ uptake in the early-growing season are of similar magnitude across the tree cover gradient in the NHL. However, the trend of respiratory CO₂ loss during late-growing season increases significantly with increasing tree cover, offsetting a larger fraction of photosynthetic CO₂ uptake, and thus resulting in a slower rate of increasing annual net CO₂ uptake in areas with higher tree cover, especially in central and southern boreal forest regions. The magnitude of this seasonal compensation effect explains the difference in net CO₂ uptake trends along the NHL vegetation- permafrost gradient. Such seasonal compensation dynamics are not captured by dynamic global vegetation models, which simulate weaker respiration control on carbon exchange during the late-growing season, and thus calls into question projections of increasing net CO₂ uptake as high latitude ecosystems respond to warming climate conditions.

The northern high latitude permafrost region has been an important contributor to the carbon sink since the 1980s. A new study finds that as tree cover increases, respiratory CO2 loss during late-growing season offsets photosynthetic CO2 uptake and leads to a slower rate of increasing annual net CO2 uptake.

Carbon exchange characteristics and their environmental effects in the northern forest ecosystem of the Greater Khingan Mountains in China

Measurement and analysis of CO₂ concentration at the ecosystem scale is the basis for studying ecosystem feedback to global climate change, and it is particularly useful for understanding the processes and mechanisms of ecosystem C exchange. Through observation of CO₂ concentration at different heights, this study examined whether a CO₂ lake phenomenon exists in the Larix gmelinii ecosystem of the Greater Khingan Mountains (China), and how it might be changed and what might represent its driving factors if such a phenomenon were found to exist. Plants and soils were sampled regularly to determine δ¹³C and to quantify the proportion of C released by each component of the ecosystem. The main path of C release and the main source of CO₂ lake formation were investigated. Statistical analysis revealed that a CO₂ lake phenomenon does exist in the L. gmelinii ecosystem. Comparative analysis showed that on the daily scale, when the ecosystem was a C source, the CO₂ lake phenomenon often occurred. On the scale of the growing season, the strongest CO₂ lake was accompanied by emergence of the peak respiratory flux. Stepwise regression analysis showed that environmental factors could explain 74.87% of the CO₂ lake phenomenon. The occurrence and strength of the CO₂ lakes were found to mainly respond to changes in temperature. Linear model analysis revealed that the rate of C release from autotrophic respiration in the forest was 51.18%; the rate of C release from heterotrophic respiration during litter decomposition was 51.78%. Therefore, the C release of the L. gmelinii ecosystem is mainly from autotrophic respiration. The CO₂ released during decomposition of litter represented the main source for the formation of CO₂ lakes. The CO₂ lake effect has substantial impact on the net C flux and plays an important role in the C source/sink effect of the ecosystem.

Quantifying Northern High Latitude Gross Primary Productivity (GPP) Using Carbonyl Sulfide (OCS)

The northern high latitude (NHL, 40°N to 90°N) is where the second peak region of gross primary productivity (GPP) other than the tropics. The summer NHL GPP is about 80% of the tropical peak, but both regions are still highly uncertain (Norton et al. 2019, https://doi.org/10.5194/bg-16-3069-2019). Carbonyl sulfide (OCS) provides an important proxy for photosynthetic carbon uptake. Here we optimize the OCS plant uptake fluxes across the NHL by fitting atmospheric concentration simulation with the GEOS-CHEM global transport model to the aircraft profiles acquired over Alaska during NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (2012-2015). We use the empirical biome-specific linear relationship between OCS plant uptake flux and GPP to derive the six plant uptake OCS fluxes from different GPP data. Such GPP-based fluxes are used to drive the concentration simulations. We evaluate the simulations against the independent observations at two ground sites of Alaska. The optimized OCS fluxes suggest the NHL plant uptake OCS flux of -247 Gg S year-1, about 25% stronger than the ensemble mean of the six GPP-based OCS fluxes. GPP-based OCS fluxes systematically underestimate the peak growing season across the NHL, while a subset of models predict early start of season in Alaska, consistent with previous studies of net ecosystem exchange. The OCS optimized GPP of 34 PgC yr-1 for NHL is also about 25% more than the ensembles mean from six GPP data. Further work is needed to fully understand the environmental and biotic drivers and quantify their rate of photosynthetic carbon uptake in Arctic ecosystems.

Process-oriented analysis of dominant sources of uncertainty in the land carbon sink

The observed global net land carbon sink is captured by current land models. All models agree that atmospheric CO₂ and nitrogen deposition driven gains in carbon stocks are partially offset by climate and land-use and land-cover change (LULCC) losses. However, there is a lack of consensus in the partitioning of the sink between vegetation and soil, where models do not even agree on the direction of change in carbon stocks over the past 60 years. This uncertainty is driven by plant productivity, allocation, and turnover response to atmospheric CO₂ (and to a smaller extent to LULCC), and the response of soil to LULCC (and to a lesser extent climate). Overall, differences in turnover explain ~70% of model spread in both vegetation and soil carbon changes. Further analysis of internal plant and soil (individual pools) cycling is needed to reduce uncertainty in the controlling processes behind the global land carbon sink.

The global net land sink is relatively well constrained. However, the responsible drivers and above/below-ground partitioning are highly uncertain. Model issues regarding turnover of individual plant and soil components are responsible.

Re-assessment of the climatic controls on the carbon and water fluxes of a boreal aspen forest over 1996-2016: Changing sensitivity to long-term climatic conditions

Recent evidence suggests that the relationships between climate and boreal tree growth are generally non-stationary; however, it remains uncertain whether the relationships between climate and carbon (C) fluxes of boreal forests are stationary or have changed over recent decades. In this study, we used continuous eddy-covariance and microclimate data over 21 years (1996-2016) from a 100-year-old trembling aspen stand in central Saskatchewan, Canada to assess the relationships between climate and ecosystem C and water fluxes. Over the study period, the most striking climatic event was a severe, 3-year drought (2001-2003). Gross ecosystem production (GEP) showed larger interannual variability than ecosystem respiration (R_e ) over 1996-2016, but R_e was the dominant component contributing to the interannual variation in net ecosystem production (NEP) during post-drought years. The interannual variations in evapotranspiration (ET) and C fluxes were primarily driven by temperature and secondarily by water availability. Two-factor linear models combining precipitation and temperature performed well in explaining the interannual variation in C and water fluxes (R²  > .5). The temperature sensitivities of all three C fluxes (NEP, GEP and R_e ) declined over the study period (p < .05), and, as a result, the phenological controls on annual NEP weakened. The decreasing temperature sensitivity of the C fluxes may reflect changes in forest structure, related to the over-maturity of the aspen stand at 100 years of age, and exacerbated by high tree mortality following the severe 2001-2003 drought. These results may provide an early warning signal of driver shift or even an abrupt status shift of aspen forest dynamics. They may also imply a universal weakening in the relationship between temperature and GEP as forests become over-mature, associated with the structural and compositional changes that accompany forest ageing.

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.

Impact of Changing Winds on the Mauna Loa CO2 Seasonal Cycle in Relation to the Pacific Decadal Oscillation

Long-term measurements at the Mauna Loa Observatory (MLO) show that the CO₂ seasonal cycle amplitude (SCA) increased from 1959 to 2019 at an overall rate of 0.22  ±  0.034 ppm decade^-1 while also varying on interannual to decadal time scales. These SCA changes are a signature of changes in land ecological CO₂ fluxes as well as shifting winds. Simulations with the TM3 tracer transport model and CO₂ fluxes from the Jena CarboScope CO₂ Inversion suggest that shifting winds alone have contributed to a decrease in SCA of -0.10  ±  0.022 ppm decade^-1 from 1959 to 2019, partly offsetting the observed long-term SCA increase associated with enhanced ecosystem net primary production. According to these simulations and MIROC-ACTM simulations, the shorter-term variability of MLO SCA is nearly equally driven by varying ecological CO₂ fluxes (49%) and varying winds (51%). We also show that the MLO SCA is strongly correlated with the Pacific Decadal Oscillation (PDO) due to varying winds, as well as with a closely related wind index (U-PDO). Since 1980, 44% of the wind-driven SCA decrease has been tied to a secular trend in the U-PDO, which is associated with a progressive weakening of westerly winds at 700 mbar over the central Pacific from 20°N to 40°N. Similar impacts of varying winds on the SCA are seen in simulations at other low-latitude Pacific stations, illustrating the difficulty of constraining trend and variability of land CO₂ fluxes using observations from low latitudes due to the complexity of circulation changes.

The Sensitivity of Vegetation Dynamics to Climate Change across the Tibetan Plateau

Vegetation dynamics are key processes which present the ecology system’s response to climate change. However, vegetation sensitivity to climate change remains controversial. This study redefined vegetation sensitivity to precipitation (VSP) and vegetation sensitivity to temperature (VST) by the coefficient of determination (R2) obtained by a linear regression analysis between climate and the normalized difference vegetation index (NDVI), as well as by using an analysis of variance to explore the significant differences between them in different seasons from 1982 to 2013, and exploring the general changed rules of VSP/VST on a timescale. Moreover, the variations in VSP and VST across the Tibetan Plateau were plotted by regression analysis. Finally, we used structural equation modeling (SEM) to verify the hypothesis that the respondence of VSP and VST to the NDVI was regulated by the hydrothermal conditions. Our results showed that: (1) the annual VSP increased in both spring and winter (R2 = 0.32, p < 0.001; R2 = 0.25, p < 0.001, respectively), while the annual VST decreased in summer (R2 = 0.21, p < 0.001); (2) the threshold conditions of seasonal VSP and seasonal VST were captured in the 4–12 mm range (monthly precipitation) and at 0 °C (monthly average temperature), respectively; (3) the SEM demonstrated that climate change has significant direct effects on VSP only in spring and winter and on VST only in summer (path coefficient of −0.554, 0.478, and −0.428, respectively). In summary, our findings highlighted that climate change under these threshold conditions would lead to a variation in the sensitivity of the NDVI to seasonal precipitation and temperature.

Satellite observations document trends consistent with a boreal forest biome shift

The boreal forest biome is a major component of Earth's biosphere and climate system that is projected to shift northward due to continued climate change over the coming century. Indicators of a biome shift will likely first be evident along the climatic margins of the boreal forest and include changes in vegetation productivity, mortality, and recruitment, as well as overall vegetation greenness. However, the extent to which a biome shift is already underway remains unclear because of the local nature of most field studies, sparsity of systematic ground-based ecological monitoring, and reliance on coarse resolution satellite observations. Here, we evaluated early indicators of a boreal forest biome shift using four decades of moderate resolution (30 m) satellite observations and biogeoclimatic spatial datasets. Specifically, we quantified interannual trends in annual maximum vegetation greenness using an ensemble of vegetation indices derived from Landsat observations at 100,000 sample sites in areas without signs of recent disturbance. We found vegetation greenness increased (greened) at 38 [29, 42] % and 22 [15, 26] % of sample sites from 1985 to 2019 and 2000 to 2019, whereas vegetation greenness decreased (browned) at 13 [9, 15] % and 15 [13, 19] % of sample sites during these respective periods [95% Monte Carlo confidence intervals]. Greening was thus 3.0 [2.6, 3.5] and 1.5 [0.8, 2.0] times more common than browning and primarily occurred in cold sparsely treed areas with high soil nitrogen and moderate summer warming. Conversely, browning primarily occurred in the climatically warmest margins of both the boreal forest biome and major forest types (e.g., evergreen conifer forests), especially in densely treed areas where summers became warmer and drier. These macroecological trends reflect underlying shifts in vegetation productivity, mortality, and recruitment that are consistent with early stages of a boreal biome shift.

Outlier Reconstruction of NDVI for Vegetation-Cover Dynamic Analyses

The normalized difference vegetation index (NDVI) contains important data for providing vegetation-cover information and supporting environmental analyses. However, understanding long-term vegetation cover dynamics remains challenging due to data outliers that are found in cloudy regions. In this article, we propose a sliding-window-based tensor stream analysis algorithm (SWTSA) for reconstructing outliers in NDVI from multitemporal optical remote-sensing images. First, we constructed a tensor stream of NDVI that was calculated from clear-sky optical remote-sensing images corresponding to seasons on the basis of the acquired date. Second, we conducted tensor decomposition and reconstruction by SWTSA. Landsat series remote-sensing images were used in experiments to demonstrate the applicability of the SWTSA. Experiments were carried out successfully on the basis of data from the estuary area of Salween River in Southeast Asia. Compared with random forest regression (RFR), SWTSA has higher accuracy and better reconstruction capabilities. Results show that SWTSA is reliable and suitable for reconstructing outliers of NDVI from multitemporal optical remote-sensing images.

Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios

Increases in atmospheric carbon dioxide (CO₂) concentrations is the main driver of global warming due to fossil fuel combustion. Satellite observations provide continuous global CO₂ retrieval products, that reveal the nonuniform distributions of atmospheric CO₂ concentrations. However, climate simulation studies are almost based on a globally uniform mean or latitudinally resolved CO₂ concentrations assumption. In this study, we reconstructed the historical global monthly distributions of atmospheric CO₂ concentrations with 1° resolution from 1850 to 2013 which are based on the historical monthly and latitudinally resolved CO₂ concentrations accounting longitudinal features retrieved from fossil-fuel CO₂ emissions from Carbon Dioxide Information Analysis Center. And the spatial distributions of nonuniform CO₂ under Shared Socio-economic Pathways and Representative Concentration Pathways scenarios were generated based on the spatial, seasonal and interannual scales of the current CO₂ concentrations from 2015 to 2150. Including the heterogenous CO₂ distributions could enhance the realism of global climate modeling, to better anticipate the potential socio-economic implications, adaptation practices, and mitigation of climate change.

Reducing model uncertainty of climate change impacts on high latitude carbon assimilation

The Arctic-Boreal Region (ABR) has a large impact on global vegetation-atmosphere interactions and is experiencing markedly greater warming than the rest of the planet, a trend that is projected to continue with anticipated future emissions of CO₂ . The ABR is a significant source of uncertainty in estimates of carbon uptake in terrestrial biosphere models such that reducing this uncertainty is critical for more accurately estimating global carbon cycling and understanding the response of the region to global change. Process representation and parameterization associated with gross primary productivity (GPP) drives a large amount of this model uncertainty, particularly within the next 50 years, where the response of existing vegetation to climate change will dominate estimates of GPP for the region. Here we review our current understanding and model representation of GPP in northern latitudes, focusing on vegetation composition, phenology, and physiology, and consider how climate change alters these three components. We highlight challenges in the ABR for predicting GPP, but also focus on the unique opportunities for advancing knowledge and model representation, particularly through the combination of remote sensing and traditional boots-on-the-ground science.

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 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.

Enhancement of ecosystem carbon uptake in a dry shrubland under moderate warming: The role of nitrogen-driven changes in plant morphology

Net ecosystem CO₂ exchange is the result of net carbon uptake by plant photosynthesis and carbon loss by soil and plant respiration. Temperature increases due to climate change can modify the equilibrium between these fluxes and trigger ecosystem-climate feedbacks that can accelerate climate warming. As these dynamics have not been well studied in dry shrublands, we subjected a Mediterranean shrubland to a 10-year night-time temperature manipulation experiment that analyzed ecosystem carbon fluxes associated with dominant shrub species, together with several plant parameters related to leaf photosynthesis, leaf morphology, and canopy structure. Under moderate night-time warming (+0.9°C minimum daily temperature, no significant reduction in soil moisture), Cistus monspeliensis formed shoots with more leaves that were relatively larger and denser canopies that supported higher plant-level photosynthesis rates. Given that ecosystem respiration was not affected, this change in canopy morphology led to a significant enhancement in net ecosystem exchange (+47% at midday). The observed changes in shoot and canopy morphology were attributed to the improved nutritional state of the warmed plants, primarily due to changes in nitrogen cycling and higher nitrogen resorption efficiency in senescent leaves. Our results show that modifications in plant morphology triggered by moderate warming affected ecosystem CO₂  fluxes, providing the first evidence for enhanced daytime carbon uptake in a dry shrubland ecosystem under experimental warming.

Growth-defense trade-offs shape population genetic composition in an iconic forest tree species

All organisms experience fundamental conflicts between divergent metabolic processes. In plants, a pivotal conflict occurs between allocation to growth, which accelerates resource acquisition, and to defense, which protects existing tissue against herbivory. Trade-offs between growth and defense traits are not universally observed, and a central prediction of plant evolutionary ecology is that context-dependence of these trade-offs contributes to the maintenance of intraspecific variation in defense [Züst and Agrawal, Annu. Rev. Plant Biol., 68, 513-534 (2017)]. This prediction has rarely been tested, however, and the evolutionary consequences of growth-defense trade-offs in different environments are poorly understood, especially in long-lived species [Cipollini et al., Annual Plant Reviews (Wiley, 2014), pp. 263-307]. Here we show that intraspecific trait trade-offs, even when fixed across divergent environments, interact with competition to drive natural selection of tree genotypes corresponding to their growth-defense phenotypes. Our results show that a functional trait trade-off, when coupled with environmental variation, causes real-time divergence in the genetic architecture of tree populations in an experimental setting. Specifically, competitive selection for faster growth resulted in dominance by fast-growing tree genotypes that were poorly defended against natural enemies. This outcome is a signature example of eco-evolutionary dynamics: Competitive interactions affected microevolutionary trajectories on a timescale relevant to subsequent ecological interactions [Brunner et al., Funct. Ecol. 33, 7-12 (2019)]. Eco-evolutionary drivers of tree growth and defense are thus critical to stand-level trait variation, which structures communities and ecosystems over expansive spatiotemporal scales.

Efficient Hole Trapping in Carbon Dot/Oxygen-Modified Carbon Nitride Heterojunction Photocatalysts for Enhanced Methanol Production from CO2 under Neutral Conditions

Artificial photosynthesis of alcohols from CO2 is still unsatisfactory owing to the rapid charge relaxation compared to the sluggish photoreactions and the oxidation of alcohol products. Here, we demonstrate that CO2 is reduced to methanol with 100 % selectivity using water as the only electron donor on a carbon nitride-like polymer (FAT) decorated with carbon dots. The quantum efficiency of 5.9 % (λ=420 nm) is 300 % higher than the previously reported carbon nitride junction. Using transient absorption spectroscopy, we observed that holes in FAT could be extracted by the carbon dots with nearly 75 % efficiency before they become unreactive by trapping. Extraction of holes resulted in a greater density of photoelectrons, indicative of reduced recombination of shorter-lived reactive electrons. This work offers a strategy to promote photocatalysis by increasing the amount of reactive photogenerated charges via structure engineering and extraction before energy losses by deep trapping.

BVOC Emissions From a Subarctic Ecosystem, as Controlled by Insect Herbivore Pressure and Temperature

Abstract

The biogenic volatile organic compounds, BVOCs have a central role in ecosystem–atmosphere interactions. High-latitude ecosystems are facing increasing temperatures and insect herbivore pressure, which may affect their BVOC emission rates, but evidence and predictions of changes remain scattered. We studied the long-term effects of + 3 °C warming and reduced insect herbivory (achieved through insecticide sprayings) on mid- and late summer BVOC emissions from field layer vegetation, supplemented with birch saplings, and the underlying soil in Subarctic mountain birch forest in Finland in 2017–2018. Reduced insect herbivory decreased leaf damage by 58–67% and total ecosystem BVOC emissions by 44–72%. Of the BVOC groups, total sesquiterpenes had 70–80% lower emissions with reduced herbivory, and in 2017 the decrease was greater in warmed plots (89% decrease) than in ambient plots (34% decrease). While non-standardized total BVOC, monoterpene, sesquiterpene and GLV emissions showed instant positive responses to increasing chamber air temperature in midsummer samplings, the long-term warming treatment effects on standardized emissions mainly appeared as changes in the compound structure of BVOC blends and varied with compounds and sampling times. Our results suggest that the effects of climate warming on the total quantity of BVOC emissions will in Subarctic ecosystems be, over and above the instant temperature effects, mediated through changes in insect herbivore pressure rather than plant growth. If insect herbivore numbers will increase as predicted under climate warming, our results forecast herbivory-induced increases in the quantity of Subarctic BVOC emissions.

Graphic Abstract

COS-derived GPP relationships with temperature and light help explain high-latitude atmospheric CO2 seasonal cycle amplification

In the Arctic and Boreal region (ABR) where warming is especially pronounced, the increase of gross primary production (GPP) has been suggested as an important driver for the increase of the atmospheric CO₂ seasonal cycle amplitude (SCA). However, the role of GPP relative to changes in ecosystem respiration (ER) remains unclear, largely due to our inability to quantify these gross fluxes on regional scales. Here, we use atmospheric carbonyl sulfide (COS) measurements to provide observation-based estimates of GPP over the North American ABR. Our annual GPP estimate is 3.6 (2.4 to 5.5) PgC · y^-1 between 2009 and 2013, the uncertainty of which is smaller than the range of GPP estimated from terrestrial ecosystem models (1.5 to 9.8 PgC · y^-1). Our COS-derived monthly GPP shows significant correlations in space and time with satellite-based GPP proxies, solar-induced chlorophyll fluorescence, and near-infrared reflectance of vegetation. Furthermore, the derived monthly GPP displays two different linear relationships with soil temperature in spring versus autumn, whereas the relationship between monthly ER and soil temperature is best described by a single quadratic relationship throughout the year. In spring to midsummer, when GPP is most strongly correlated with soil temperature, our results suggest the warming-induced increases of GPP likely exceeded the increases of ER over the past four decades. In autumn, however, increases of ER were likely greater than GPP due to light limitations on GPP, thereby enhancing autumn net carbon emissions. Both effects have likely contributed to the atmospheric CO₂ SCA amplification observed in the ABR.

Unusual characteristics of the carbon cycle during the 2015-2016 El Niño

The 2015-2016 El Niño was one of the strongest on record, but its influence on the carbon balance is less clear. Using Northern Hemisphere atmospheric CO₂ observations, we found both detrended atmospheric CO₂ growth rate (CGR) and CO₂ seasonal-cycle amplitude (SCA) of 2015-2016 were much higher than that of other El Niño events. The simultaneous high CGR and SCA were unusual, because our analysis of long-term CO₂ observations at Mauna Loa revealed a significantly negative correlation between CGR and SCA. Atmospheric inversions and terrestrial ecosystem models indicate strong northern land carbon uptake during spring but substantially reduced carbon uptake (or high emissions) during early autumn, which amplified SCA but also resulted in a small anomaly in annual carbon uptake of northern ecosystems in 2015-2016. This negative ecosystem carbon uptake anomaly in early autumn was primarily due to soil water deficits and more litter decomposition caused by enhanced spring productivity. Our study demonstrates a decoupling between seasonality and annual carbon cycle balance in northern ecosystems over 2015-2016, which is unprecedented in the past five decades of El Niño events.

High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data

Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

Environmental quality and output volatility: the case of South Asian economies

This study explores the impact of environmental degradation on output volatility for eight South Asian economies over the time span 1971-2017. Environmental degradation is measured by CO2 emissions, nitrous oxide (N2O), methane emissions (CH4), greenhouse gas emissions (GHG), and environmental pollutants index (EPI), whereas output volatility is constructed using a rolling window of five-year moving standard deviation. The results of cross-sectional dependence (CSD) tests indicate the presence of CSD among South Asian economies. For empirical analysis, second-generation panel time series approaches are employed. Also, the findings of panel unit root tests (URTs) signify that the variables are stationary at the first difference and have a long-run relationship. Westerlund cointegration test is used to assess the long-run relationship among the variables. Moreover, this study has used a fully modified ordinary least square (FMOLS) and dynamic modified ordinary least square (DOLS) methods to examine the relationship between environmental degradation and output volatility. In the long run, all indicators of environmental degradation are positive and significant signaling the harmful effects of environmental degradation on output volatility. However, the impact of nitrous oxide is larger relative to other indicators used in the study. The outcome, therefore, suggests that promoting clean investment in nitric acid plants might help improve the environmental quality in the region which in turn fosters the process of economic stability.

Ancient plant DNA reveals High Arctic greening during the Last Interglacial

Summer warming is driving a greening trend across the Arctic, with the potential for large-scale amplification of climate change due to vegetation-related feedbacks [Pearson et al., Nat. Clim. Chang. (3), 673-677 (2013)]. Because observational records are sparse and temporally limited, past episodes of Arctic warming can help elucidate the magnitude of vegetation response to temperature change. The Last Interglacial ([LIG], 129,000 to 116,000 y ago) was the most recent episode of Arctic warming on par with predicted 21st century temperature change [Otto-Bliesner et al., Philos. Trans. A Math. Phys. Eng. Sci. (371), 20130097 (2013) and Post et al., SciAdv (5), eaaw9883 (2019)]. However, high-latitude terrestrial records from this period are rare, so LIG vegetation distributions are incompletely known. Pollen-based vegetation reconstructions can be biased by long-distance pollen transport, further obscuring the paleoenvironmental record. Here, we present a LIG vegetation record based on ancient DNA in lake sediment and compare it with fossil pollen. Comprehensive plant community reconstructions through the last and current interglacial (the Holocene) on Baffin Island, Arctic Canada, reveal coherent climate-driven community shifts across both interglacials. Peak LIG warmth featured a ∼400-km northward range shift of dwarf birch, a key woody shrub that is again expanding northward. Greening of the High Arctic-documented here by multiple proxies-likely represented a strong positive feedback on high-latitude LIG warming. Authenticated ancient DNA from this lake sediment also extends the useful preservation window for the technique and highlights the utility of combining traditional and molecular approaches for gleaning paleoenvironmental insights to better anticipate a warmer future.

Disentangling the Regional Climate Impacts of Competing Vegetation Responses to Elevated Atmospheric CO2

Biophysical vegetation responses to elevated atmospheric carbon dioxide (CO2) affect regional hydroclimate through two competing mechanisms. Higher CO2 increases leaf area (LAI), thereby increasing transpiration and water losses. Simultaneously, elevated CO2 reduces stomatal conductance and transpiration, thereby increasing rootzone soil moisture. Which mechanism dominates in the future is highly uncertain, partly because these two processes are difficult to explicitly separate within dynamic vegetation models. We address this challenge by using the GISS ModelE global climate model to conduct a novel set of idealized 2×CO2 sensitivity experiments to: evaluate the total vegetation biophysical contribution to regional climate change under high CO2; and quantify the separate contributions of enhanced LAI and reduced stomatal conductance to regional hydroclimate responses. We find that increased LAI exacerbates soil moisture deficits across the sub-tropics and more water-limited regions, but also attenuates warming by ∼0.5-1°C in the US Southwest, Central Asia, Southeast Asia, and northern South America. Reduced stomatal conductance effects contribute ∼1°C of summertime warming. For some regions, enhanced LAI and reduced stomatal conductance produce nonlinear and either competing or mutually amplifying hydroclimate responses. In northeastern Australia, these effects combine to exacerbate radiation-forced warming and contribute to year-round water limitation. Conversely, at higher latitudes these combined effects result in less warming than would otherwise be predicted due to nonlinear responses. These results highlight substantial regional variation in CO2-driven vegetation responses and the importance of improving model representations of these processes to better quantify regional hydroclimate impacts.

Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2

Atmospheric carbon dioxide concentration ([CO₂ ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO₂ ] increase and thus climate change. However, ecosystem CO₂ responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO₂ ]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO₂ ] (iCO₂ ) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO₂ is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO₂ responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO₂ responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO₂ , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.

Carbon sequestration and storage in Norwegian Arctic coastal wetlands: Impacts of climate change

Coastal wetlands contain some of the largest stores of pedologic and biotic carbon pools, and climate change is likely to influence the ability of these ecosystems to sequester carbon. Recent studies have attempted to provide data on carbon sequestration in both temperate and tropical coastal wetlands. Alteration of Arctic wetland carbon sequestration rates is also likely where coastal forcing mechanisms interact directly with these coastal systems. At present there are no data available to provide a detailed understanding of present day and historical carbon sequestration rates within Arctic coastal wetlands. In order to address this knowledge gap, rates of carbon sequestration were assessed within five Arctic coastal wetland sites in Norway. This was undertaken using radiometric dating techniques (²¹⁰Pb and ¹³⁷Cs) to establish a geochronology for recent wetland development, and soil carbon stocks were estimated from cores. Average carbon sequestration rates were varied, both between sites and over time, ranging between 19 and 603 g C m² y^-1, and these were correlated with increases in the length of the growing season. Stocks ranged between 3.67 and 13.79 Mg C ha^-1, which is very low compared with global average estimations for similar coastal systems, e.g. 250 Mg C ha^-1 for temperate salt marshes, 280 Mg C ha^-1 for mangroves, and 140 Mg C ha^-1 for seagrasses. This is most likely due to isostatic uplift and sediment accretion historically outpacing sea level rise, which results in wetland progradation and thus a continuous formation of new marsh with thin organic soil horizons. However, with increasing rates of sea level rise it is uncertain whether this trend is set to continue or be reversed.

Climate-Driven Variability and Trends in Plant Productivity Over Recent Decades Based on Three Global Products

Variability in climate exerts a strong influence on vegetation productivity (gross primary productivity; GPP), and therefore has a large impact on the land carbon sink. However, no direct observations of global GPP exist, and estimates rely on models that are constrained by observations at various spatial and temporal scales. Here, we assess the consistency in GPP from global products which extend for more than three decades; two observation-based approaches, the upscaling of FLUXNET site observations (FLUXCOM) and a remote sensing derived light use efficiency model (RS-LUE), and from a suite of terrestrial biosphere models (TRENDYv6). At local scales, we find high correlations in annual GPP among the products, with exceptions in tropical and high northern latitudes. On longer time scales, the products agree on the direction of trends over 58% of the land, with large increases across northern latitudes driven by warming trends. Further, tropical regions exhibit the largest interannual variability in GPP, with both rainforests and savannas contributing substantially. Variability in savanna GPP is likely predominantly driven by water availability, although temperature could play a role via soil moisture-atmosphere feedbacks. There is, however, no consensus on the magnitude and driver of variability of tropical forests, which suggest uncertainties in process representations and underlying observations remain. These results emphasize the need for more direct long-term observations of GPP along with an extension of in situ networks in underrepresented regions (e.g., tropical forests). Such capabilities would support efforts to better validate relevant processes in models, to more accurately estimate GPP.