Plant height as an indicator for alpine carbon sequestration and ecosystem response to warming.

Growing evidence indicates that plant community structure and traits have changed under climate warming, especially in cold or high-elevation regions. However, the impact of these warming-induced changes on ecosystem carbon sequestration remains unclear. Using a warming experiment on the high-elevation Qinghai-Tibetan Plateau, we found that warming not only increased plant species height but also altered species composition, collectively resulting in a taller plant community associated with increased net ecosystem productivity (NEP). Along a 1,500 km transect on the Plateau, taller plant community promoted NEP and soil carbon through associated chlorophyll content and other photosynthetic traits at the community level. Overall, plant community height as a dominant trait is associated with species composition and regulates ecosystem C sequestration in the high-elevation biome. This trait-based association provides new insights into predicting the direction, magnitude and sensitivity of ecosystem C fluxes in response to climate warming.

Vertical structural complexity of plant communities represents the combined effects of resource acquisition and environmental stress on the Tibetan Plateau.

The vertical structural complexity (VSC) of plant communities reflects the occupancy of spatial niches and is closely related to resource utilization and environmental adaptation. However, understanding the large-scale spatial pattern of VSC and its underlying mechanisms remains limited. Here, we systematically investigate 2013 plant communities through grid sampling on the Tibetan Plateau. VSC is quantified as the maximum plant height within a plot (Height-max), coefficient of variation of plant height (Height-var), and Shannon evenness of plant height (Height-even). Precipitation dominates the spatial variation in VSC in forests and shrublands, supporting the classic physiological tolerance hypothesis. In contrast, for alpine meadows, steppes, and desert grasslands in extreme environments, non-resource limiting factors (e.g., wide diurnal temperature ranges and strong winds) dominate VSC variation. Generally, with the shifting of climate from favorable to extreme, the effect of resource availability gradually decreases, but the effect of non-resource limiting factors gradually increases, and that the physiological tolerance hypothesis only applicable in favorable conditions. With the help of machine learning models, maps of VSC at 1-km resolution are produced for the Tibetan Plateau. Our findings and maps of VSC provide insights into macroecological studies, especially for adaptation mechanisms and model optimization.

Adaptation mechanisms of leaf vein traits to drought in grassland plants.

Leaf veins play an important role in water transport, and are closely associated with photosynthesis and transpiration. Resource heterogeneity in the environment, particularly in water resources, causes changes in leaf vein structure and function, thereby affecting plant growth and community assemblages. Therefore, it is necessary to explore the spatial variation and evolutionary mechanisms of leaf veins in natural communities. Natural communities are composed of dominant and non-dominant species. However, few studies to date have explored the trait variation of dominant and non-dominant species on a large scale. In this study, we set up 10 sampling sites along the water gradient (from east to west) in the Loess Plateau of China, and measured and calculated the vein density (vein length per unit area, VLA), vein diameter (VD), and vein volume ratio (VVR) of 173 species, including dominant and non-dominant species. The mean values of VLA, VD, and VVR were 10.95 mm mm-2, 22.24 µm, and 3%, respectively. VD and VVR of the dominant species were significantly higher than those of the non-dominant species. Unexpectedly, there was no significant change in the VLA with the water gradient, although the VD increased with drought. Leaf vein traits did not change significantly with evolution. There was a significant trade-off between VLA and VD. Our findings demonstrate that the response of veins to environmental changes is dependent on the degree of drought and provide new insights for further large-scale studies.

Relationships of stomatal morphology to the environment across plant communities.

The relationship between stomatal traits and environmental drivers across plant communities has important implications for ecosystem carbon and water fluxes, but it has remained unclear. Here, we measure the stomatal morphology of 4492 species-site combinations in 340 vegetation plots across China and calculate their community-weighted values for mean, variance, skewness, and kurtosis. We demonstrate a trade-off between stomatal density and size at the community level. The community-weighted mean and variance of stomatal density are mainly associated with precipitation, while that of stomatal size is mainly associated with temperature, and the skewness and kurtosis of stomatal traits are less related to climatic and soil variables. Beyond mean climate variables, stomatal trait moments also vary with climatic seasonality and extreme conditions. Our findings extend the knowledge of stomatal trait-environment relationships to the ecosystem scale, with applications in predicting future water and carbon cycles.

China's current forest age structure will lead to weakened carbon sinks in the near future.

Forests are chiefly responsible for the terrestrial carbon sink that greatly reduces the buildup of CO2 concentrations in the atmosphere and alleviates climate change. Current predictions of terrestrial carbon sinks in the future have so far ignored the variation of forest carbon uptake with forest age. Here, we predict the role of China's current forest age in future carbon sink capacity by generating a high-resolution (30 m) forest age map in 2019 over China's landmass using satellite and forest inventory data and deriving forest growth curves using measurements of forest biomass and age in 3,121 plots. As China's forests currently have large proportions of young and middle-age stands, we project that China's forests will maintain high growth rates for about 15 years. However, as the forests grow older, their net primary productivity will decline by 5.0% ± 1.4% in 2050, 8.4% ± 1.6% in 2060, and 16.6% ± 2.8% in 2100, indicating weakened carbon sinks in the near future. The weakening of forest carbon sinks can be potentially mitigated by optimizing forest age structure through selective logging and implementing new or improved afforestation. This finding is important not only for the global carbon cycle and climate projections but also for developing forest management strategies to enhance land sinks by alleviating the age effect.

Maximum potential of vegetation carbon sink in Chinese forests.

Forest vegetation is essential in sequestering carbon dioxide (CO2) from the atmosphere and mediating global warming. The carbon (C) sink potential of forest vegetation in different provinces is vital for policymakers to develop C-neutral technical routes and regional priorities in China; however, the mechanism remains unclear. In this study, we compiled the public data on forest vegetation biomass or storage along forest succession series between 2003 and 2022 and obtained the spatial variation of the maximum C storage(BCmax) of forest vegetation using classic logistic equation and nonlinear fitting. Furthermore, the C sink potential (∆Cpot) of the Chinese forest vegetation was calculated based on the differences between the BCmax and intensive field-investigated data in the 2010s. The results showed that the BCmax in the Chinese forest vegetation was approximately 19.03 Pg. The BCmax in southwest and northeast China were higher than those in other regions. The ∆Cpot was estimated as 8.83 Pg. Moreover, 1 km × 1 km spatial raster data for ∆Cpot were produced using the spatial raster calculation. Similarly, the per capita ∆Cpot of regions with low economic development (southwest, central, and southern Chinese provinces) were five to ten times higher than those of regions with a higher economic level. The ∆Cpot correlated negatively with gross domestic product (GDP)across all Chinese provinces. Our findings provide new insights into the ∆Cpot of the Chinese forest vegetation under natural restoration and emphasize that some differences in financial and political support among different provinces facilitate achieving a large ∆Cpot for C neutrality.

Soil carbon sequestration potential of cultivated lands and its controlling factors in China.

Understanding soil organic carbon (SOC) stocks and carbon sequestration potential in cultivated lands can have significant benefit for mitigating climate change and emission reduction. However, there is currently a lack of spatially explicit information on this topic in China, and our understanding of the factors that influence both saturated SOC level (SOCS) and soil organic carbon density (SOCD) remains limited. This study predicted SOCS and SOCD of cultivated lands across mainland China based on point SOC measurements, and mapped its spatial distribution using environmental variables as predictors. Based on the differentiation between SOCS and SOCD, the soil organic carbon sequestration potentials (SOCP) of cultivated land were calculated. Boosted regression trees (BRT), random forest (RF), and support vector machine (SVM) were evaluated as prediction models, and the RF model presented the best performance in predicting SOCS and SOCD based on 10-fold cross-validation. A total of 991 topsoil (0-20 cm) SOC measurements and 12 environmental variables explaining topography, climate, organism, soil properties, and human activity were used as predictors in the model. Both SOCS and SOCD suggested higher SOC levels in northeast China and lower levels in central China. The cultivated lands in China had the potential to sequester about 2.13 ± 0.96 kg m-2 (3.25 Pg) SOC in the top 20 cm soil depth. Northeastern China had the largest SOCP followed by Northern China, and Southwestern China had the lowest SOCP. The primary environmental variables that affected the spatial variation of SOCS were mean annual temperature, followed by clay content and normalized difference vegetation index (NDVI). The assessment and mapping of SOCP in China's cultivated lands holds significance importance as it can provide valuable insights to policymakers and researchers about SOCP, and aid in formulating climate change mitigation strategies.

High-resolution maps of vegetation nitrogen density on the Tibetan Plateau: An intensive field-investigation.

Nitrogen (N) is a vital macronutrient in plant growth and development that plays a crucial role in the regulation of numerous physiological processes. The Tibetan Plateau is among the most species-diverse vegetation zones in the world, and is sensitive to climate change; however, research on vegetation N in the region remains limited. This study used field grid-sampling of 2040 plant communities to investigate the spatial variation and driving factors of vegetation N on the Tibetan Plateau. The results yielded an average N content, density and storage in vegetation of 8.48 mg g-1, 27.02 g m-2, and 29.84Tg, respectively. The ratio-based optimal partitioning hypothesis appears to be more suitable than the isometric allocation hypothesis to explain variation in vegetation N on the Tibetan Plateau. Variation in vegetation N density, was influenced by several environmental factors of which the most significant was radiation. Based on these results, a Random Forest model was used to predict a N density distribution map at 1 km resolution, achieving an accuracy (R2) of 0.72 (aboveground N density), 0.61 (belowground N density), and 0.69 (total vegetation N density). Trends for high densities were predicted in the southeast and low densities in the northwest of the region. Our findings and maps could be used to provide key N cycle parameters, contributing to future remote sensing, radar analyses, modeling and ecological management.

Atmospheric wet organic nitrogen deposition in China: Insights from the national observation network.

Organic nitrogen (N) is an important component of atmospheric reactive N deposition, and its bioavailability is almost as important as that of inorganic N. Currently, there are limited reports of national observations of organic N deposition; most stations are concentrated in rural and urban areas, with even fewer long-term observations of natural ecosystems in remote areas. Based on the China Wet Deposition Observation Network, this study regularly collected monthly wet deposition samples from 43 typical ecosystems from 2013 to 2021 and measured related N concentrations. The aim was to provide a more comprehensive assessment of the multi-component characteristics of atmospheric wet N deposition and reveal the influencing factors and potential sources of wet dissolved organic N (DON) deposition. The results showed that atmospheric wet deposition fluxes of NO3-, NH4+, DON and dissolved total N (DTN) were 4.68, 5.25, 4.32, and 13.05 kg N ha-1 yr-1, respectively, and that DON accounted for 30 % of DTN deposition (potentially up to 50 % in remote areas). Wet DON deposition was related to anthropogenic emissions (agriculture, biomass burning, and traffic), natural emissions (volatile organic compound emissions from vegetation), and precipitation processes. The wet DON deposition flux was higher in South, Central, and Southwest China, with more precipitation and intensive agricultural activities or more vegetation cover, and lower in Northwest China and Inner Mongolia, with less precipitation and human activities or vegetation cover. DON was the main contributor to DTN deposition in remote areas and was possibly related to natural emissions. In rural and urban areas, DON may have been more influenced by agricultural activities and anthropogenic emissions. This study quantified the long-term spatiotemporal patterns of wet N deposition and provides a reference for future N addition experiments and N cycle studies. Further consideration of DON deposition is required, especially in the context of anthropogenic control of NO2 and NH3.

Spatial-temporal variation of the carbon sequestration rate of afforestation in China: Implications for carbon trade and planning.

Afforestation and reforestation (A&R) are nature-based and cost-effective solutions for enhancing terrestrial carbon sinks and facilitating faster carbon neutrality. However, the lack of hierarchical spatial-temporal maps for the carbon sequestration rate (CSR) from A&R at the national scale impedes the scientific implementation of forest management planning to a large extent. Here, we assessed the spatial-temporal CSR per area for A&R at the provincial, prefectural, and county levels in China using a forest carbon sequestration model under three climate scenarios. Results showed that the CSR of vegetation (CSRVeg), soil (CSRSoil), and the ecosystem (CSREco) significantly varied across space and time. In China, the CSRVeg, CSRSoil, and CSREco were primarily regulated by the spatial variations in temperature and precipitation. Additionally, CSRVeg was found to be positively influenced by precipitation and temperature, whereas temperature had a negative influence on CSRSoil. Therefore, the differences between the CSRVeg and CSRSoil should be emphasized in the future. These information on the spatiotemporal variation of CSR of A&R (vegetation, soil, and ecosystem) on unit area basis and at levels of province, prefecture, and county in China, can be used as a comparable protocol to estimate the carbon sinks of A&R at different scales. Overall, these hierarchical spatiotemporal maps for CSR on A&R may help to identify priority areas of forest management planning and carbon trade policy to achieve faster carbon neutrality for China in the future.

The essential role of biodiversity in the key axes of ecosystem function.

Biodiversity is essential for maintaining the terrestrial ecosystem multifunctionality (EMF). Recent studies have revealed that the variations in terrestrial ecosystem functions are captured by three key axes: the maximum productivity, water use efficiency, and carbon use efficiency of the ecosystem. However, the role of biodiversity in supporting these three key axes has not yet been explored. In this study, we combined the (i) data collected from more than 840 vegetation plots across a large climatic gradient in China using standard protocols, (ii) data on plant traits and phylogenetic information for more than 2,500 plant species, and (iii) soil nutrient data measured in each plot. These data were used to systematically assess the contribution of environmental factors, species richness, functional and phylogenetic diversity, and community-weighted mean (CWM) and ecosystem traits (i.e., traits intensity normalized per unit land area) to EMF via hierarchical partitioning and Bayesian structural equation modeling. Multiple biodiversity attributes accounted for 70% of the influence of all the variables on EMF, and ecosystems with high functional diversity had high resource use efficiency. Our study is the first to systematically explore the role of different biodiversity attributes, including species richness, phylogenetic and functional diversity, and CWM and ecosystem traits, in the key axes of ecosystem functions. Our findings underscore that biodiversity conservation is critical for sustaining EMF and ultimately ensuring human well-being.

Integrating multiple plant functional traits to predict ecosystem productivity.

Quantifying and predicting variation in gross primary productivity (GPP) is important for accurate assessment of the ecosystem carbon budget under global change. Scaling traits to community scales for predicting ecosystem functions (i.e., GPP) remain challenging, while it is promising and well appreciated with the rapid development of trait-based ecology. In this study, we aim to integrate multiple plant traits with the recently developed trait-based productivity (TBP) theory, verify it via Bayesian structural equation modeling (SEM) and complementary independent effect analysis. We further distinguish the relative importance of different traits in explaining the variation in GPP. We apply the TBP theory based on plant community traits to a multi-trait dataset containing more than 13,000 measurements of approximately 2,500 species in Chinese forest and grassland systems. Remarkably, our SEM accurately predicts variation in annual and monthly GPP across China (R2 values of 0.87 and 0.73, respectively). Plant community traits play a key role. This study shows that integrating multiple plant functional traits into the TBP theory strengthens the quantification of ecosystem primary productivity variability and further advances understanding of the trait-productivity relationship. Our findings facilitate integration of the growing plant trait data into future ecological models.

High environmental costs behind rapid economic development: Evidence from economic loss caused by atmospheric acid deposition.

The rapid growth of energy-intensive and high-emission industries has propelled China's economy but has also led to massive levels of air pollutant emissions and ecological problems, such as acid deposition. Despite recent declines, atmospheric acid deposition in China is still severe. Long-term exposure to high levels of acid depositions has a substantial negative impact on the ecosystem. Evaluating these hazards and incorporating this issue into planning and decision-making processes is critical to achieving sustainable development goals in China. However, the long-term economic loss caused by atmospheric acid deposition and its temporal and spatial variation in China is unclear. Hence, the aim of this study was to assess the environmental cost of acid deposition in the agriculture, forestry, construction, and transportation industries from 1980 to 2019, using long-term monitoring, integrated data, and the dose-response method with localization parameters. The results showed that the estimated cumulative environmental cost of acid deposition was USD 230 billion, representing 0.27% of the gross domestic product (GDP) in China. This cost, was particularly high for building materials, followed by crops, forests, and roads. Temporally, the environmental cost and the ratio of environmental cost to GDP decreased from their peaks by 43% and 91%, respectively, because of emission controls targeting acidifying pollutants and promotion of clean energy. Spatially, the largest environmental cost occurred in developing provinces, indicating that more stringent emission reduction measures should be implemented in these regions. These findings highlight the huge environmental costs behind rapid development; however, the implementation of reasonable emission reduction measures can effectively reduce these environmental costs, providing a promising paradigm for other undeveloped and developing countries.

Divergent response and adaptation of specific leaf area to environmental change at different spatio-temporal scales jointly improve plant survival.

Specific leaf area (SLA) is one of the most important plant functional traits. It integrates multiple functions and reflects strategies of plants to obtain resources. How plants employ different strategies (e.g., through SLA) to respond to dynamic environmental conditions remains poorly understood. This study aimed to explore the spatial variation in SLA and its divergent adaptation through the lens of biogeographic patterns, evolutionary history, and short-term responses. SLA data for 5424 plant species from 76 natural communities in China were systematically measured and integrated with meta-analysis of field experiments (i.e., global warming, drought, and nitrogen addition). The mean value of SLA across all species was 21.8 m2  kg-1 , ranging from 0.9 to 110.2 m2  kg-1 . SLA differed among different ecosystems, temperature zones, vegetation types, and functional groups. Phylogeny had a weak effect on SLA, but plant species evolved toward higher SLA. Furthermore, SLA responded nonlinearly to environmental change. Unexpectedly, radiation was one of the main factors determining the spatial variation in SLA on a large scale. Conversely, short-term manipulative experiments showed that SLA increased with increased resource availability and tended to stabilize with treatment duration. However, different species exhibited varying response patterns. Overall, variation in long-term adaptation of SLA to environmental gradients and its short-term response to resource pulses jointly improve plant adaptability to a changing environment. Overall SLA-environment relationships should be emphasized as a multidimensional strategy for elucidating environmental change in future research.

The potential bias of nitrogen deposition effects on primary productivity and biodiversity.

Atmospheric nitrogen (N) deposition is composed of both inorganic nitrogen (IN) and organic nitrogen (ON), and these sources of N may exhibit different impacts on ecosystems. However, our understanding of the impacts of N deposition is largely based on experimental gradients of INs or more rarely ONs. Thus, the effects of N deposition on ecosystem productivity and biodiversity may be biased. We explored the differential impacts of N addition with different IN:ON ratios (0:10, 3:7, 5:5, 7:3, and 10:0) on aboveground net primary productivity (ANPP) of plant community and plant diversity in a typical temperate grassland with a long-term N addition experiment. Soil pH, litter biomass, soil IN concentration, and light penetration were measured to examine the potential mechanisms underlying species loss with N addition. Our results showed that N addition significantly increased plant community ANPP by 68.33%-105.50% and reduced species richness by 16.20%-37.99%. The IN:ON ratios showed no significant effects on plant community ANPP. However, IN-induced species richness loss was about 2.34 times of ON-induced richness loss. Soil pH was positively related to species richness, and they exhibited very similar response patterns to IN:ON ratios. It implies that soil acidification accounts for the different magnitudes of species loss with IN and ON additions. Overall, our study suggests that it might be reasonable to evaluate the effects of N deposition on plant community ANPP with either IN or ON addition. However, the evaluation of N deposition on biodiversity might be overestimated if only IN is added or underestimated if only ON is added.

Plant magnesium on the Qinghai-Tibetan Plateau: Spatial patterns and influencing factors.

Magnesium (Mg) plays a crucial role in regulating plant photosynthesis and stress resistance. However, our understanding of plant Mg at the community level remains limited because of lack of systematic investigations. This study, for the first time, comprehensively evaluated community-level Mg content and density, and determined their spatial patterns and driving factors, on the Qinghai-Tibetan Plateau (TP), using data from 680 ecosystems (169 forests, 22 shrublands, 466 grasslands, and 23 deserts). Mg density was 1.01, 2.36, 1.87, and 2.26 g m-2 in leaves, branches, trunks, and roots, respectively. Notably, we generated maps of plant Mg content and density with a 1 km × 1 km resolution based on random forest models. Mg content decreased from northwest to southeast, but Mg density was higher in the east of the plateau, which reflected plant adaptive strategies to the unique radiation, oxygen, and temperature conditions (major driving factors) on the TP. Our findings provide insights into biogeochemical cycling and could facilitate the optimization of remote sensing parameters.

Predicting ecosystem productivity based on plant community traits.

With the rapid accumulation of plant trait data, major opportunities have arisen for the integration of these data into predicting ecosystem primary productivity across a range of spatial extents. Traditionally, traits have been used to explain physiological productivity at cell, organ, or plant scales, but scaling up to the ecosystem scale has remained challenging. Here, we show the need to combine measures of community-level traits and environmental factors to predict ecosystem productivity at landscape or biogeographic scales. We show how theory can extend the production ecology equation to enormous potential for integrating traits into ecological models that estimate productivity-related ecosystem functions across ecological scales and to anticipate the response of terrestrial ecosystems to global change.

Carbon sequestration of Chinese forests from 2010 to 2060: spatiotemporal dynamics and its regulatory strategies.

Forestation is important for sequestering atmospheric carbon, and it is a cost-effective and nature-based solution (NBS) for mitigating global climate change. Here, under the assumption of forestation in the potential plantable lands, we used the forest carbon sequestration (FCS) model and field survey involving 3365 forest plots to assess the carbon sequestration rate (CSR) of Chinese existing and new forestation forests from 2010 to 2060 under three forestation and three climate scenarios. Without considering the influence of extreme events and human disturbance, the estimated average CSR in Chinese forests was 0.358 ± 0.016 Pg C a-1, with partitioning to biomass (0.211 ± 0.016 Pg C a-1) and soil (0.147 ± 0.005 Pg C a-1), respectively. The existing forests account for approximately 93.5% of the CSR, which will peak near 2035, and decreasing trend was present overall after 2035. After 2035, effective tending management is required to maintain the high CSR level, such as selective cutting, thinning, and approximate disturbance. However, new forestation from 2015 in the potential plantable lands would play a minimal role in additional CSR increases. In China, the CSR is generally higher in the Northeast, Southwest, and Central-South, and lower in the Northwest. Considering the potential losses through deforestation and logging, it is realistically estimated that CSR in Chinese forests would remain in the range of 0.161-0.358 Pg C a-1 from 2010 to 2060. Overall, forests have the potential to offset 14.1% of the national anthropogenic carbon emissions in China over the period of 2010-2060, significantly contributing to the carbon neutrality target of 2060 with the implementation of effective management strategies for existing forests and expansion of forestation.