Forestation at the right time with the right species can generate persistent carbon benefits in China

Suitability mapping of native tree species in dry-hot valleys of Yunnan based on InVEST-MaxEnt coupled modeling: model validation framework with native tree species actual distribution and seed germination

Introduction

The target valleys along the Jinsha, Nujiang, Lancang, and Yuanjiang Rivers exhibit acute human-land conflicts and ecosystem vulnerability. Predicting the distribution of potential suitable habitats for native tree species in Yunnan Province provides basin-scale insights for the management of ecosystems in dry and hot valleys, thereby advancing restoration planning in dry-hot valleys.

Methods

This study investigates native tree species suitability in Yunnan's dry-hot valleys using an integrated MaxEnt-InVEST modeling framework.

Results

Temperature and precipitation emerged as dominant bioclimatic controls, with optimal species occurrence (1 000-2 500 m) showing negative elevation correlation. Four native tree species (Osteomeles schwerinae, Phyllanthus emblica, Quercus francetii and Sapindus delavayi) displayed fragmented suitable areas along mountainous riparian zones, while habitat quality hotspots mainly covered non-urbanized regions, avoiding central urban clusters and northeastern/southeastern karst zones. The coupled model demonstrated significantly improved accuracy compared to the standalone MaxEnt by incorporating land-use impacts, with Yuanmou County case analysis confirming the enhanced predictive capability through actual distribution patterns. Spatial prioritization identified core planting clusters in central/southeastern valleys, though fragmented by agricultural encroachment.

Discussion

This methodology provides a cost-effective solution for vegetation restoration planning in ecologically fragile dry-hot ecosystems. The research results can provide scientific support for the restoration of degraded ecosystems in dry-hot valleys of Yunnan Province, the national Afforestation program and soil and water conservation projects.

Soil carbon stability regulate carbon dynamics following large-scale afforestation

Large-scale afforestation is considered an effective measure to mitigate climate change. However, due to the differences in the properties of soil organic carbon (SOC), the dynamic response of SOC to large-scale afforestation remained unclear. Therefore, we conducted paired sampling (farmland and afforestation) in plantation areas across northern China to evaluate the relationship between SOC stability and SOC increments (ΔSOC) resulting from afforestation. Our findings indicated that SOC-unstable soil supported greater carbon increments through afforestation, but at the expense of reduced SOC stability after afforestation. Additionally, we observed that this relationship exhibited geographical characteristics, with SOC-unstable soil demonstrating a stronger capacity to enhance ΔSOC at higher latitudes, particularly in the topsoil. This is primarily attributed to the fact that higher latitudes and colder climates enhance the contribution of particulate organic carbon to ΔSOC and weaken the regulatory effect of SOC chemical composition (carboxyl and aromatic carbon) on SOC stability after afforestation. These findings underscore the importance of incorporating pre-afforestation SOC stability to accurately predict soil carbon-afforestation feedback.

Biophysical impact of forest age changes on land surface temperature in China

Forest age structures have been substantially affected by natural disturbances and anthropogenic activities worldwide. Their changes can significantly influence local and nonlocal climate through both the biogeochemical and biophysical processes. However, numerous studies have focused on the biogeochemical effect of forest age changes whereas the biophysical effect has received far less attention. Here we investigated how forest age changes influence land surface temperature (LST) by comparing older forests and adjacent younger forests pixels and unraveled underlying biophysical mechanisms using satellite observations over China during 2003-2012. Our study showed that older forests had a substantial annual cooling benefit than adjacent medium-aged and young forests. Attribution analysis indicated that the cooling effect of latent heat flux counteracted the albedo-induced warming effect, leading to the net cooling effect of older evergreen needle-leaved forest or evergreen broadleaved forest. Furthermore, the cooling effect of sensible heat flux is greater than the albedo-driven warming effect, contributing to the net cooling effect of older deciduous broadleaved forest. Our work is a step forward to underscore the potential of preserving mature forests as a local climate adaptation strategy and provides important parameterization foundation for earth system models without incorporation of forest age modules.

Greening but enhanced vegetation water stress in the Yellow River Basin: A holistic perspective

The Yellow River Basin (YRB) has emerged as a focal point of global vegetation greening due to climate change and human activities. Given its ecological vulnerability and intense human activities, environmental sustainability has become an urgent concern for scholars. Current research on the hydrological effects of vegetation greening, from a reductionist perspective, still struggle to answer the crucial question that whether vegetation water stress is increasing or decreasing. Towards that, we adopt a holistic perspective to explore the relationships between monthly vegetation dynamics and multiple water stress indicators in the YRB from 1982 to 2018. Using statistical methods and the random forest model, we revealed that both gross primary productivity and water use efficiency showed an increasing trend, with rates of 5.83 g Cm-2 and 0.01 g Cmm-1m-2 per year, respectively. We identified that with increasing climatic aridity, the water stress factors for vegetation transition from monthly scale water conditions (vapor pressure deficit, VPD) to 1-2 months scale (soil water content, SWC) and seasonal scale (standardized precipitation evapotranspiration index-3, SPEI-3) water balance status. And with an aridity index of 0.35 as the threshold, the response of vegetation to water stress factors exhibits marked spatial differentiation. Furthermore, since 2000, despite a persistent greening trend in the YRB, there has been a noticeable expansion in the spatial range of intermediate and long-term water stress factors (SWC, SPEI-3), indicating an enhancing vegetation water stress. This suggests that a serious attention should be paid to the future ecological security of the YRB under the intensified climate change.

Understanding sustainability of woody species suitability zones on the Loess Plateau for optimal creation zone selection in response to future climate change

Climate change has profound implications for the distribution of suitable habitats for woody species. In this study, we assessed the optimal distribution thresholds for twelve woody species on the Loess Plateau using the Maximum Entropy (MaxEnt) model, incorporating sample points of tree species alongside relevant environmental variables. We analyzed the sustainability of potentially suitable zones and proposed a framework for selecting a regulatory model to establish the most suitable creation zones in response to future climate change. The results indicated that: (1) The distributions potentially suitable for Platycladus orientalis and Pinus tabuliformis were predominantly influenced by mean annual temperatures, whereas Pinus armandii and Quercus aliena var. acutiserrata exhibited optimal conditions at temperatures around -4 °C. Both Hippophae rhamnoides and Larix gmelinii var. principis-rupprechtii had suitable threshold precipitation levels exceeding 200 mm, with optimal thresholds surpassing 250 mm. (2) Most high-suitability zones for woody species across various future climate scenarios were primarily located in southern regions, including examples such as Betula platyphylla Sukaczev, Platycladus orientalis, Pinus sylvestris var. mongholica. Some of these high-suitability areas displayed insular and linear distributions, notably Larix gmelinii var. principis-rupprechtii, Quercus aliena var. acutiserrata, Salix cheilophila. (3) There was no southward shift in the northern boundary of the sustainability zones for any woody species across the different scenarios. Betula platyphylla and Salix babylonica exhibited the broadest distribution of sustainability zones. (4) The most suitable areas for the establishment of woody species were primarily found in the western, southern, and eastern regions, whereas the northern and central areas were less favorable for tree growth. Among the scenarios analyzed, SSP585 presents the most extensive distribution area. This study is expected to improve the distribution structure of woody species and the implementation of management policies.

A new framework for making carbon compensation standards considering regional differences at different scales in China

Carbon compensation represents an effective strategy to promote carbon neutrality, address inter-regional inequalities, and support sustainable development. However, existing research on carbon compensation standards often neglects disparities in natural resource endowments and socioeconomic conditions among regions. This study proposes a new framework for making carbon compensation standards that account for regional differences. We explore key factors influencing the Carbon Deficit Index (CDI) and develop carbon compensation standards considering the regional differences of these factors. Carbon compensation amounts are identified and assigned at the three administrative scale: province, city, and county scale in China. The study reveals that between 2000 and 2015, the number of carbon deficit provinces increased from 9 to 21, with a spatial expansion outward from North China as the epicenter. The key factors impacting the CDI include urbanization rate, population, forest area, average annual precipitation, silt content, and soil organic carbon content. By considering regional differences in these key factors, the proposed carbon compensation standards can effectively reduce inter-regional inequalities. These standards can be applied consistently across the three administrative scales. Our findings suggest that carbon compensation standards that take into account regional differences in natural resource endowments，socioeconomic conditions, and payment capacity can enhance the fairness of carbon compensation actions at different scales, providing a valuable reference for the future development of cross-regional carbon compensation policies.

Optimization of vegetation carbon content parameters and their application in carbon storage estimation in China

As a key parameter for C pool and flux assessments, vegetation carbon (C) content can be used in ecological models to predict climate-induced changes in the C sequestration capacity of vegetation. However, the differences in methods for upscaling C content from the organ to the community scale and their impact on regional C stock estimates have been ignored. Based on a comprehensive community structure survey of 72 typical natural ecosystems in China and 27,905 measured samples of plant organs (leaves, twigs, trunks, and roots), we first quantified the differences among scaling-up methods for vegetation C content. These methods included the community or dominant species-weighted mean, geometric mean, arithmetic mean, and traditional empirical coefficients (45 % and 50 %), and their impact on C storage estimation at the regional scale. Comparing the accuracy, variability, and response patterns of the different scaling-up methods, the dominant C species biomass-weighted mean (CDWM) method had the highest similarity to the community-weighted C mean (CCWM) method. Concerning vegetation C storage estimation in China's natural terrestrial ecosystems, the relative errors of the other methods ranged from -2.6 % to 8.22 % compared with that of the CCWM method (18.39 Pg C). The empirical coefficients had the highest uncertainty, with a 45 % empirical coefficient underestimating the vegetation C stock by 2.60 %, and a 50 % empirical coefficient overestimating it by 8.22 %. The CDWM method proposed here has high reliability for C storage estimation (overestimated by only 0.44 %), making it a preferable sampling and scaling-up method for regional C content and stock assessment. Additionally, our study provided the C content of plant organs for China's provinces and typical vegetation types based on the CCWM, which could be used for regional C stock assessment and C cycle models.

Predicting the potential distribution of Astragali Radix in China under climate change adopting the MaxEnt model

Introduction

Astragali Radix is the dried root of Astragalus mongoliae or Astragalus membranaceus, a leguminous plant. Since ancient times, Astragali Radix has been widely used in Chinese traditional Chinese medicine. As people become more health-conscious, the market demand for Astragali Radix grows and its popularity is increasing in the international market. As an important medicinal plant, the growth of Astragali Radix is strongly influenced by environmental conditions. In order to meet the market demand for high quality Astragali Radix herbs, it is necessary to search and find areas suitable for the growth of Astragali Radix.

Methods

In this study, we assessed the potential impacts of climate change on the distribution of the Chinese medicinal plant Astragali Radix using the maximum entropy (MaxEnt) model in combination with a geographic information system(GIS). Distribution data and environmental variables were analyzed to predict suitable areas for Astragali Radix under the SSP126, SSP245 and SSP585 scenario for current and future (2041-2060, 2061-2080, 2081-2100). Jackknife is used to assess the importance of environmental variables, and environmental variables with a model contribution greater than 5% were considered to be the main drivers.

Results

The results showed that the current area of suitable area for Astragali Radix is 188.41 km2, and the three climate scenarios show an increasing trend in the future, with a maximum of 212.70 km2. North China has always been the main suitable area, while the area of suitable area in Southwest China is decreasing, and Xinjiang will be developed as a new suitable area in the future. Annual precipitation (41.6%), elevation (15.9%), topsoil calcium carbonate (14.8%), annual mean temperature (8.3%), precipitation seasonality (8%) and topsoil pH (6%) contributed more to the model and were the main environmental influences on the distribution of Astragali Radix. In addition, the centroids of the suitable areas shifted northward under all three climate scenarios, indicating a migratory response to global warming.

Discussion

Our study found that suitable area of Astragali Radix has been expanding for most of the time in each period of the three climate scenarios compared with the current situation. In the future, humans can focus on enhancing the cultivation techniques of Astragali Radix in these suitable areas. This study provide a scientific basis for the development of planting strategies and spatial distribution management of Astragali Radix. It helps to optimize the selection of planting areas and resource conservation of Chinese herbs.

Particle size is an important factor influencing the effects of biochar return to woodland soils: An evaluation from the perspective of sapling growth and soil microbial carbon processes

Biochar can increase ecosystem carbon sequestration by promoting plant growth and stabilizing soil organic carbon (SOC). Biochar produced from forest waste typically varies in particle size and is frequently applied directly for soil enhancement without pulverization. The effects of different biochar particle sizes on sapling growth, woodland soil properties and microbial carbon processes are unclear. This study used field experiments to compare the effects of different biochar particle sizes on sapling growth and microbial metabolic entropy (qCO2). The impacting mechanisms were explored by examining soil physicochemical properties, enzyme activity, and microbial community structure. The application of forest waste (FW) and small particle biochar (SPBC, particle size<2 mm) did not significantly affect sapling growth. Conversely, middle particle biochar (MPBC, particle size 2-10 mm) and large particle biochar (LPBC, particle size>10 mm) reduced sapling biomass by 20.76% and 38.87%, respectively, compared to SPBC. MPBC and LPBC applications resulted in soil nutrient loss (total nitrogen and available phosphorus), inhibiting sapling growth. After 167 days, qCO2 rankings were as follows: FW (30.37 ± 5.18) (P<0.05)> LPBC (20.91 ± 3.62) > CK (16.21 ± 2.71) > MPBC (15.99 ± 3.54) > SPBC (7.8 ± 0.80) (P < 0.05). The rankings of organic carbon retention rates rankings were as follows: SPBC (85.14%) > LPBC (70.35%) > FW (67.31%) > CK (54.53%) > MPBC (51.96%). SPBC increased biochar-soil-microbe interactions, raised the relative proportion of k/r-strategy bacteria, reduced extracellular cellulase activity thus inhibit qCO2. In conclusion, small particle biochar (<2 mm), compared to larger-particle biochar, improves SOC sequestration without negatively affecting sapling growth. Therefore, particle size should be considered as a management indicator for biochar applications in artificial forest practices.

Assessment of the potential for carbon sink enhancement in the overlapping ecological project areas of China

Ecological engineering can significantly improve ecosystem carbon sequestration. However, few studies have projected the carbon sink trends in regions where ecological engineering projects overlap and have not considered the different climate change conditions and land use scenarios. Using the ensemble empirical mode decomposition method and machine learning algorithms (enhanced boosted regression trees), the aims of this study to elucidate the stability of carbon sinks and their driving mechanisms in areas where ecological projects overlap and to predict the potential enhancement in carbon sinks under varying climate and human activity scenarios. The findings revealed that: (1) The carbon sinks clearly and steadily increased in regions where five ecological projects were implemented from 1982 to 2019. In contrast, the carbon sinks did not significantly increase in regions with two or three ecological projects. (2) As the number of ecological projects increased, the impact of human activities on the carbon sinks gradually decreased. In eastern China, rapid economic development and significant interference from human activities hindered the growth of carbon sinks. In contrast, in western China, the warming and humidification trend of the climate, large-scale afforestation, and other ecological projects have significantly improved carbon sinks. (3) The regions with five overlapping ecological projects exhibited the greatest enhancement and stability of carbon sinks under different scenarios. Compared with the SSP585 scenario, under the SSP126 scenario, the carbon sinks increased, and their stability was greater. Achieving carbon neutrality requires major ecological projects to account for the limitations imposed by climatic conditions. Instead of isolated projects or the implementation of single restoration measures, a comprehensive approach that uses the synergistic effects of combined ecological strategies is recommended.

Ecological restoration enhances dryland carbon stock by reducing surface soil carbon loss due to wind erosion

Enhancing terrestrial carbon (C) stock through ecological restoration, one of the prominent approaches for natural climate solutions, is conventionally considered to be achieved through an ecological pathway, i.e., increased plant C uptake. By conducting a comprehensive regional survey of 4279 1 × 1 m2 plots at 517 sites across China's drylands and a 13-y manipulative experiment in a semiarid grassland within the same region, we show that greater soil and ecosystem C stocks in restored than degraded lands result predominantly from decreased surface soil C loss via suppressed wind erosion. This biophysical pathway is always overlooked in model evaluation of land-based C mitigation strategies. Surprisingly, stimulated plant growth plays a minor role in regulating C stocks under ecological restoration. In addition, the overall enhancement of C stocks in the restored lands increases with both initial degradation intensity and restoration duration. At the national scale, the rate of soil C accumulation (7.87 Tg C y-1) due to reduced wind erosion and surface soil C loss under dryland restoration is equal to 38.8% of afforestation and 56.2% of forest protection in China. Incorporating this unique but largely missed biophysical C-conserving mechanism into land surface models will greatly improve global assessments of the potential of land restoration for mitigating climate change.

Contributions of ecological restoration policies to China's land carbon balance

Unleashing the land sector's potential for climate mitigation requires purpose-driven changes in land management. However, contributions of past management changes to the current global and regional carbon cycles remain unclear. Here, we use vegetation modelling to reveal how a portfolio of ecological restoration policies has impacted China's terrestrial carbon balance through developing counterfactual 'no-policy' scenarios. Pursuing conventional policies and assuming no changes in climate or atmospheric carbon dioxide (CO2) since 1980 would have led China's land sector to be a carbon source of 0.11 Pg C yr-1 for 2001-2020, in stark contrast to a sink of 175.9 Tg C yr-1 in reality. About 72.7% of this difference can be attributed to land management changes, including afforestation and reforestation (49.0%), reduced wood extraction (21.8%), fire prevention and suppression (1.6%) and grassland grazing exclusion (0.3%). The remaining 27.3% come from changes in atmospheric CO2 (42.2%) and climate (-14.9%). Our results underscore the potential of active land management in achieving 'carbon-neutrality' in China.

Dormancy characteristics of lammas-growth seedlings of subtropical trees and their phenological responses to experimental warming

Lammas growth of trees means the additional growth of the shoot after the growth cessation and bud set in late summer. In temperate tree species, lammas growth occurs irregularly and is often regarded as abnormal, disturbed growth. In subtropical tree species, however, lammas growth is a prevalent phenomenon, possibly due to the prolonged occurrence of high temperatures in the autumn. The occurrence of lammas growth extends the growing season of trees, but its influence on subsequent dormancy phenomena and bud burst phenology remains largely unexplored. By comparing seedlings showing lammas growth with others not showing it, we carried out an experimental study of how lammas growth affects the bud burst phenology and the underlying dormancy phenomena under both ambient and controlled chilling, forcing and warming conditions in four subtropical tree species: Carya illinoinensis, Cinnamomum japonicum, Phoebe chekiangensis and Torreya grandis. With the exception of C. illinoinensis, lammas growth delayed bud burst in all the species under ambient conditions. In the chilling experiment, the delayed bud burst appeared to be due to higher minimum forcing requirement, higher dormancy depth, and in T. grandis, also due to lower chilling sensitivity in the lammas-growth seedlings than in the non-lammas-growth ones. However, a spring warming experiment showed that the sensitivity of bud burst to spring temperatures was higher in the lammas-growth seedlings than in the non-lammas-growth ones. Because of this, the difference between the two phenotypes in the timing of bud burst vanished with increasing warming. Our findings elucidate the significant impact of lammas growth on the dormancy dynamics of subtropical tree species, highlighting the necessity to better understand how the physiological phenomena causing lammas growth change the trees' subsequent environmental responses under changing climatic conditions.

Attenuated asymmetry of above- versus belowground stoichiometry to a decadal nitrogen addition during stand development

Deciphering the linkage between ecological stoichiometry and ecosystem functioning under anthropogenic nitrogen (N) deposition is critical for understanding the impact of afforestation on terrestrial carbon (C) sequestration. However, the specific changes in above- versus belowground stoichiometric asymmetry with stand age in response to long-term N addition remain poorly understood. In this study, we investigated changes in stoichiometry following a decadal addition of three levels of N (control, no N addition; low N addition, 20 kg N ha-1 year-1; high N addition, 50 kg N ha-1 year-1) in young, intermediate, and mature stands in three temperate larch plantations (Larix principis-rupprechtii) in North China. We found that low N addition had no impact on both above- (leaf and litter) and belowground (soil and microbe) stoichiometry. In contrast, high N addition resulted in significant asymmetry in above- versus belowground stoichiometry, which then diminished during stand development. Following 10 years of N inputs, the young and intermediate plantations transitioned from a state of relative N limitation to co-limitation by both N and phosphorus (P), whereas the mature plantation continued to experience relative N limitation. Conversely, soil microorganisms exhibited relative P limitation in all three plantations. Broader niche differentiation (N limitation for trees, but P limitation for microorganisms) under long-term N input may have been responsible for the faster attainment of stoichiometric homeostasis in mature plantations than in young plantations. Our findings provide stoichiometric-based insight into the operating mechanisms of large C sinks in young forests, particularly above- versus belowground C stock asymmetry, and highlight the need to consider the role of flexible stoichiometry when forecasting future forest C sinks.

Integrating both restoration and regeneration potentials into real-world forest restoration planning: A case study of Hong Kong

Forest restoration is a vital nature-based solution for mitigating climate change and land degradation. To ensure restoration effectiveness, the costs and benefits of alternative restoration strategies (i.e., active restoration vs. natural regeneration) need to be evaluated. Existing studies generally focus on maximum restoration potential, neglecting the recovery potential achievable through natural regeneration processes, leading to incomplete understanding of the true benefits and doubts about the necessity of active restoration. In this study, we introduce a multi-stage framework incorporating both restoration and regeneration potential into prioritized planning for ecosystem restoration. We used the vegetated landscape of Hong Kong (covering 728 km2) as our study system due to its comprehensive fine-resolution data and unique history of vegetation recovery, making it an ideal candidate to demonstrate the importance of this concept and inspire further research. We analyzed vegetation recovery status (i.e., recovering, degrading, and stable) over the past decade based on the canopy height data derived from multi-temporal airborne LiDAR. We assessed natural regeneration potential and maximum restoration potential separately, producing spatially-explicit predictions. Our results show that 44.9% of Hong Kong's vegetated area has showed evidence of recovery, but remaining gains through natural regeneration are limited, constituting around 4% of what could be attained through active restoration. We further estimated restoration priority by maximizing the restoration gain. When prioritizing 5% of degraded areas, the increment in canopy height could be up to 10.9%. Collectively, our findings highlight the importance of integrating both restoration and regeneration potential into restoration planning. The proposed framework can aid policymakers and land managers in optimizing forest restoration options and promoting the protection and recovery of fragile ecosystems.

Substantial nitrogen abatement accompanying decarbonization suppresses terrestrial carbon sinks in China

China faces challenges in reaching its carbon neutrality goal by the year 2060 to meet the Paris Agreement and improving air quality simultaneously. Dramatic nitrogen emission reductions will be brought by this ambitious target, yet their impact on the natural ecosystem is not clear. Here, by combining two atmospheric chemistry models and two process-based terrestrial ecosystem models constrained using nationwide measurements, we show that atmospheric nitrogen deposition in China's terrestrial land will decrease by 44-57% following two emission control scenarios including one aiming at carbon neutrality. They consequently result in a pronounced shrinkage in terrestrial net ecosystem production, by 11-20% depending on models and emission scenarios. Our results indicate that the nitrogen emission reductions accompanying decarbonization would undermine natural carbon sinks and in turn set back progress toward carbon neutrality. This unintended impact calls for great concern about the trade-offs between nitrogen management and carbon neutrality.

Multi-model assessment of potential natural vegetation to support ecological restoration

Ecological restoration is imperative for controlling desertification. Potential natural vegetation (PNV), the theoretical vegetation succession state, can guides near-natural restoration. Although a rising transition from traditional statistical methods to advanced machine learning and deep learning is observed in PNV simulation, a comprehensive comparison of their performance is still unexplored. Therefore, we overview the performance of PNV mapping in terms of 12 commonly used methods with varying spatial scales and sample sizes. Our findings indicate that the methodology should be carefully selected due to the variation in performance of different model types, with Area Under the Curve (AUC) values ranging from 0.65 to 0.95 for models with sample sizes up to 80% of the total sample size. Specifically, semi-supervised learning performs best with small sample sizes (i.e., 10 to 200), while Random Forest, XGBoost, and artificial neural networks perform better with large sample sizes (i.e., over 500). Further, the performance of all models tends to improve significantly as the sample size increases and the grain size of the crystals becomes smaller. Take the downstream Tarim River Basin, a hyper-arid region undergoing ecological restoration, as a case study. We showed that its potential restored areas were overestimated by 2-3 fold as the spatial scale became coarser, revealing the caution needed while planning restoration projects at coarse resolution. These findings enhance the application of PNV in the design of restoration programs to prevent desertification.

Large potential of strengthening the land carbon sink in China through anthropogenic interventions

The terrestrial ecosystem in China mitigates 21%-45% of the national contemporary fossil fuel CO2 emissions every year. Maintaining and strengthening the land carbon sink is essential for reaching China's target of carbon neutrality. However, this sink is subject to large uncertainties due to the joint impacts of climate change, air pollution, and human activities. Here, we explore the potential of strengthening land carbon sink in China through anthropogenic interventions, including forestation, ozone reduction, and litter removal, taking advantage of a well-validated dynamic vegetation model and meteorological forcings from 16 climate models. Without anthropogenic interventions, considering Shared Socioeconomic Pathways (SSP) scenarios, the land sink is projected to be 0.26-0.56 Pg C a-1 at 2060, to which climate change contributes 0.06-0.13 Pg C a-1 and CO2 fertilization contributes 0.08-0.44 Pg C a-1 with the stronger effects for higher emission scenarios. With anthropogenic interventions, under a close-to-neutral emission scenario (SSP1-2.6), the land sink becomes 0.47-0.57 Pg C a-1 at 2060, including the contributions of 0.12 Pg C a-1 by conservative forestation, 0.07 Pg C a-1 by ozone pollution control, and 0.06-0.16 Pg C a-1 by 20% litter removal over planted forest. This sink can mitigate 90%-110% of the residue anthropogenic carbon emissions in 2060, providing a solid foundation for the carbon neutrality in China.

Increased ecological land and atmospheric CO2 dominate the growth of ecosystem carbon sinks under the regulation of environmental conditions in national key ecological function zones in China

Increased ecological land (IEL) such as forests and grasslands can greatly enhance ecosystem carbon sinks. Understanding the mechanisms for the magnitude of IEL-induced ecosystem carbon sinks is crucial for achieving carbon neutrality. We estimated the impact of IEL, specifically the increase in forests and grasslands, as well as global changes including atmospheric CO2 concentration, nitrogen deposition, and climate change on net ecosystem productivity (NEP) in National Key Ecological Function Zones (NKEFZs) in China using a calibrated ecological process model. The NEP in NKEFZs in China was calculated to be 119.4 Tg C yr-1, showing an increase of 42.6 Tg C yr-1 from 2001 to 2021. Compared to the slight contributions of climate change (-8.0%), nitrogen deposition (11.5%), and reduction in ecological land (-3.5%), the increase in NEP was primarily attributed to CO2 (66.5%) and IEL (33.5%). Moreover, the effect of IEL (14.8 Tg C yr-1) surpassed that of global change (13.1 Tg C yr-1) in the land use change zone. The IEL-induced NEP is significantly associated with CO2 fertilization, regulated by precipitation and nitrogen deposition. The high values of IEL-induced NEP occurred in areas with precipitation exceeding 800 mm and nitrogen deposition exceeding 25 kg N ha-1 yr-1. We recommend prioritizing the expansion of ecological land in areas with sufficient water and nutrients to enhance CO2 fertilization, while avoiding increasing ecological land in regions facing unfavorable climate change conditions. This study serves as a foundation for comprehending the NEP response to ecological restoration and global change.

Impact of greening trends on biogenic volatile organic compound emissions in China from 1985 to 2022: Contributions of afforestation projects

The rapid expansion of green areas in China has enhanced carbon sinks, but it also presents challenges regarding increased biogenic volatile organic compound (BVOC) emissions. This study examines the impact of greening trends on BVOC emissions in China from 1985 to 2001 and from 2001 to 2022, focusing on evaluating long-term trends in BVOC emissions within eight afforestation project areas during these two periods. Emission factors for 62 dominant tree species and provincial Plant Functional Types were updated. The BVOC emission inventories were developed for China at a spatial resolution of 27 km × 27 km using the Model of Emissions of Gases and Aerosols from Nature. The national BVOC emissions in 2018 were estimated at 54.24 Tg, with isoprene, monoterpenes, sesquiterpenes, and other BVOC contributing 26.94 Tg, 2.29 Tg, 0.44 Tg, and 24.57 Tg, respectively. Over the past 37 years, BVOC emissions experienced a slow growth rate of 1.7 % (0.79 Tg) during 1985-2001, followed by a significant increase of 12 % (6 Tg) from 2001 to 2022. BVOC emissions in the eight afforestation project areas increased by 2 % and 20 % during the two periods. From 2001 to 2022, at the regional scale, the Shelterbelt program for the middle reaches of the Yellow River area exhibited the largest rate of increase (43 %) in BVOC emissions. The Shelterbelt program for the upper and middle reaches of the Yangtze River made the most largest contribution (45 %) to the national increase in BVOC emissions. Afforestation projects have shifted towards planting more broadleaf trees than needleleaf trees from 2001 to 2022, and there also showed a change from herbaceous plants to broadleaf trees. These trends have led to higher average emission factors for vegetation, resulting in increased BVOC emissions. It underscores the importance of considering BVOC emissions when evaluating afforestation initiatives, emphasizing the need to balancing ecological benefits with potential atmospheric consequences.

The Long-Term Effects of Barren Land Afforestation on Plant Productivity, Soil Fertility, and Soil Moisture in China: A Meta-Analysis

As global ecological degradation intensifies, the long-term impacts of afforestation on productivity and soil fertility in barren lands have become critical in improving global ecological security and productivity. Through meta-analysis, this study integrates data from 109 barren land afforestation sites across China, aiming to comprehensively analyze the effects on plant productivity and soil fertility while identifying the key environmental drivers of these changes. We found that afforestation consistently enhances plant productivity across 60 years. However, soil fertility and moisture initially surged significantly after afforestation but gradually declined after the first decade, indicating the limited long-term benefits. Climatic factors, namely precipitation and humidity index, are crucial in enhancing plant productivity, while geographic factors, specifically lower elevations and gentler slopes, are associated with greater increases in soil fertility. Elevation and slope are two key factors that influence soil moisture after afforestation. These findings highlight the need for ongoing soil management and ecological maintenance in afforestation projects to sustain the soil fertility benefits. Our study provides a robust scientific foundation for afforestation strategies aimed at barren land restoration and offers valuable insights for policy formulation in barren land afforestation.

Stability in change: building a stable ecological security pattern in Northeast China under climate and land use changes

Climate change and land use change caused by human activities have a profound impact on ecological security. Simulating the spatio-temporal changes in ecosystem service value and ecological security patterns under different carbon emission scenarios in the future is of great significance for formulating sustainable development policies. This study quantified the four major ecosystem services (habitat quality, water retention, soil erosion, and carbon storage) in Northeast China (NC), identified ecological source areas, and constructed a stable ecological security pattern. The results show that the spatial patterns of soil erosion, carbon storage, water retention, and habitat quality, the four major ecosystem services in NC, are relatively stable in the next 30 years, and there is no significant difference from the current spatial pattern distribution. The SSP1-2.6 carbon emission scenario is a priority model for the development of NC in the next 30 years. In this carbon emission scenario, the NC has the largest ecological resources (191,177 km2) and the least comprehensive resistance value (850.006 × 10-4). At the same time, the relative resistance of the corridor in this scenario is the smallest, and the area of the mandatory reserve pinch points is the least. The ecological corridors in the SSP1-2.6 scenario form a network distribution among the ecological sources, connecting several large ecological sources as a whole. This study fills the knowledge gap in building a stable ecological security pattern in NC under the background of global change, and provides a scientific basis for the decision-making of regional ecological security and land resource management.

Forest carbon storage and sink estimates under different management scenarios in China from 2020 to 2100

Forests play a crucial role in mitigating climate change through carbon storage and sequestration, though environmental change drivers and management scenarios are likely to influence these contributions across multiple spatial and temporal scales. In this study, we employed three tree growth models-the Richard, Hossfeld, and Korf models-that account for the biological characteristics of trees, alongside national forest inventory (NFI) datasets from 1994 to 2018, to evaluate the carbon sink potential of existing forests and afforested regions in China from 2020 to 2100, assuming multiple afforestation and forest management scenarios. Our results indicate that the Richard, Hossfeld, and Korf models provided a good fit for 26 types of vegetation biomass in both natural and planted Chinese forests. These models estimate that in 2020, carbon stocks in existing Chinese forests are 7.62 ± 0.05 Pg C, equivalent to an average of 44.32 ± 0.32 Mg C/ ha. Our predictions then indicate this total forest carbon stock is expected to increase to 15.51 ± 0.99 Pg C (or 72.26 ± 4.6 Mg C/ha) in 2060, and further to 19.59 ± 1.36 Pg C (or 91.31 ± 6.33 Mg C/ha) in 2100. We also show that plantation management measures, namely tree species replacement, would increase carbon sinks to 0.09 Pg C/ year (contributing 38.9 %) in 2030 and 0.06 Pg C/ year (contributing 32.4 %) in 2060. Afforestation using tree species with strong carbon sink capacity in existing plantations would further significantly increase carbon sinks from 0.02 Pg C/year (contributing 10.3 %) in 2030 to 0.06 Pg C/year (contributing 28.2 %) in 2060. Our results quantify the role plantation management plays in providing a strong increase in forest carbon sequestration at national scales, pointing to afforestation with native tree species with high carbon sequestration as key in achieving China's 2060 carbon neutrality target.

Carbon pools in forest systems and new estimation based on an investigation of carbon sequestration

Forests, the ancient wooden giants, are both symbols of natural beauty and reservoirs of carbon stocks. The current climate crisis has created an urgent need for an in-depth study of forest ecosystems and carbon stocks. Based on forest inventory data from field surveys and four bioclimatic zones [Zone 1 (Z1, humid forest), Zone 2 (Z2, semi-humid forest), Zone 3 (Z3, semi-humid to semi-arid forest-grassland), and Zone 4 (Z4, semi-arid typical grassland)], two methods [Method 1 (M1) and Method 2 (M2)] were used to estimate carbon stocks in forest ecosystems in Shaanxi Province, China, and explored the spatial patterns of carbon pools and potential influences. The total forest ecosystem carbon pool amounted to 520.80 Tg C, of which 53.60% was stored aboveground, 17.16% belowground, and 29.24% in soil (depth of 0-10 cm). Spatially, there were marked north-south gradients in both biomass (Z2 > Z3 > Z1 > Z4) and soil organic carbon densities (Z1 > Z2 > Z3 > Z4). The differences between aboveground and belowground biomass carbon density across broadleaf, needle-leaf, and broadleaf and needle-leaf mixed forest were not pronounced, while soil organic carbon density had the order of broadleaf (18.38 Mg C/ha) > needle-leaf (11.29 Mg C/ha) > broadleaf and needle-leaf mixed forest (10.33 Mg C/ha). Under an ideal scenario that excludes external factors, mainly forest growth, the sequestration potential of forest biomass by 2032 was estimated by M1 as 85.43 Tg, and by M2 to be substantially higher at 176.21 Tg. As of 2062, M1 estimated 155.97 Tg of sequestration potential for forest biomass. The spatial patterns of forest biomass and soil carbon density were closely related to climatic factors, and these relationships allowed the spatial division into two distinct climatic regions. Moreover, biomass carbon density was significantly correlated with the normalized difference vegetation index, soil silt, and elevation. This study provides key information for promoting the strategic shift from light-green to deep-green forest systems in Shannxi Province and updates the estimation methods of forest ecosystems' carbon pools based on field surveys.

Carbon storage through China's planted forest expansion

China's extensive planted forests play a crucial role in carbon storage, vital for climate change mitigation. However, the complex spatiotemporal dynamics of China's planted forest area and its carbon storage remain uncaptured. Here we reveal such changes in China's planted forests from 1990 to 2020 using satellite and field data. Results show a doubling of planted forest area, a trend that intensified post-2000. These changes lead to China's planted forest carbon storage increasing from 675.6 ± 12.5 Tg C in 1990 to 1,873.1 ± 16.2 Tg C in 2020, with an average rate of ~ 40 Tg C yr-1. The area expansion of planted forests contributed ~ 53% (637.2 ± 5.4 Tg C) of the total above increased carbon storage in planted forests compared with planted forest growth. This proactive policy-driven expansion of planted forests has catalyzed a swift increase in carbon storage, aligning with China's Carbon Neutrality Target for 2060.

Importance of soil moisture conservation in mitigating climate change

A troubling feedback loop, where drier soil contributes to hotter climates, has been widely recognized. This study, drawing on climate model simulations, reveals that maintaining current global soil moisture levels could significantly alleviate 32.9% of land warming under low-emission scenarios. This action could also postpone reaching critical warming thresholds of 1.5 °C and 2.0 °C by at least a decade. Crucially, preserving soil moisture at current levels could prevent noticeable climate change impacts across 42% of the Earth's land, a stark deviation from projections suggesting widespread impacts before the 2060s. To combat soil drying, afforestation in mid-to-low latitude regions within the next three decades is proposed as an effective strategy to increase surface water availability. This underscores the substantial potential of nature-based solutions for managing soil moisture, benefiting both climate change mitigation and ecological enhancement.

Maximizing carbon sequestration potential in Chinese forests through optimal management

Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1-3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement.

Responses of streamflow to forest expansion in a typical subhumid watershed under future climate conditions

Water availability in the subhumid region is highly vulnerable to frequent droughts. Water scarcity in this region has become a limiting factor for ecosystem health, human livelihood, and regional economic development. A notable pattern of land cover change in the subhumid region of the United States is the increasing forest area due to afforestation/reforestation and woody plant encroachment (WPE). Given the distinct hydrological processes and runoff generation between forests and grasslands, it is important to evaluate the impacts of forest expansion on water resources, especially under future climate conditions. In this study, we focused on a typical subhumid watershed in the United States - the Little River Watershed (LRW). Utilizing SWAT + simulations, we projected streamflow dynamics at the end of the 21st century in two climate scenarios (RCP45 and RCP85) and eleven forest expansion scenarios. In comparison to the period of 2000-2019, future climate change during 2080-2099 will increase streamflow in the Little River by 5.1% in the RCP45 but reduce streamflow significantly by 30.1% in the RCP85. Additionally, our simulations revealed a linear decline in streamflow with increasing forest coverage. If all grasslands in LRW were converted into forests, it would lead to an additional 41% reduction in streamflow. Of significant concern is Lake Thunderbird, the primary reservoir supplying drinking water to the Oklahoma City metropolitan area. Our simulation showed that if all grasslands were replaced by forests, Lake Thunderbird during 2080-2099 would experience an average of 8.6 years in the RCP45 and 9.4 years in the RCP85 with water inflow amount lower than that during the extreme drought event in 2011/2012. These findings hold crucial implications for the formulation of policies related to afforestation/reforestation and WPE management in subhumid regions, which is essential to ensuring the sustainability of water resources.