A two-fold increase of carbon cycle sensitivity to tropical temperature variations

Sensitivity of land carbon sinks to the three major oscillations in the Northern Hemisphere

The Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Pacific-North American Pattern (PNA) cause climate variability in the Northern Hemisphere (NH), which affects the carbon cycle of terrestrial ecosystems. Based on a dynamic global vegetation model, we analysed the impacts of the AO, NAO and PNA on changes in terrestrial climate and carbon cycle dynamics from 1980 to 2017. The positive AO (pAO), positive NAO (pNAO), and positive PNA (pPNA) mainly led to warmer and more humid conditions in the North Asia (NA) and Europe (EUR), whereas the negative AO (nAO), negative NAO (nNAO), and negative PNA (nPNA) resulted in colder and drier conditions. Furthermore, the nAO, nNAO, and nPNA increased the carbon sinks of terrestrial ecosystems, whereas the pAO, pNAO, and pPNA reduced the carbon sinks, especially in EUR. We also quantified the direct impacts of the oscillations in the concurrent season and their legacy impacts from the preceding season separately. Increased AO and NAO indices increased the carbon sinks in the East Asia (EA) and EUR, whereas an increased PNA index reduced the carbon sinks in most parts of the NH. With respect to legacy impacts, increased AO and PNA indices enhanced the carbon sinks in the Central-Western Asia and North Africa (CWN), Temperate North America (TNA) and Boreal North America (BNA), whereas an increased NAO index strengthened the carbon source capacity in the CWN, EUR, TNA, BNA. These results provide a framework for conducting further research on the mechanisms of interannual variability of the terrestrial carbon cycle.

The optimal applications of scPDSI and SPEI in characterizing meteorological drought, agricultural drought and terrestrial water availability on a global scale

The Palmer Drought Severity Index (scPDSI) and the Standardized Precipitation Evapotranspiration Index (SPEI) are two of the most commonly used drought indices. However, scPDSI and SPEI at a specific scale are often used interchangeably to characterize meteorological drought, agricultural drought, or terrestrial water availability, leading to potential inaccuracies in research outcomes. This study thus presents a global-scale assessment of the applications of scPDSI and SPEI at various timescales (SPEIs) in these contexts. Our findings indicate that scPDSI is more suitable for monitoring agricultural drought than meteorological drought, and highlight the effectiveness of SPEI at one month scale (SPEI01) for meteorological drought. Additionally, SPEI at nine months scale (SPEI09) is more appropriate for agricultural drought. Regarding their relationship with vegetation water stress, scPDSI and SPEI09 are more closely associated with root-zone soil moisture, while SPEI01 is most closely linked to vapor pressure deficit. Furthermore, we evaluate the capability of scPDSI and SPEI in representing terrestrial water availability by analyzing the responses of diverse vegetation indicators to them, including the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Solar-Induced Chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP). All four vegetation indicators show the highest sensitivity of negative response to SPEI01 in cold climate regions, suggesting SPEI01 is most applicable in these regions. In drylands, vegetation indicators exhibit higher sensitivity of positive responses to SPEI at six months scale (SPEI06) and SPEI09, indicating SPEI06 and SPEI09 effectively characterize water availability in such areas. These findings enhance the understanding of scPDSI and SPEI, providing clearer guidelines for their global-scale applications in meteorological drought, agricultural drought, and terrestrial water availability.

Assessing and improving the high uncertainty of global gross primary productivity products based on deep learning under extreme climatic conditions

Gross Primary Productivity (GPP) is a crucial indicator of the carbon fixed by plants through photosynthesis, playing a vital role in understanding and managing ecological and environmental processes. However, global warming, characterized by elevated temperatures, water shortage, and increased drought stress, has significantly impacted GPP. Various GPP products based on different algorithms and input data have been developed, but their performance under extreme climatic conditions remains unverified. This study evaluated the consistency and accuracy of eight global GPP products from 2003 to 2014 using flux towers data. The results show that GPP products performed well under overall conditions, with an average correlation coefficient (R2) of 0.604, and Penman-Monteith-Leuning-version-2 (PMLv2) showed the best performance (R2 = 0.664). However, under extreme climatic conditions like high temperature, high vapor pressure deficit (VPD), and drought, the accuracy significantly dropped (R2 = 0.3), with Global-dataset-of-solar-induced-chlorophyll-fluorescence (GOSIF) being the most affected. Accuracy was lower in croplands (CRO) and grasslands (GRA). To enhance accuracy under extreme climatic conditions, GPP products were used as inputs to a Convolutional Neural Network (CNN) based on ECMWF-Reanalysis-5th-Generation (ERA5) meteorological data and compared with random forests (RF). Four GPP products significantly contributed to the model, with a cumulative contribution of 80.3 %. Under extreme climatic conditions, CNN significantly improved the estimation accuracy of GPP and outperformed RF. The optimal values for R2 and the root mean square error (RMSE) were 0.905 (increase by at least 201.7 %) and 7.708 gC m-2 8d-1 (decrease by at least 50.7 %). The model also performed well at 20 independent validation sites (R2 = 0.783). This study offers a method to improve GPP estimation under extreme climatic conditions, unrestricted by time and space.

Transcriptome-wide methylated RNA immunoprecipitation sequencing profiling reveals m6A modification involved in response to heat stress in Apostichopus japonicus

BACKGROUND

Global warming-induced environmental stresses have diverse effects on gene expression and regulation in the life processes of various aquatic organisms. N6 adenylate methylation (m6A) modifications are known to influence mRNA transcription, localization, translation, stability, splicing, and nuclear export, which are pivotal in mediating stress responses. Apostichopus japonicus is a significant species in aquaculture and a representative of benthic organisms in ecosystems, thus there is a growing need for research on its heat stress mechanism.

RESULTS

In this study, m6A-modified whole transcriptome profiles of the respiratory tree tissues of A. japonicus in the control (T18) and high-temperature stress (T32) groups were obtained using MeRIP-seq technology. The results showed that 7,211 common m6A peaks, and 9,459 genes containing common m6A were identified in three replicates T18 and T32 groups. The m6A peaks were found to be highly enriched in the 3' untranslated region, and the common sequence of the m6A peak was also enriched, which was shown as RRACH (R = G or A; H = A, C, or U). A total of 1,200 peaks were identified as significantly differentially enriched in the T32 group compared with the T18 group. Among them, 245 peaks were upregulated and 955 were downregulated, which indicated that high temperature stress significantly altered the methylation pattern of m6A, and there were more demethylation sites in the T32 group. Conjoint analysis of the m6A methylation modification and the transcript expression level (the MeRIP-seq and RNA-seq data) showed co-differentiated 395 genes were identified, which were subsequently divided into four groups with a predominant pattern that more genes with decreased m6A modification and up-regulated expression, including HSP70IV, EIF2AK1, etc. GO enrichment and KEGG analyses of differential m6A peak related genes and co-differentiated genes showed the genes were significantly associated with transcription process and pathways such as protein processing in the endoplasmic reticulum, Wnt signaling pathway, and mTOR signaling pathway, etc. CONCLUSION: The comparisons of m6A modification patterns and conjoint analyses of m6A modification and gene expression profiles suggest that m6A modification was involved in the regulation of heat stress-responsive genes and important functional pathways in A. japonicus in response to high-temperature stress. The study will contribute to elucidate the regulatory mechanism of m6A modification in the response of A. japonicus to environmental stress, as well as the conservation and utilization of sea cucumber resources in the context of environmental changes.

Weakening of global terrestrial carbon sequestration capacity under increasing intensity of warm extremes

The net ecosystem exchange (NEE), determining terrestrial carbon sequestration capacity, is strongly controlled by climate change and has exhibited substantial year-to-year fluctuations. How the increased frequency and intensity of warm extremes affect NEE variations remains unclear. Here, we combined multiple NEE datasets from atmospheric CO2 inversions, Earth system models, eddy-covariance data-driven methods and climate datasets to show that the terrestrial carbon sequestration capacity is weakened during warm extreme occurrences over the past 40 years, primarily contributed by tropical regions (81% ± 48%). The underlying mechanism can be rooted in the overwhelmingly decreased trend of gross primary productivity compared with terrestrial ecosystem respiration. Additionally, the weakened terrestrial carbon sequestration capacity is mainly driven by the transition from temperature or soil moisture control to vapour pressure deficit control, which is associated with the increasing intensity of warm extremes. Our findings suggest that warm extremes threaten the global carbon sequestration function of terrestrial ecosystems. Therefore, more attention should be given to the evolution of the increasing intensity of warm extremes in future climate projections.

Enhanced global carbon cycle sensitivity to tropical temperature linked to internal climate variability

The sensitivity of atmospheric CO2 growth rate to tropical temperature (γT) has almost doubled between 1959 and 2011, a trend that has been linked to increasing drought in the tropics. However, γT has declined since then. Understanding whether these variations in γT reflect forced changes or internal climate variability in the carbon cycle is crucial for future climate projections. We show that doubling sensitivity events can arise in simulations by Earth system models with perturbed initial conditions but are likely explained by internal climate variability. We show that the doubling sensitivity event is associated with the occurrence of a few, but very strong, El Niño events, such as 1982/83 and 1997/98. Such extreme events result in concurrent carbon release by tropical and extratropical ecosystems, increasing the variance of the global land carbon sink and its apparent sensitivity to tropical temperature. Our results imply that the doubling sensitivity does not necessarily indicate a change in carbon cycle response to climate change.

The impacts of rising vapour pressure deficit in natural and managed ecosystems

An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land-atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co-evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

Ecohydrological investigation of cloud seeding effect on vegetation activity in the Boryeong Dam Basin, South Korea

Cloud seeding is well known to address water shortage problems caused by droughts by adding more precipitation and consequent runoff. Unlike previous studies, this study investigates another positive effect of cloud seeding on the activation of vegetation by integrating numerical cloud seeding simulations and processed-based modeling of various ecohydrological components. As the carbon cycle is closely related to the hydrological processes in ecosystems, we adopt the RHESSys ecohydrological modeling to synthetically simulate runoff and soil moisture along with primary productivity and vegetation respiration. Numerical simulations with and without cloud seeding are generated by the WRF-ARW model for the Boryeong Dam basin, one of the basins vulnerable to droughts, in 2021. The cloud seeding simulations of two cases are input into the RHESSys model to examine changes in hydrological and ecological components due to the added amount of precipitation. The results exhibit significant increases in annual precipitation (18 %) and runoff (22 %), and enhanced soil moisture stimulating the ecological components such as GPP and NPP, especially in spring. Cloud seeding can be considered to create optimal conditions for vegetation to absorb or sequester carbon from the atmosphere, thereby boosting vegetation growth. Additionally, the time-lagged correlations between cloud seeding and soil moisture, GPP, NPP, and respiration suggest that vegetation activity is highly dependent on antecedent 1-2 months occurrences of cloud seeding. This study implies that the cloud seeding effect on additional NPP can be considered as a countermeasure of the global average forest loss, which means that carbon emission rise in the global warming era can be partly alleviated by cloud seeding.

Impacts of commodity prices and governance on the expansion of tropical agricultural frontiers

Deforestation in the tropics remains a significant global challenge linked to carbon emissions and biodiversity loss. Agriculture, forestry, wildfires, and urbanization have been repeatedly identified as main drivers of tropical deforestation. Understanding the underlying mechanisms behind these direct causes is crucial to navigate the multiple tradeoffs between competing forest uses, such as food and biomass production (SDG 2), climate action (SDG 13), and life on land (SDG 15). This paper develops and implements a global-scale empirical approach to quantify two key factors affecting land use decisions at tropical forest frontiers: agricultural commodity prices and national governance. It relies on data covering the period 2004-2015 from multiple public sources, aggregated to countries and agro-ecological zones. Our analysis confirms the persistent influence of commodity prices on agricultural land expansion, especially in forest-abundant regions. Economic and environmental governance quality co-determines processes of expansion and contraction of agricultural land in the tropics, yet at much smaller magnitudes than other drivers. We derive land supply elasticities for direct use in standard economic impact assessment models and demonstrate that our results make a difference in a Computable General Equilibrium framework.

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.

Land use/cover and land degradation across the Eurasian steppe: Dynamics, patterns and driving factors

Despite the ecological and socio-economic importance of Eurasian steppe, the land use/cover change, land degradation and the threats facing this precious ecosystem still have not been comprehensively understood. Taking advantages of the land use/cover change monitoring platform (FROM-GLC Plus), this study developed the annual land use/cover maps during 2000-2022, and the land use/cover change, especially the change of grassland, was further analyzed. The grassland area exhibited a net increase, predominantly transformed from cropland, forest, and bareland, accounting for 17.64 %, 31.91 %, and 45.60 %, respectively. To monitor land degradation, we adopted the framework suggested by the United Nations Convention to Combat Desertification (UNCCD). According to the monitoring result, grassland constituted the highest proportion of degraded land (39.82 %). This may due to its dominance in the Eurasian steppe's land use/cover, as the extent of grassland degradation (1.92 %) was lower than the overall land degradation level (2.83 %) across the region. To offer tailored and sustainable development recommendations, we quantified the driving factors behind land dynamics using the geographical detector model and convergent cross mapping (CCM), considering both spatial and temporal dimensions. Environmental and socio-economic factors, such as precipitation, temperature, urbanization, mining and grazing intensity, etc., were integrated into the analysis. We found that urbanization, cropland and moisture distribution emerged as key drivers influencing land degradation's spatial distribution in the Eurasian steppe, while temperature variations between years impacted vegetation changes. This research thus provides a deeper understanding of the region's land dynamics, enhancing comprehensive monitoring of the Eurasian steppe's land dynamics. Moreover, it serves as a foundation for policymakers and land managers to devise conservation strategies and sustainable development initiatives for this critical ecosystem.

Four years of climate warming reduced dark carbon fixation in coastal wetlands

Dark carbon fixation (DCF), conducted mainly by chemoautotrophs, contributes greatly to primary production and the global carbon budget. Understanding the response of DCF process to climate warming in coastal wetlands is of great significance for model optimization and climate change prediction. Here, based on a 4-yr field warming experiment (average annual temperature increase of 1.5°C), DCF rates were observed to be significantly inhibited by warming in coastal wetlands (average annual DCF decline of 21.6%, and estimated annual loss of 0.08-1.5 Tg C yr-1 in global coastal marshes), thus causing a positive climate feedback. Under climate warming, chemoautotrophic microbial abundance and biodiversity, which were jointly affected by environmental changes such as soil organic carbon and water content, were recognized as significant drivers directly affecting DCF rates. Metagenomic analysis further revealed that climate warming may alter the pattern of DCF carbon sequestration pathways in coastal wetlands, increasing the relative importance of the 3-hydroxypropionate/4-hydroxybutyrate cycle, whereas the relative importance of the dominant chemoautotrophic carbon fixation pathways (Calvin-Benson-Bassham cycle and W-L pathway) may decrease due to warming stress. Collectively, our work uncovers the feedback mechanism of microbially mediated DCF to climate warming in coastal wetlands, and emphasizes a decrease in carbon sequestration through DCF activities in this globally important ecosystem under a warming climate.

Recent decline in tropical temperature sensitivity of atmospheric CO2 growth rate variability

A two-fold enhancement in the sensitivity of atmospheric CO2 growth rate (CGR) to tropical temperature interannual variability (Γ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ ) till early 2000s has been reported, which suggests a drought-induced shift in terrestrial carbon cycle responding temperature fluctuations, thereby accelerating global warming. However, using six decades long atmospheric CO2 observations, we show thatΓ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ has significantly declined in the last two decades, to the level during the 1960s. TheΓ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ decline begs the question of whether the sensitivity of ecosystem carbon cycle to temperature variations at local scale has largely decreased. With state-of-the-art dynamic global vegetation models, we further find that the recentΓ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ decline is barely attributed to ecosystem carbon cycle response to temperature fluctuations at local scale, which instead results from a decrease in spatial coherence in tropical temperature variability and land use change. Our results suggest that the recently reported loss of rainforest resilience has not shown marked influence on the temperature sensitivity of ecosystem carbon cycle. Nevertheless, the increasing extent of land use change as well as more frequent and intensive drought events are likely to modulate the responses of ecosystem carbon cycle to temperature variations in the future. Therefore, our study highlights the priority to continuously monitor the temperature sensitivity of CGR variability and improve Earth system model representation on land use change, in order to predict the carbon-climate feedback.

Warming inhibits increases in vegetation net primary productivity despite greening in India

India is the second-highest contributor to the post-2000 global greening. However, with satellite data, here we show that this 18.51% increase in Leaf Area Index (LAI) during 2001-2019 fails to translate into increased carbon uptake due to warming constraints. Our analysis further shows 6.19% decrease in Net Primary Productivity (NPP) during 2001-2019 over the temporally consistent forests in India despite 6.75% increase in LAI. We identify hotspots of statistically significant decreasing trends in NPP over the key forested regions of Northeast India, Peninsular India, and the Western Ghats. Together, these areas contribute to more than 31% of the NPP of India (1274.8 TgC.year-1). These three regions are also the warming hotspots in India. Granger Causality analysis confirms that temperature causes the changes in net-photosynthesis of vegetation. Decreasing photosynthesis and stable respiration, above a threshold temperature, over these regions, as seen in observations, are the key reasons behind the declining NPP. Our analysis shows that warming has already started affecting carbon uptake in Indian forests and calls for improved climate resilient forest management practices in a warming world.

Characterizing the regional XCO2 variability and its association with ENSO over India inferred from GOSAT and OCO-2 satellite observations

India is primarily concerned with comprehending regional carbon source-sink response in the context of changes in atmospheric CO2 concentrations or anthropogenic emissions. Recent advancements in high-resolution satellite's fine-scale XCO2 measurements provide an opportunity to understand unprecedented details of source-sink activity on a regional scale. In this study, we investigated the long-term variations of XCO2 concentration and growth rates as well as its covarying relationship with ENSO and regional climate parameters (temperature, precipitation, soil moisture, and NDVI) over India from 2010 to 2021 using GOSAT and OCO-2 retrievals. The results show since the launch of OCO-2 in 2014, the number of monthly high-quality XCO2 soundings over India has grown nearly 100-fold compared to GOSAT, launched in 2009. Also, the discrepancy in XCO2 increase of 2.54(2.43) ppm/yr was observed in GOSAT (OCO-2) retrieval during an overlapping measurement period (2015-2021). Additionally, wavelet analysis indicated that the OCO-2 retrieval is able to capture a better frequency of local-scale XCO2 variability compared to GOSAT, owing to its high-resolution cloud-free XCO2 soundings, providing more well-defined regional-scale source-sink features. Furthermore, dominant spatial pattern of XCO2 variability observed over south and southeast of India in both satellites, with XCO2 semi-annual and annual variability more distinctly present in OCO-2 compared to GOSAT. A cross-correlation analysis suggested GOSAT XCO2 growth rate positively correlates with ENSO in different homogeneous monsoon regions of India, with ENSO leading the GOSAT XCO2 growth rate in all homogeneous regions by 3-9 months. The South Peninsular region sensitive to ENSO changes, especially during 2015-2016 ENSO event, where a decrease in CO2 uptake was observed is closely linked with precipitation, soil moisture, and temperature anomalies. However, regional climate parameters show a low correlation with XCO2 growth since CO2 is a long-lived well-mixed gas primarily having an imprint of large-scale transport in column CO2.

Low frequency changes in CO2 concentration in East Asia related to Pacific decadal oscillation and Atlantic multi-decadal oscillation for mid-summer and early fall

The climatological seasonal maximum and minimum CO₂ concentrations in East Asia for 1987-2020 have been recorded at April and August, respectively. We found that the CO₂ concentration in East Asia during July, August, and September (JAS) is lower than normal before the late 1990s and after the early 2010s (Low_CO₂ period), and higher than normal from the late 1990s to the early 2010s (High_CO₂ period). The low-frequency variability of CO₂ concentration in East Asia during JAS correlates with both Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO)-related sea surface temperatures (SSTs). We analyzed atmospheric and oceanic conditions during JAS between the two periods, finding that precipitation in East Asia decreased during JAS in High_CO₂ period than that in Low_CO₂ period, possibly due to PDO and AMO-related SST forcing, which decreases vegetation's photosynthetic activity. This may lead to a higher CO₂ concentration than normal in East Asia in High_CO₂ period through reduced uptake of CO₂ from the atmosphere. This implies that terrestrial vegetation activity influenced by remote SST forcings should be monitored to better understand regional carbon cycles in East Asia.

Increasingly negative tropical water-interannual CO2 growth rate coupling

Terrestrial ecosystems have taken up about 32% of the total anthropogenic CO2 emissions in the past six decades1. Large uncertainties in terrestrial carbon-climate feedbacks, however, make it difficult to predict how the land carbon sink will respond to future climate change2. Interannual variations in the atmospheric CO2 growth rate (CGR) are dominated by land-atmosphere carbon fluxes in the tropics, providing an opportunity to explore land carbon-climate interactions3-6. It is thought that variations in CGR are largely controlled by temperature7-10 but there is also evidence for a tight coupling between water availability and CGR11. Here, we use a record of global atmospheric CO2, terrestrial water storage and precipitation data to investigate changes in the interannual relationship between tropical land climate conditions and CGR under a changing climate. We find that the interannual relationship between tropical water availability and CGR became increasingly negative during 1989-2018 compared to 1960-1989. This could be related to spatiotemporal changes in tropical water availability anomalies driven by shifts in El Niño/Southern Oscillation teleconnections, including declining spatial compensatory water effects9. We also demonstrate that most state-of-the-art coupled Earth System and Land Surface models do not reproduce the intensifying water-carbon coupling. Our results indicate that tropical water availability is increasingly controlling the interannual variability of the terrestrial carbon cycle and modulating tropical terrestrial carbon-climate feedbacks.

Global concurrent climate extremes exacerbated by anthropogenic climate change

Increases in concurrent climate extremes in different parts of the world threaten the ecosystem and our society. However, spatial patterns of these extremes and their past and future changes remain unclear. Here, we develop a statistical framework to test for spatial dependence and show widespread dependence of temperature and precipitation extremes in observations and model simulations, with more frequent than expected concurrence of extremes around the world. Historical anthropogenic forcing has strengthened the concurrence of temperature extremes over 56% of 946 global paired regions, particularly in the tropics, but has not yet significantly affected concurrent precipitation extremes during 1901-2020. The future high-emissions pathway of SSP585 will substantially amplify the concurrence strength, intensity, and spatial extent for both temperature and precipitation extremes, especially over tropical and boreal regions, while the mitigation pathway of SSP126 can ameliorate the increase in concurrent climate extremes for these high-risk regions. Our findings will inform adaptation strategies to alleviate the impact of future climate extremes.

Diagnosing destabilization risk in global land carbon sinks

Global net land carbon uptake or net biome production (NBP) has increased during recent decades1. Whether its temporal variability and autocorrelation have changed during this period, however, remains elusive, even though an increase in both could indicate an increased potential for a destabilized carbon sink2,3. Here, we investigate the trends and controls of net terrestrial carbon uptake and its temporal variability and autocorrelation from 1981 to 2018 using two atmospheric-inversion models, the amplitude of the seasonal cycle of atmospheric CO2 concentration derived from nine monitoring stations distributed across the Pacific Ocean and dynamic global vegetation models. We find that annual NBP and its interdecadal variability increased globally whereas temporal autocorrelation decreased. We observe a separation of regions characterized by increasingly variable NBP, associated with warm regions and increasingly variable temperatures, lower and weaker positive trends in NBP and regions where NBP became stronger and less variable. Plant species richness presented a concave-down parabolic spatial relationship with NBP and its variability at the global scale whereas nitrogen deposition generally increased NBP. Increasing temperature and its increasing variability appear as the most important drivers of declining and increasingly variable NBP. Our results show increasing variability of NBP regionally that can be mostly attributed to climate change and that may point to destabilization of the coupled carbon-climate system.

Recent decrease of the impact of tropical temperature on the carbon cycle linked to increased precipitation

The atmospheric CO₂ growth rate (CGR) variability is largely controlled by tropical temperature fluctuations. The sensitivity of CGR to tropical temperature [Formula: see text] has strongly increased since 1960, but here we show that this trend has ceased. Here, we use the long-term CO₂ records from Mauna Loa and the South Pole to compute CGR, and show that [Formula: see text] increased by 200% from 1960-1979 to 1979-2000 but then decreased by 117% from 1980-2001 to 2001-2020, almost returning back to the level of the 1960s. Variations in [Formula: see text] are significantly correlated with changes in precipitation at a bi-decadal scale. These findings are further corroborated by results from a dynamic vegetation model, collectively suggesting that increases in precipitation control the decreased [Formula: see text] during recent decades. Our results indicate that wetter conditions have led to a decoupling of the impact of the tropical temperature variation on the carbon cycle.

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.

Nitrogen and water availability control plant carbon storage with warming

Plants may slow global warming through enhanced growth, because increased levels of photosynthesis stimulate the land carbon (C) sink. However, how climate warming affects plant C storage globally and key drivers determining the response of plant C storage to climate warming remains unclear, causing uncertainty in climate projections. We performed a comprehensive meta-analysis, compiling 393 observations from 99 warming studies to examine the global patterns of plant C storage responses to climate warming and explore the key drivers. Warming significantly increased total biomass (+8.4 %), aboveground biomass (+12.6 %) and belowground biomass (+10.1 %). The effect of experimental warming on plant biomass was best explained by the availability of soil nitrogen (N) and water. Across the entire dataset, warming-induced changes in total, aboveground and belowground biomass all positively correlated with soil C:N ratio, an indicator of soil N availability. In addition, warming stimulated plant biomass more strongly in humid than in dry ecosystems, and warming tended to decrease root:shoot ratios at high soil C:N ratios. Together, these results suggest dual controls of warming effects on plant C storage; warming increases plant growth in ecosystems where N is limiting plant growth, but it reduces plant growth where water availability is limiting plant growth.

Divergent responses of cropland soil organic carbon to warming across the Sichuan Basin of China

Cropland soils are considered to have the potential to sequester carbon (C). Warming can increase soil organic C (SOC) by enhancing primary production, but it can also cause carbon release from soils. However, the role of warming in governing cropland SOC dynamics over broad geographic scales remains poorly understood. Using over 4000 soil samples collected in the 1980s and 2010s across the Sichuan Basin of China, this study assessed the warming-induced cropland SOC change and the correlations with precipitation, cropland type and soil type. Results showed mean SOC content increased from 11.10 to 13.85 g C kg^-1. Larger SOC increments were observed under drier conditions (precipitation < 1050 mm, dryland and paddy-dryland rotation cropland), which were 1.67-2.23 times higher than under wetter conditions (precipitation > 1050 mm and paddy fields). Despite the significant associations of SOC increment with crop productivity, precipitation, fertilization, cropland type and soil type, warming also acted as one of major contributors to cropland SOC change. The SOC increment changed parabolically with the rise in temperature increase rate under relatively drier conditions, while temperature increase had no impact on cropland SOC increment under wetter conditions. Meanwhile, the patterns of the parabolical relationship varied with soil types in drylands, where the threshold of temperature increase rate, the point at which the SOC increment switched from increasing to decreasing with warming, was lower for clayey soils (Ali-Perudic Argosols) than for sandy soils (Purpli-Udic Cambosols). These results illustrate divergent responses of cropland SOC to warming under different environments, which were contingent on water conditions and soil types. Our findings emphasize the importance of formulating appropriate field water management for sustainable C sequestration and the necessity of incorporating environment-specific mechanisms in Earth system models for better understanding of the soil C-climate feedback in complex environments.

Soil seed bank distribution and restoration potential in the vegetation of Buska Mountain range, Hamar district, southwestern Ethiopia

The seed banks are vital components for the reestablishment of degraded lands since they are used to predict the future coverage of vegetation and allow for the implementation of appropriate conservation measures in a particular area. The study was conducted in the Buska Mountains of the Hamar area in south-western Ethiopia and determined the composition, density and vertical distribution of soil seed banks under various land-use systems and soil layers. A total of 96 soil samples were involved in the study; four land-use types (grassland, forest, scrub and bare ground). Three distinct soil layers from each plot (0–3 cm, 3–6 cm, 6–9 cm depths) were sampled. Jaccard's Similarity Coefficient was applied to evaluate the correspondence between different land-use types and soil layers. One-way ANOVA was used to compute species density and composition respectively within land-use systems along with the seed bank and above ground vegetation. Fifty six (56) species within 27 plant families and 50 genera were recorded. Twenty percent of the species was contributed by Asteraceae followed by Poaceae (16%). Herbaceous growth forms were the most dominant in the area, contributing about 78.6%. The total seedling density in the study plots was 8171 seedlings/m². Jaccard's Similarity Coefficient is relatively higher (0.52) between grassland and scrub, while the forest and bare land had the least amount of similarity (0.22). There was seen a higher similarity of species between the first and second soil layers and a decreasing density with soil depth. A substantial difference between the aboveground species and seed bank was recorded in the area. The lower resemblance between the standing vegetation and the seed bank infers a lower overall restoration potential and suggests other alternative regeneration mechanisms such as seedling plantation of priority indigenous plant species and avoiding anthropogenic disturbances.

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Seed banks play an important role in ecosystem resilience serving as a reservoir of regeneration potential.

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Based on the findings of this study, the new plant recruitments could be predicted.

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It produced a suggestion on the restoration, biological variety conservation and vegetation succession for the maintenance of biodiversity in arid climatic regions.

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In view of the ever-increasing effects of climate change in rangelands in dry regions, like ours, the study’s findings could be an invaluable source of awareness.

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.

Increasing sensitivity of dryland vegetation greenness to precipitation due to rising atmospheric CO2

Water availability plays a critical role in shaping terrestrial ecosystems, particularly in low- and mid-latitude regions. The sensitivity of vegetation growth to precipitation strongly regulates global vegetation dynamics and their responses to drought, yet sensitivity changes in response to climate change remain poorly understood. Here we use long-term satellite observations combined with a dynamic statistical learning approach to examine changes in the sensitivity of vegetation greenness to precipitation over the past four decades. We observe a robust increase in precipitation sensitivity (0.624% yr⁻¹) for drylands, and a decrease (−0.618% yr⁻¹) for wet regions. Using model simulations, we show that the contrasting trends between dry and wet regions are caused by elevated atmospheric CO₂ (eCO₂). eCO₂ universally decreases the precipitation sensitivity by reducing leaf-level transpiration, particularly in wet regions. However, in drylands, this leaf-level transpiration reduction is overridden at the canopy scale by a large proportional increase in leaf area. The increased sensitivity for global drylands implies a potential decrease in ecosystem stability and greater impacts of droughts in these vulnerable ecosystems under continued global change.

Changes in vegetation responses to precipitation may be hydroclimate dependent. Here the authors reveal contrasting trends of vegetation sensitivity to precipitation in drylands vs. wetter ecosystems over the last 4 decades and identify increased CO2 as a major contributing factor.

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.

Seasonal and Inter-Annual Variations of Carbon Dioxide Fluxes and Their Determinants in an Alpine Meadow

The alpine meadow is one of the most important ecosystems on the Qinghai-Tibet Plateau (QTP) due to its huge carbon storage and wide distribution. Evaluating the carbon fluxes in alpine meadow ecosystems is crucial to understand the dynamics of carbon storage in high-altitude areas. Here, we investigated the carbon fluxes at seasonal and inter-annual timescales based on 5 years of observations of eddy covariance fluxes in the Zoige alpine meadow on the eastern Tibetan Plateau. We found that the Zoige alpine meadow acted as a faint carbon source of 94.69 ± 86.44 g C m^-2 y^-1 during the observation periods with large seasonal and inter-annual variations (IAVs). At the seasonal scale, gross primary productivity (GPP) and ecosystem respiration (Re) were positively correlated with photosynthetic photon flux density (PPFD), average daily temperature (Ta), and vapor pressure (VPD) and had negative relationships with volumetric water content (VWC). Seasonal variations of net ecosystem carbon dioxide (CO₂) exchange (NEE) were mostly explained by Ta, followed by PPFD, VPD, and VWC. The IAVs of GPP and Re were mainly attributable to the IAV of the maximum GPP rate (GPP_max) and maximum Re rate (Re_max), respectively, both of which increased with the percentage of Cyperaceae and decreased with the percentage of Polygonaceae changes across years. The IAV of NEE was well explained by the anomalies of the maximum CO₂ release rate (MCR). These results indicated that the annual net CO₂ exchange in the alpine meadow ecosystem was controlled mainly by the maximum C release rates. Therefore, a better understanding of physiological response to various environmental factors at peak C uptake and release seasons will largely improve the predictions of GPP, Re, and NEE in the context of global change.

Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability

Global fluctuations in annual land carbon uptake (NEE_IAV) depend on water and temperature variability, yet debate remains about local and seasonal controls of the global dependences. Here, we quantify regional and seasonal contributions to the correlations of globally-averaged NEE_IAV against terrestrial water storage (TWS) and temperature, and respective uncertainties, using three approaches: atmospheric inversions, process-based vegetation models, and data-driven models. The three approaches agree that the tropics contribute over 63% of the global correlations, but differ on the dominant driver of the global NEE_IAV, because they disagree on seasonal temperature effects in the Northern Hemisphere (NH, >25°N). In the NH, inversions and process-based models show inter-seasonal compensation of temperature effects, inducing a global TWS dominance supported by observations. Data-driven models show weaker seasonal compensation, thereby estimating a global temperature dominance. We provide a roadmap to fully understand drivers of global NEE_IAV and discuss their implications for future carbon–climate feedbacks.

The dominant driver of variations in global land carbon sink remains unclear. Here the authors show that the seasonal compensation of temperature effects on land carbon sink in the Northern Hemisphere could induce a global water dominance.

Revisiting the cumulative effects of drought on global gross primary productivity based on new long-term series data (1982-2018)

Drought has broad and deep impacts on vegetation. Studies on the effects of drought on vegetation have been conducted over years. Recently, the cumulative effect of drought is recognized as another key factor affecting plant growth. However, global-scale studies on this phenomenon are still lacking. Thus, based on new satellite based gross primary productivity (GPP) and multi-temporal scale Standardized Precipitation Evapotranspiration Index data sets, we explored the cumulative effect duration (CED) of drought on global vegetation GPP and analyzed its variability across elevations and climatic zones. The main findings were as follows: (1) The cumulative effect of drought on GPP was widespread, with an average CED of 4.89 months. (2) CED of drought on GPP varied among vegetation types. Specifically, grasslands showed the longest duration, with an average value of 5.28 months, followed by shrublands (5.09 months), wetlands (5.03 months), croplands (4.85 months), savannas (4.58 months), and forestlands (4.57 months). (3) CED of drought on GPP changes with climate conditions. It decreased with the decrease of precipitation in the driest month (P_dry ) and mean annual precipitation in tropical and arid climate zones, respectively. In both temperate and cold climate zones, CED of drought on GPP was shorter in areas with dry winter than that in areas with dry summer. It increased with the decrease of mean annual air temperature in tropical climate zones and decreased with the increase of summer temperature in temperate and cold climatic zones. (4) With increasing elevation, CED of drought on GPP showed a pattern of increasing (0-3000 m), then decreasing (3000-5000 m), and increasing again (>5000 m). Our findings highlight the heterogeneity of CED of drought on GPP, owing to differences in vegetation types, long-term hydrothermal conditions, elevation, etc. The results could deepen our understanding of the effects of drought on global vegetation.

Continuity Scaling: A Rigorous Framework for Detecting and Quantifying Causality Accurately

Data-based detection and quantification of causation in complex, nonlinear dynamical systems is of paramount importance to science, engineering, and beyond. Inspired by the widely used methodology in recent years, the cross-map-based techniques, we develop a general framework to advance towards a comprehensive understanding of dynamical causal mechanisms, which is consistent with the natural interpretation of causality. In particular, instead of measuring the smoothness of the cross-map as conventionally implemented, we define causation through measuring the scaling law for the continuity of the investigated dynamical system directly. The uncovered scaling law enables accurate, reliable, and efficient detection of causation and assessment of its strength in general complex dynamical systems, outperforming those existing representative methods. The continuity scaling-based framework is rigorously established and demonstrated using datasets from model complex systems and the real world.

Soil heterotrophic respiration in response to rising temperature and moisture along an altitudinal gradient in a subtropical forest ecosystem, Southwest China

Globally, one-third of the terrestrial carbon (C) is stored in tropical soils. The warming predicted for this century is expected to increase microbial decomposition in soil and escalate climate change potential by releasing more carbon dioxide (CO₂) into the atmosphere. Understanding the response of soils to warming is a key challenge in predicting future climate change trajectories. Here we examined the combined effect of soil temperature (T_s) and soil water content (VWC) on soil heterotrophic respiration (R_sh) and its temperature sensitivity across different altitudes (2400, 1900, and 1450 m ASL) in the Ailaoshan subtropical forest ecosystem, Southwest China. Along the elevation gradient, soil C stocks in the top 10 cm soil layer increased significantly from 10.7 g/ kg at 1480 m ASL to 283.1 g/ kg at 2480 m ASL. Soil cores from various elevations were translocated to the same, and lower elevations and R_sh from those cores were measured every month from February 2010 to January 2014. Temperature sensitivity (Q₁₀) of R_sh for the period was highest at the highest (H) elevation (Q₁₀ = 5.3), decreased significantly towards the middle (M, Q₁₀ = 3.1) and low (L, Q₁₀ = 1.2) elevation. Q₁₀ at M and L elevation did not differ between the place of origin and translocated cores. For the cores within each elevation, Q₁₀ did not vary across the years. Our models suggest that R_sh increased significantly in response to an increase in T_s at each elevation under an intermediate VWC. Hence, the rate of emission was higher in lower elevations due to a higher T_s range. Our findings highlight that the predicted warming over the 21st century will have the greatest impact of T_s on R_sh, especially on the soils at the highest elevations, and will lead towards positive feedback to the climate system.

Tropical extreme droughts drive long-term increase in atmospheric CO2 growth rate variability

The terrestrial carbon sink slows the accumulation of carbon dioxide (CO2) in the atmosphere by absorbing roughly 30% of anthropogenic CO2 emissions, but varies greatly from year to year. The resulting variations in the atmospheric CO2 growth rate (CGR) have been related to tropical temperature and water availability. The apparent sensitivity of CGR to tropical temperature ([Formula: see text]) has changed markedly over the past six decades, however, the drivers of the observation to date remains unidentified. Here, we use atmospheric observations, multiple global vegetation models and machine learning products to analyze the cause of the sensitivity change. We found that a threefold increase in [Formula: see text] emerged due to the long-term changes in the magnitude of CGR variability (i.e., indicated by one standard deviation of CGR; STDCGR), which increased 34.7% from 1960-1979 to 1985-2004 and subsequently decreased 14.4% in 1997-2016. We found a close relationship (r2 = 0.75, p < 0.01) between STDCGR and the tropical vegetated area (23°S - 23°N) affected by extreme droughts, which influenced 6-9% of the tropical vegetated surface. A 1% increase in the tropical area affected by extreme droughts led to about 0.14 Pg C yr-1 increase in STDCGR. The historical changes in STDCGR were dominated by extreme drought-affected areas in tropical Africa and Asia, and semi-arid ecosystems. The outsized influence of extreme droughts over a small fraction of vegetated surface amplified the interannual variability in CGR and explained the observed long-term dynamics of [Formula: see text].

Tropical tall forests are more sensitive and vulnerable to drought than short forests

Our limited understanding of the impacts of drought on tropical forests significantly impedes our ability in accurately predicting the impacts of climate change on this biome. Here, we investigated the impact of drought on the dynamics of forest canopies with different heights using time-series records of remotely sensed Ku-band vegetation optical depth (Ku-VOD), a proxy of top-canopy foliar mass and water content, and separated the signal of Ku-VOD changes into drought-induced reductions and subsequent non-drought gains. Both drought-induced reductions and non-drought increases in Ku-VOD varied significantly with canopy height. Taller tropical forests experienced greater relative Ku-VOD reductions during drought and larger non-drought increases than shorter forests, but the net effect of drought was more negative in the taller forests. Meta-analysis of in situ hydraulic traits supports the hypothesis that taller tropical forests are more vulnerable to drought stress due to smaller xylem-transport safety margins. Additionally, Ku-VOD of taller forests showed larger reductions due to increased atmospheric dryness, as assessed by vapor pressure deficit, and showed larger gains in response to enhanced water supply than shorter forests. Including the height-dependent variation of hydraulic transport in ecosystem models will improve the simulated response of tropical forests to drought.

Inferring causal relations from observational long-term carbon and water fluxes records

Land, atmosphere and climate interact constantly and at different spatial and temporal scales. In this paper we rely on causal discovery methods to infer spatial patterns of causal relations between several key variables of the carbon and water cycles: gross primary productivity, latent heat energy flux for evaporation, surface air temperature, precipitation, soil moisture and radiation. We introduce a methodology based on the convergent cross-mapping (CCM) technique. Despite its good performance in general, CCM is sensitive to (even moderate) noise levels and hyper-parameter selection. We present a robust CCM (RCCM) that relies on temporal bootstrapping decision scores and the derivation of more stringent cross-map skill scores. The RCCM method is combined with the information-geometric causal inference (IGCI) method to address the problem of strong and instantaneous variable coupling, another important and long-standing issue of CCM. The proposed methodology allows to derive spatially explicit global maps of causal relations between the involved variables and retrieve the underlying complexity of the interactions. Results are generally consistent with reported patterns and process understanding, and constitute a new way to quantify and understand carbon and water fluxes interactions.

Qinghai-Tibetan Plateau Greening and Human Well-Being Improving: The Role of Ecological Policies

Appropriate human activities can have significantly positive effects on vegetation dynamics. In the past 50 years, various ecological policies have improved both ecological change and human well-being in the Qinghai–Tibetan Plateau (QTP), efficiently achieving multiple Sustainable Development Goals (SDGs) of the United Nations’ 2030 Agenda for Sustainable Development. During 1981–2017, the annual mean normalized difference vegetation index (NDVI) of the protected areas (PAs) tended to increase significantly at a rate of 2.93 × 10−4/a (p < 0.01), while non-PAs only increased by 0.6 × 10−4/a (p < 0.5). Improvement in the NDVI of the PAs is more obvious than that of non-PAs. Specifically, the earlier the establishment of the Pas is, the more significant the greening effect will be. Moreover, ecological protection has not slowed improvements in human welfare; on the contrary, the Human Development Index (HDI) has nearly doubled in the past 40 years. In terms of global ecological construction, the Chinese government has demonstrated the responsibilities of a large country in global ecological governance. Chinese initiatives can guide other nations in contributing to the global sustainability aspirations embodied in the 2030 SDGs Agenda. This study can be used as a reference for other countries in the world to coordinate the development of ecological protection and well-being.

Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks

Interannual variability of the terrestrial ecosystem carbon sink is substantially regulated by various environmental variables and highly dominates the interannual variation of atmospheric carbon dioxide (CO₂) concentrations. Thus, it is necessary to determine dominating factors affecting the interannual variability of the carbon sink to improve our capability of predicting future terrestrial carbon sinks. Using global datasets derived from machine-learning methods and process-based ecosystem models, this study reveals that the interannual variability of the atmospheric vapor pressure deficit (VPD) was significantly negatively correlated with net ecosystem production (NEP) and substantially impacted the interannual variability of the atmospheric CO₂ growth rate (CGR). Further analyses found widespread constraints of VPD interannual variability on terrestrial gross primary production (GPP), causing VPD to impact NEP and CGR. Partial correlation analysis confirms the persistent and widespread impacts of VPD on terrestrial carbon sinks compared to other environmental variables. Current Earth system models underestimate the interannual variability in VPD and its impacts on GPP and NEP. Our results highlight the importance of VPD for terrestrial carbon sinks in assessing ecosystems’ responses to future climate conditions.

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.

Decadal variability in land carbon sink efficiency

BACKGROUND

The climate mitigation target of limiting the temperature increase below 2 °C above the pre-industrial levels requires the efforts from all countries. Tracking the trajectory of the land carbon sink efficiency is thus crucial to evaluate the nationally determined contributions (NDCs). Here, we define the instantaneous land sink efficiency as the ratio of natural land carbon sinks to emissions from fossil fuel and land-use and land-cover change with a value of 1 indicating carbon neutrality to track its temporal dynamics in the past decades.

RESULTS

Land sink efficiency has been decreasing during 1957-1990 because of the increased emissions from fossil fuel. After the effect of the Mt. Pinatubo eruption diminished (after 1994), the land sink efficiency firstly increased before 2009 and then began to decrease again after 2009. This reversal around 2009 is mostly attributed to changes in land sinks in tropical regions in response to climate variations.

CONCLUSIONS

The decreasing trend of land sink efficiency in recent years reveals greater challenges in climate change mitigation, and that climate impacts on land carbon sinks must be accurately quantified to assess the effectiveness of regional scale climate mitigation policies.

Tracking the seasonal and inter-annual variations of global gross primary production during last four decades using satellite near-infrared reflectance data

Terrestrial vegetation absorbs approximately 30% of the anthropogenic carbon dioxide (CO₂) emitted into the atmosphere through photosynthesis (represented by gross primary productivity, GPP) and thus effectively mitigates global warming. However, large uncertainties still remain in the global GPP estimations and their long-term trends. Here we used the satellite-based near-infrared reflectance (NIRv) as the proxy of GPP and generated a global long-term (1982-2018) GPP datasets (hereafter GPP_NIRv). Analysis at the site-level showed that NIRv could accurately capture both the monthly and annual variations in GPP (R² = 0.71 and 0.74 respectively) at 104 flux sites. Upscaling the relationships between NIRv and GPP to the global scale, the global annual GPP was estimated to be 128.3 ± 4.0 Pg C yr^-1 during the last four decades, which fell between the estimations from the machine-learning upscaling approach, light-use-efficiency (LUE) models and processed-based models. The seasonal variation of GPP_NIRv was also consistent with those from flux sites and models. More importantly, the inter-annual trends in GPP_NIRv during the last four decades were consistent with those from processed-based models across latitudes, which outperformed the other GPP products. This evidence suggested that the long-term GPP datasets derived from NIRv have better abilities to capture the seasonal and inter-annual variations of terrestrial GPP at the global scale. The long-term GPP_NIRv product could be beneficial for the estimation of terrestrial carbon fluxes and for the projection of future climates.

Soil moisture-atmosphere feedback dominates land carbon uptake variability

Year-to-year changes in carbon uptake by terrestrial ecosystems have an essential role in determining atmospheric carbon dioxide concentrations¹. It remains uncertain to what extent temperature and water availability can explain these variations at the global scale^2-5. Here we use factorial climate model simulations⁶ and show that variability in soil moisture drives 90 per cent of the inter-annual variability in global land carbon uptake, mainly through its impact on photosynthesis. We find that most of this ecosystem response occurs indirectly as soil moisture-atmosphere feedback amplifies temperature and humidity anomalies and enhances the direct effects of soil water stress. The strength of this feedback mechanism explains why coupled climate models indicate that soil moisture has a dominant role⁴, which is not readily apparent from land surface model simulations and observational analyses^2,5. These findings highlight the need to account for feedback between soil and atmospheric dryness when estimating the response of the carbon cycle to climatic change globally^5,7, as well as when conducting field-scale investigations of the response of the ecosystem to droughts^8,9. Our results show that most of the global variability in modelled land carbon uptake is driven by temperature and vapour pressure deficit effects that are controlled by soil moisture.

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.

Soil carbon loss by experimental warming in a tropical forest

Tropical soils contain one-third of the carbon stored in soils globally¹, so destabilization of soil organic matter caused by the warming predicted for tropical regions this century² could accelerate climate change by releasing additional carbon dioxide (CO₂) to the atmosphere^3-6. Theory predicts that warming should cause only modest carbon loss from tropical soils relative to those at higher latitudes^5,7, but there have been no warming experiments in tropical forests to test this⁸. Here we show that in situ experimental warming of a lowland tropical forest soil on Barro Colorado Island, Panama, caused an unexpectedly large increase in soil CO₂ emissions. Two years of warming of the whole soil profile by four degrees Celsius increased CO₂ emissions by 55 per cent compared to soils at ambient temperature. The additional CO₂ originated from heterotrophic rather than autotrophic sources, and equated to a loss of 8.2 ± 4.2 (one standard error) tonnes of carbon per hectare per year from the breakdown of soil organic matter. During this time, we detected no acclimation of respiration rates, no thermal compensation or change in the temperature sensitivity of enzyme activities, and no change in microbial carbon-use efficiency. These results demonstrate that soil carbon in tropical forests is highly sensitive to warming, creating a potentially substantial positive feedback to climate change.

Causes of slowing-down seasonal CO2 amplitude at Mauna Loa

Changing amplitude of the seasonal cycle of atmospheric CO₂ (SCA) in the northern hemisphere is an emerging carbon cycle property. Mauna Loa (MLO) station (20°N, 156°W), which has the longest continuous northern hemisphere CO₂ record, shows an increasing SCA before the 1980s (p < .01), followed by no significant change thereafter. We analyzed the potential driving factors of SCA slowing-down, with an ensemble of dynamic global vegetation models (DGVMs) coupled with an atmospheric transport model. We found that slowing-down of SCA at MLO is primarily explained by response of net biome productivity (NBP) to climate change, and by changes in atmospheric circulations. Through NBP, climate change increases SCA at MLO before the 1980s and decreases it afterwards. The effect of climate change on the slowing-down of SCA at MLO is mainly exerted by intensified drought stress acting to offset the acceleration driven by CO₂ fertilization. This challenges the view that CO₂ fertilization is the dominant cause of emergent SCA trends at northern sites south of 40°N. The contribution of agricultural intensification on the deceleration of SCA at MLO was elusive according to land-atmosphere CO₂ flux estimated by DGVMs and atmospheric inversions. Our results also show the necessity to adequately account for changing circulation patterns in understanding carbon cycle dynamics observed from atmospheric observations and in using these observations to benchmark DGVMs.

Contribution of land use to the interannual variability of the land carbon cycle

Understanding the driving mechanisms of the interannual variability (IAV) of the net land carbon balance (S_net) is important to predict future climate–carbon cycle feedbacks. Past studies showed that the IAV of S_net was correlated with tropical climate variation and controlled by semiarid vegetation. But today’s land ecosystems are also under extensive human land use and management. Here, we report a previously hidden role of land use in driving the IAV of S_net by using an improved biosphere model. We found that managed land accounted for 30–45% of the IAV of S_net over 1959–2015, while the contribution of intact land is reduced by more than half compared with previous assessments of the global carbon budget. Given the importance of land use in modulating future land climate–carbon cycle feedbacks, climate mitigation efforts should strive to reduce land-use emissions and enhance the climate resilience of carbon sinks over managed land.

Terrestrial carbon uptake as high inter-annual variability which can be used to help understand future responses to climate change. Here the authors’ modeling reveals a large portion of this variability is driven by human land use changes and management, and not captured by other models.

Towards Sustainable Urban Planning for Puyo (Ecuador): Amazon Forest Landscape as Potential Green Infrastructure

The peri-urban area of Puyo, where agricultural, urban and conservation logics are mixed, is a contested area in the Ecuadorian Amazon. Rapid urban growth and agricultural activities are the main threats to the conservation of its biodiversity. To promote the conservation of natural spaces in urban planning instruments, it is necessary to first demonstrate their environmental and ecological value. In this paper, such value was analyzed by quantifying biodiversity value and carbon storage capacity in situ. The results show that Puyo’s periphery (a 4 km radius) is an opportunity space, where the conservation of its biodiversity is a key factor in strategies to promote sustainable urban development. Firstly, there are natural areas of high environmental value (secondary forest, gramalote pastures with trees and gramalote pastures) that all together fix 1,664,683 Mg CO2 and control hydrological risks (with 80% of the green areas linked to flood areas)—valuable ecosystem services. Secondly, the conservation of biodiversity brings associated economic activities that can promote local sustainable development. Despite this, the results reveal that the conservation of peri-urban natural ecosystems is not a goal in Puyo’s urban planning strategy. Therefore, future research should be focused on urban planning tools that promote environmentally, economically and socially sustainable urban development.