BACKGROUND AND AIMS:We aimed to elucidate how anthropogenic disturbances influence plant community assembly by integrating taxonomic, phylogenetic and functional diversity, and to quantify the relative effects of environmental drivers amid large-scale water conservancy projects. METHODS:We surveyed 123 forest community plots across the Three Gorges Reservoir Area (TGRA) in China and assessed the relative contributions of various environmental factors to plant taxonomic, phylogenetic and functional diversity by using random forest analyses and structural equation models. KEY RESULTS:We found phylogenetic overdispersion and functional clustering within plant communities in the TGRA. Anthropogenic disturbances, particularly proximity to the nearest railway line, emerged as the primary driver of the three plant diversity indicators. Notably, none of the functional traits displayed significant phylogenetic signal, indicating a decoupling of functional and phylogenetic diversity occurred in areas of high human disturbances. As the intensity of disturbances increased, phylogenetic diversity increased, with plant communities shifting from clusters of closely related species towards more random assemblages. In contrast, functional diversity decreased, with communities becoming more functionally similar. This suggests that functional traits may evolve independently of phylogenetic history, challenging traditional perspectives on community assembly. CONCLUSIONS:Our study demonstrates a critical divergence in biodiversity responses to anthropogenic pressure: while disturbances enhance phylogenetic diversity through environmental filtering, they simultaneously induce functional homogenization via trait-mediated selection processes. This divergence highlights the inadequacy of single-metric assessments and underscores the importance of integrative frameworks for understanding community assembly in human-modified ecosystems.

Vegetation carbon turnover time (τveg) dominates the uncertainty in terrestrial carbon cycle dynamics. Reports have shown that the τveg of mature or old-growth forests in North America and Europe has decreased because of faster carbon loss under global climate change. However, the temporal trend of τveg in widespread younger forests, which exhibit different growth patterns, remains inconclusive. Here, we consistently revealed a significant overall increase in τveg (0.025 ± 0.002 years per year) across China’s forests that are characterized by a relatively young forest age structure, using multisource data-model assimilation and long-term network observations. In young forests that receive high nitrogen deposition, increasing levels of CO2 accelerate vegetation growth, causing it to grow faster than it dies or decomposes, leading to increases in the τveg. The effects of forest age on τveg dynamics and the high sensitivity of enhanced carbon sinks to τveg should be incorporated into future land surface models to ensure that the τveg dynamics and their impacts on terrestrial carbon cycling and climate mitigation are accurately assessed. Our results also provide valuable insights for forest management aimed at enhancing carbon retention and sequestration through optimizing age-related stand dynamics.

Abstract The terrestrial carbon sink depends not only on how much biomass forests accumulate, but also on how long that carbon remains stored in vegetation. This is known as vegetation carbon turnover time ( τ veg ), which varies with forest age, structure and climate. Furthermore, τ veg is widely expected to decline under climate change as warming and disturbance accelerate biomass loss. However, most evidence comes from mature forests, even as global forest demographics shift due to reforestation, disturbance and land‐use change. Younger forests differ in growth rates, mortality patterns and stand structure, which may create distinct turnover trajectories with rapid biomass accumulation potentially slowing τ veg . Here, we evaluated this possibility using 17 years of in situ data from a network of temperate, subtropical and tropical forest plots across China. We found that τ veg declined over time in mature forests but increased in younger ones. These opposing trends were shaped by age‐specific trade‐offs between growth and mortality, mediated by stand structure and environmental conditions. Synthesis . Our results demonstrate that forest age strongly influences vegetation carbon turnover and must be integrated into models to improve predictions of terrestrial carbon sink dynamics.

Abstract While ecological dissimilarity plays a critical role in biological invasions, it remains unclear whether ecological differences between alien species and co‐occurring species in their native range persist after introduction. Leveraging the unidirectional introduction of plant species native to the Mediterranean into California, we conducted a cross‐continental study to examine whether Mediterranean‐origin species are phylogenetically and functionally distinct from co‐occurring species in their native range, and whether these differences are maintained relative to California native species after introduction. Mediterranean‐origin species introduced to California were phylogenetically and functionally distant from co‐occurring native species in both native and introduced ranges. They also exhibited distinct patterns of trait coordination between stress tolerance‐related traits (e.g., leaf dry matter content) and resource acquisition‐related traits (e.g., leaf nitrogen concentration and specific root length), and a more acquisitive strategy across ranges. Synthesis . These findings suggest that ecological dissimilarity and persistent trait coordination of species in their home range may contribute to their establishment after introduction, highlighting the value of native‐range trait information for understanding invasion functional strategies in novel environments.

Leaf litter decomposition is a key ecological process that strongly regulates carbon sequestration and nutrient cycling in forests. While the effects of climate and initial litter nutrient chemistry on mass loss are well established, the dynamics of multiple nutrients in decomposing leaf litter, particularly those beyond nitrogen (N) and phosphorus (P), and their downstream effects on subsequent mass loss and nutrient release remain insufficiently understood. We conducted a two-year litterbag decomposition experiment using litter from seven tree species in a mixed evergreen and deciduous broad-leaved forest along an altitudinal gradient (800–1800 m a.s.l.) in subtropical China. Alongside concurrent temporal high-resolution microclimatic data, we followed changes in concentrations of multiple litter nutrients, including potassium (K), calcium (Ca), and magnesium (Mg). Despite initial variation in litter nutrient concentrations and climatic conditions, nutrient concentrations in decomposing litter generally converged over time, except for the dissimilar P and Ca at later decomposition stages. Initial nutrients, particularly P, Ca, and Mg concentrations, displayed modest but consistent effects on nutrient concentrations in decomposing litter. Most importantly, air temperature and nutrient concentrations in the decomposing litter influenced subsequent mass loss and nutrient release in distinct ways. By incorporating multiple nutrients to link nutrient dynamics in decomposing litter to the subsequent decomposition process, our study provides an integrative framework to enhance process-based predictions of nutrient and carbon cycling in forests.

The operation of the Three Gorges Dam (TGD) has profoundly altered riparian ecosystems, which serve as critical transitional zones for maintaining riverine water quality. Although numerous studies have examined soil nutrients and heavy metals dynamics in riparian zones, their long-term trajectories remain poorly understood. In this study, we established a long-term monitoring site and compiled data from literature covering riparian soils in 15 districts over 15 years of dam operation (2007-2021). Generalized Linear Mixed Models (GLMMs) were employed to assess the contributions of key factors influencing soil properties in the riparian reservoir zone (RRZ). RRZ soils showed higher soil organic carbon (SOC) and heavy metal concentrations (Cd, Cr, Cu, Zn) compared to adjacent Upland soils. Interannual flooding frequency emerged as the dominant factor, explaining over 50% of the variability in most soil properties. Specifically, pH, total nutrients (SOC, TP TK) and heavy metal concentrations (Cd, Cr, Cu, Pb, Zn) all significantly increased with interannual flooding frequency, while soil available nutrients (AN, AP, AK) significantly declined. Elevation also played a critical role, with soils at 145-155 m showing higher SOC and heavy metal concentrations, while those at 165-175 m had higher TN, TK, AN, and AK levels. To mitigate these impacts, ecological management strategies, including vegetation restoration, are urgently needed. This study offers critical insights for the protection and restoration of riparian zones in the Three Gorges Reservoir, providing a foundation for future management efforts.

Carbon (C), nitrogen (N), and phosphorus (P) are fundamental elements for plant growth and metabolism. Leaf C-N-P stoichiometry provides critical insights into plant nutrient use efficiency and ecosystem-scale carbon-nutrient interactions, particularly under global change. However, comprehensive long-term records of leaf C, N, and P concentrations remain scarce. Here we compiled and publicly released the Leaf Carbon-Nitrogen-Phosphorus Concentrations in China's Forests (CNP-China) dataset, containing 628 standardized records from 52 dominant tree species across 11 representative China's forest ecosystems from 2005 to 2020. All samples were collected and analyzed following the Chinese Ecosystem Research Network (CERN) protocols, with accompanying plot-level geographic and environmental data, species taxonomy and functional traits, and surface soil properties (0-20 cm depth). The dataset underwent rigorous quality control, including unit harmonization, error checking, and outlier detection, and is provided in accessible CSV format. CNP-China enables critical assessments of stoichiometric responses to environmental change, supports improved ecosystem modeling, and facilitates cross-biome comparisons of nutrient cycling dynamics, providing an essential foundation for understanding forest carbon-nutrient feedback under global change.

Effectively achieving the United Nations’ Sustainable Development Goals (SDGs) alongside climate change adaptation and mitigation actions requires recognizing synergies and trade-offs among various targets. The relationship between vegetation conservation and economic development is complex and context-dependent across different regions and scales, and the lack of long-term and large-scale data remains a challenge in fully verifying this relationship. Existing area-based vegetation conservation metrics did not account for the ecological heterogeneity of vegetation zones. We proposed a zonal vegetation ratio to measure the extent of conservation of zonal vegetation, defined as the proportion of zonal vegetation area to the total area within a region. We analyzed the relationship of the zonal vegetation ratio with economic levels and Net Primary Productivity (NPP) using three decades of data from more than 2,000 rural counties (∼94.1% of the total land area) in China. Although the zonal vegetation ratio showed negative correlations with per area economic indicators and NPP nationally, variations occurred across vegetation zones. The relationship was mutually beneficial in the desert and alpine zones, which suggested that vegetation conservation and economic growth could coexist under certain conditions. After controlling for individual and temporal effects, the zonal vegetation ratio positively impacted fiscal revenue. Dynamic panel analyses suggested a potential positive causal link between the zonal vegetation ratio and fiscal revenue, although unobserved external factors limited causal certainty. These findings advocate for context-specific policies to align vegetation conservation and economic development. They highlight the need for further research to validate causal relationships and inform policy formulation.

Background and Aims Successional theory predicts directional shifts in plant community composition following disturbance. However, the long-term effects of chronic, recurring disturbances on plant ecological strategies at the community level in human-altered landscapes, and how they differ between the assemblages of native and alien species, remain poorly understood.Methods Using Grime's competitor, stress-tolerator, ruderal (CSR) framework, we examine temporal and spatial changes in plant strategies at the community level in the Three Gorges Reservoir Area, China. Based on repeated plant community surveys in 2012 and 2018 at the same localities, we assess the differences in the assemblages of native and alien strategies in response to chronic disturbances by extreme hydrological fluctuations and intense human activities over time and along a shoreline-to-upland disturbance gradient.Key Results Our results reveal a temporal shift in native assemblages, with a decline in R-score and an increase in C- and S-scores, while alien assemblages maintained a strong R-strategy. Spatial patterns show that native assemblages adopted a mid-elevation peak in C-strategy, with S- and R-strategies dominating at higher and lower elevations, respectively. In contrast, there is no spatial variation in the CSR strategies of alien plant assemblages.Conclusions Our findings demonstrate that chronic disturbances (e.g. water fluctuations and human activities) drive a spatiotemporal decoupling of the CSR strategies between native and alien plant assemblages. This divergence requires targeted management by prioritizing suppression of ruderal alien species and promoting competitive and stress-tolerant native species to guide succession dynamics.

Shrubland soils play a significant role in global carbon sequestration, yet the factors influencing soil organic carbon stocks at different depths in subtropical shrublands remain poorly understood, introducing large biases in understanding and predicting terrestrial carbon dynamics. This study examines the relative impacts of abiotic and biotic drivers on SOC density (SOCD) in topsoils (0-30 cm) and subsoils (30-100 cm) by capitalizing on a consistent broad-scale sampling across 297 sites in subtropical shrublands of China. Contrary to earlier findings suggesting greater SOC storage in subsoils, we found that topsoils and subsoils contribute equally to SOC stocks per unit area on average. Existing SOC maps overestimated SOCD by 30.13 % in topsoils and 22.23 % in subsoils. Past climate conditions had a lasting positive influence on topsoil SOC, while current climate emerged as the dominant indirect driver of SOCD in both soil layers. Edaphic properties emerged as a major driver of SOCD and dominated the indirect effects of paleoclimate legacy rather than that of current climate on the geographic pattern of SOCD, whereas vegetation attributes and recent human disturbances had relatively minor impacts. Our findings reveal that subtropical shrublands store less SOC than previously estimated, underscoring the urgent need to refine SOC assessments and reconsider their long-term carbon sequestration potential. We further illustrate the critical role of past climate over extended timescales in shaping current SOC distribution and highlight the importance of integrating paleoclimate legacies and edaphic interactions into Earth System Models to improve predictions of SOC dynamics under climate change.

The loss of biodiversity is irreversible and represents one of humanity’s greatest sustainability challenges. It has severe consequences for ecosystems and human well-being and requires global action. China, a global biodiversity hotspot, has experienced rapid habitat loss due to land-use change. Yet, current assessments, such as the IUCN Red List, suffer from incomplete coverage and fail to account for dynamic changes in habitat. This creates critical gaps in conservation planning. Here, we integrate species composition dissimilarities with satellite-derived land-use changes to quantify extinction risks across China. Our findings reveal a nationwide increase in extinction risk (3.91%) alongside a decline in habitat (2.81%). Current protected areas disproportionately prioritize lower-risk western regions, while IUCN assessments often overlook high-risk areas in human-modified landscapes. Our results establish a framework for quantifying extinction risks driven by dynamic habitat loss—a critical dimension that traditional IUCN metrics neglect. We provide actionable insights to advance sustainable development goals.

The leaf nitrogen to phosphorus ratio(N:P)is an important indicator describing plant nutrition limitation.Large-scale N:P data plays an essential role in assessing nutrition utilization in ecosystems and estimating the carbon sink potential under nitrogen and phosphorus deposition.However,ecosystems are highly influenced by human activities,leading to greater uncertainty in their study.This dataset establishes relationships between ground-measured data and environmental factors using a machine learning algorithm,generating a d dataset of leave nitrogen to phosphorus ratios in China's shrubland ecosystems with a resolution of 1 km,with each grid cell representing the estimated leaf N∶P ratio,and is available in TIFF format.The testing results and comparison with other similar data both demonstrates the high accuracy of the dataset.This dataset objectively reflects nutrition limitation in shrubland vegetation,and can be used for studies on nutrient utilization and carbon sink potential in shrubland ecosystem.

Leaf litter nitrogen (N) and phosphorus (P), as the final products reflecting the foliar nutrient status after resorption, strongly influence forest production and nutrient cycling. However, our nuanced understanding of their general patterns and controls is still lacking, and whether differential regulatory mechanisms exist between climatic zones remains largely incomplete, which introduces substantial uncertainty in the comprehension of net ecosystem productivity and nutrient cycling. Here, we aimed to evaluate patterns of leaf litter N and P concentrations of broad-leaved tree species, and further quantify their controls from climatic, soil physical, soil chemical, and green foliar nutrient factors across and within the tropics and extra-tropics by updating a global dataset comprising 1171 records from 159 studies. We found that tropical tree species exhibited higher leaf litter N concentrations but lower leaf litter P concentrations than extra-tropical tree species. In contrast to previous findings, the effects of climatic and edaphic variables on leaf litter N and P concentrations are more pronounced in the tropics than in the extra-tropics. Different from past bivariate analyses of climate-nutrient relationships for leaf litter, climate exerted more indirect effects on leaf litter N and P concentrations through soil texture, hydrology, nutrient availability, and green foliar nutrients. We also observed direct effects of green foliar N and P concentrations on leaf litter N and P concentrations enhanced from tropical to extra-tropical zones. Overall, this study refines our understanding of differential controls over leaf litter N and P concentrations across climatic zones and highlights the crucial yet often overlooked role of soil physical and chemical properties. These insights further underscore the urgent need to integrate multiple climatic, edaphic, and green foliar nutrient variables into geographically explicit biogeochemical models to improve our understanding of leaf litter-driven forest nutrient cycling in response to future environmental changes for different climatic zones.

AbstractAccurate estimations of carbon (C), nitrogen (N), and phosphorus (P) densities in shrublands are pivotal for assessing terrestrial ecosystem carbon sequestration. Combining in‐situ investigations and machine learning facilitates large‐scale patterns mapping, however, which often overlooks underlying ecological regulations. Here we utilize data from 1,122 survey plots across China's shrublands and develop a novel knowledge‐based deep learning framework that integrates a structural equation model (SEM) to elucidate mechanisms and construct an artificial neural network (ANN) based on these causal relationships. Results show that biomass allocation to different organs follows allometric regulations and that N and P concentrations maintain a degree of stoichiometric homeostasis following biological stoichiometry theory. This insight guides the construction of our ANN, which outperforms both SEM and other prevalent machine learning methods. By leveraging ecological theories to inform model construction, our framework not only enhances prediction accuracy and explainability but also provides a methodological blueprint for ecological research.

Darwin's two opposing hypotheses, proposing that non-native species closely or distantly related to native species are more likely to succeed, are known as 'Darwin's Naturalization Conundrum'. Recently, invasion ecologists have sought to unravel these hypotheses. Studies that incorporate rich observational data in disturbed ecosystems that integrate phylogenetic and functional perspectives have potential to shed light on the conundrum. Using 313 invaded plant communities including 46 invasive plant species and 531 native plant species across the Three Gorges Reservoir Area in China, we aim to evaluate the coexistence mechanisms of invasive and native plants by integrating phylogenetic and functional dimensions at spatial and temporal scales. Our findings revealed that invasive plants tended to co-occur more frequently with native plant species that were phylogenetically distant but functionally similar in the reservoir riparian zone. Furthermore, our study demonstrated that the filtering of flood-dry-flood cycles played a significant role in deepening functional similarities of native communities and invasive-native species over time. Our study highlights the contrasting effects of phylogenetic relatedness and functional similarity between invasive and native species in highly flood-disturbed habitats, providing new sights into Darwin's Naturalization Conundrum.

is one of the dominant species in the evergreen broad-leaf forest on the southern slope of Shennongjia. The study of spatial distribution pattern and spatial correlation of

Quercus myrsinifolia is one of the dominant species in the evergreen broad-leaf forest on the southern slope of Shennongjia. The study of spatial distribution pattern and spatial correlation of Q. myrsinifolia population will help to understand population development and potential ecological processes, as well as the structure and biodiversity maintenance mechanism of evergreen broad-leaf forests at the northern edge of the subtropics. Based on forest dynamic monitoring data from one 1 hm2 permanent plot on the southern slope of Shennongjia, we employed pair correlation functions g(r) and marked correlation functions to analyze the diameter structure of the Q. myrsinifolia population, spatial distribution patterns at different diameter classes, and intraspecific and interspecific spatial associations. The results showed that diameter structure of Q. myrsinifolia population exhibited an inverted 'J'-shaped distribution, suggesting a healthy regeneration status and belonging to a growing population type. The spatial distribution showed a decreasing trend in aggregation with increasing diameter. Positive correlations among individuals strengthened with closer diameter classes, while weakening with larger diameter differences. Interspecific spatial associations showed an increasing correlation of Q. myrsinifolia with understory dominant species with increasing spatial scales, but no correlation was observed with canopy-dominant species. Our results suggested that the spatial pattern of Q. myrsinifolia populations on the southern slope of Shennongjia was mainly influenced by habitat filtering, seed dispersal limitation, and intraspecific and interspecific competition. Furthermore, the adaptive strategies of Q. myrsinifolia varied when they coexisted with different species.

BACKGROUND:Leaf nitrogen (N) and phosphorus (P) resorption is a fundamental adaptation strategy for plant nutrient conservation. However, the relative roles that environmental factors and plant functional traits play in regulating N and P resorption remain largely unclear, and little is known about the underlying mechanism of plant functional traits affecting nutrient resorption. Here, we measured leaf N and P resorption and 13 plant functional traits of leaf, petiole, and twig for 101 representative broad-leaved tree species in our target subtropical transitional forests. We integrated these multiple functional traits into the plant economics spectrum (PES). We further explored whether and how elevation-related environmental factors and these functional traits collectively control leaf N and P resorption. RESULTS:We found that deciduous and evergreen trees exhibited highly diversified PES strategies, tending to be acquisitive and conservative, respectively. The effects of PES, rather than of environmental factors, dominated leaf N and P resorption patterns along the elevational gradient. Specifically, the photosynthesis and nutrient recourse utilization axis positively affected N and P resorption for both deciduous and evergreen trees, whereas the structural and functional investment axis positively affected leaf N and P resorption for evergreen species only. Specific leaf area and green leaf nutrient concentrations were the most influential traits driving leaf N and P resorption. CONCLUSIONS:Our study simultaneously elucidated the relative contributions of environmental factors and plant functional traits to leaf N and P resorption by including more representative tree species than previous studies, expanding our understanding beyond the relatively well-studied tropical and temperate forests. We highlight that prioritizing the fundamental role of traits related to leaf resource capture and defense contributes to the monitoring and modeling of leaf nutrient resorption. Therefore, we need to integrate PES effects on leaf nutrient resorption into the current nutrient cycling model framework to better advance our general understanding of the consequences of shifting tree species composition for nutrient cycles across diverse forests.

The operation of Three Gorges Dam (TGD) has dramatically impacted the adjacent riparian ecosystem. Riparian ecosystems link the terrestrial and aquatic environments and play a vital role in maintaining water quality. Studies that characterize riparian soil nutrient and heavy metal concentration dynamics have attracted attention, but they lack validation over long time scales. We collected data for riparian soils in 15 regions and in a long-term monitoring site after 15 years of dam operation (2007 to 2021). Year, submergence, and soil type significantly influenced riparian soil nutrient and heavy metal concentrations. Soil in the riparian zone, which was subjected to annual flood-dry-flood cycles, showed a significant decrease in nutrient concentrations (soil organic carbon, soil available nitrogen, soil available phosphorus, and soil available potassium), and a significant increase in heavy metal concentration (Cd, Cu, Pb and Zn), especially for Cd. Dam operation has resulted in diminished soil nutrient concentrations and made the riparian zone more vulnerable to heavy metal pollution, a problem whose severity appears to increase with time. Hence, additional information and intensified management is urgently needed.

Biodiversity and climate are interconnected through carbon. Drivers of climate change and biodiversity loss interact in complex ways to produce outcomes that may be synergistic, and biodiversity loss and climate change reinforce each other. Prioritizing the conservation of flagship and umbrella species is often used as a surrogate strategy for broader conservation goals, but it is unclear whether these efforts truly benefit biodiversity and carbon stocks. Conservation of the giant panda offers a paradigm to test these assumptions. Here, using the benchmark estimates of ecosystem carbon stocks and species richness, we investigated the relationships among the giant panda, biodiversity, and carbon stocks and assessed the implications of giant panda conservation for biodiversity and carbon-focused conservation efforts. We found that giant panda density and species richness were significantly positively correlated, while no correlation was found between giant panda density and soil carbon or total carbon density. The established nature reserves protect 26 % of the giant panda conservation region, but these areas contain <21 % of the ranges of other species and <21 % of total carbon stocks. More seriously, giant panda habitats are still facing high risks of habitat fragmentation. Habitat fragmentation is negatively correlated with giant panda density, species richness, and total carbon density. The ongoing giant panda habitat fragmentation is likely to cause an additional 12.24 Tg C of carbon emissions over 30 years. Thus, giant panda-focused conservation efforts have effectively prevented giant panda extinction but have been less effective in maintaining biodiversity and high‑carbon ecosystems. It is urgent for China to contribute to the development of an effective and representative national park system that integrates climate change issues into national biodiversity strategies and vice versa in dealing with the dual environmental challenges of biodiversity loss and climate change under a post-2020 framework.