Drought represents a paramount abiotic stressor constraining global agroforestry productivity. Plants have evolved multifaceted adaptive strategies involving active modulation of symbiotic microbial communities to mitigate drought stress. These plant-associated microbes enhance plant drought adaptation via five principal mechanisms: (i) extracellular polymeric substance-mediated biofilm formation on plant surface enhances hydroregulation and edaphic structural stability; (ii) osmoprotectant biosynthesis (e.g., proline) maintains cellular osmotic equilibrium; (iii) synthesizing antioxidants to reduce damage from reactive oxygen species and oxidative stress; (iv) regulating plant phytohormone metabolism by secreting hormones (e.g. indole-3-acetic acid) and 1-aminocyclopropane-1-carboxylic deaminase; (v) emitting signaling molecules (e.g. volatile organic compounds, hormones and enzymes) to activate plant drought adaptation. Future researches should focus on the development of host-specific drought-adaptive microbial consortia while elucidating phyllosphere–rhizosphere microbiome crosstalk, ultimately harnessing translational microbiome engineering to evaluate their efficacy in multi-environment agricultural systems.

The decline in tree growth has become a global issue. It is critically important to explore the factors affecting tree growth under the background of global climate change to understand tree growth models. A database was established based on Robinia pseudoacacia growth and its driving factors on China’s Loess Plateau. Linear regression and three machine learning methods, including support vector machine, random forest (RF) and gradient boosting machine were used to develop R. pseudoacacia growth models considering forest age, density, climate factors and topographic factors. The root mean square deviation method was adopted to quantitatively assess the relationship between tree growth and soil properties. The average tree height of R. pseudoacacia on the Loess Plateau was 8.8 ± 0.1 m, the average diameter at breast height (DBH) was 10.4 ± 0.1 cm and the average crown diameter was 3.2 ± 0.1 m. The RF model was a fast and effective machine learning method for predicting R. pseudoacacia growth, which showed the best simulation capability and could account for 67% of tree height variability and 55% of DBH variability. Model importance indicated that forest age and stand density were the main factors predicting R. pseudoacacia growth, followed by climate factors. The trade-off between R. pseudoacacia growth and soil properties revealed that soil texture and soil pH were the primary determinants of R. pseudoacacia growth in this region. Our synthesis provides a good framework for sustainable forest management in vulnerable ecological areas under future climate change.

We screened 161 eligible papers of experimental data across the Tibetan plateau for Meta-analysis, in order to systematically assess and validate potential application of plant resource allocation strategies, such as the optimal allocation hypothesis, the isometric allocation hypothesis, and the allometric allocation hypothesis under environmental changes, and to explore the effects of environmental factors (temperature change, grazing intensity) on plant resource allocation strategies in alpine grassland ecosystems on the Tibetan Plateau. Overall, we found that the aboveground and belowground growth relationship in alpine grasslands follows the allometric growth hypothesis, which was unaffected by warming, grazing and their interactions. In addition, the biomass transferred between aboveground and belowground, the former was decreased, while the later was increased under warming condition in alpine steppe implies that the resource allocation strategy in alpine steppe grassland may potentially follow the optimal allocation hypothesis. We further found that the effect of soil properties on biomass, not the biomass allocation, was different under warming and grazing condition in alpine grasslands, which further conforms the above conclusion. In addition, warming helped to mitigate the negative effects of grazing, which indicated that the interaction between warming and grazing is important in alpine grassland ecosystems. Overall, results of this study are of theoretical significance for understanding how moderate grazing affects the growth of plants in alpine grasslands under changing climate.

The mating systems and floral traits often among relatives of hermaphroditic plants can exhibit considerable diversity. This diversity can be influenced by the evolution of selfing and associated floral traits as a form of reproductive assurance (RA) when pollen limitation (PL) results from insufficient pollinator availability. To explore whether the degree of PL primarily drives differences in mating systems and floral traits, we conducted a comprehensive study involving two closely related species, Halenia elliptica and Halenia grandiflora, in three sympatric sites. We investigated floral characteristics, pollinator visitation, PL, autonomous selfing ability, RA and mating system in studied populations. Our findings show that H. elliptica produces smaller flowers and less nectar production than H. grandiflora, making it less attractive to pollinators. Compared with H. grandiflora, H. elliptica experienced more severe outcross pollen limitation (OPL), but compensates with a higher capacity for autonomous selfing, ensuring seed production under natural conditions. Moreover, significant differences in mating systems were detected between them, with H. elliptica exhibiting a higher selfing rate than H. grandiflora across all studied sympatric populations. These differences are also reflected in variations in herkogamy and dichogamy. Our study suggested that the degree of OPL impacts the divergence in mating systems and floral traits between sympatric closely related species, offering valuable insights into the evolution of plant mating systems and floral traits.

Tree allometric models based on height (H) and diameter (D) are the most commonly used method to estimate forest biomass. Environments and stand characteristics are recognized to affect tree allometries. However, few studies have considered to incorporate these effects into allometric models, which restricts the use of these models in a wide domain. Adopting the power-law function Y = aG^b as a basic model where Y is either tree height or biomass and the corresponding G is tree diameter D at breast height or D²H, we developed a two-step approximation procedure to quantify the effects of environments and stand characteristics on allometric coeffcients a and b for Cunninghamia lanceolata and Pinus forest in China. Results show that most of the allometric coeffcients are dependent on stand characteristics for C. lanceolata forest, and on mean annual temperature, stand age and latitude for Pinus forest. The allometric models via the two-step approximation Y = f(α + α_jx_j) G^{f (β+βixi)} (x_j or x_i are key drivers associated with environments and stand characteristics. α, α_j,β and β_i are regression coeffcients) considerably improved the accuracy of tree height and biomass estimation. Compared to the basic model, the second approximation models signifcantly reduced the mean absolute bias between the observed and computed values by 25%–34% for C. lanceolata and by 21%–26% for Pinus forest, respectively. Our results highlight the necessity of incorporating environments and stand characteristics into the allometric models and provide a universal method to accurately estimate H-D-based tree biomass across a wider domain.

The intricate interplay among plant productivity and soil factors is a pivotal driver for sustaining the carbon sequestration capacity of coastal wetlands. Yet, it remains uncertain whether climate warming will reshape the cause-and-effect interactions between coastal plant productivity and soil factors. In this study, we combined a manipulative warming experiment with a convergent cross-mapping technique to quantify the causal relationships, which can be either unidirectional or bidirectional, between plants (gross primary productivity, GPP) and soil environment (e.g. soil temperature, moisture and salinity). Our findings revealed that warming amplified the interaction between GPP and soil salinity in the coastal wetland ecosystem. While soil temperature primarily drove this causal relationship in control plots, a more complex interaction emerged in warming plots: soil salinity not only directly influenced GPP but also indirectly affected it by altering soil temperature and moisture. Overall, warming increased the number of causal pathways linking GPP with soil environmental factors, such as the effect of soil salinity on GPP and the impacts of GPP on soil moisture. These findings provide experimental evidence of intensified plant–soil causality in coastal wetlands under climate warming.

Interspecific plant–soil feedback (PSF)—the influence of soil conditioned by one plant species on another—is key to ecosystem processes but remains challenging to predict due to complex factors like species origin and phylogenetic relatedness. These aspects are underexplored, limiting our understanding of the mechanisms driving PSFs and their broader implications for ecosystem functioning and species coexistence. To shed light on the role of plant species origin and phylogenetic distance in interspecific PSFs, we conducted a greenhouse experiment with 10 native responding species and soils conditioned by 10 native and 10 exotic species resulting in 20 species pairs. These pairs represented a range of phylogenetic distances between both species, spanning up to 270 million years of evolutionary history since their last common ancestor. Conditioning by both native and exotic species reduced biomass production, with stronger inhibition observed for native-conditioned soils. Native-conditioned soils also exhibited lower phosphorus levels, higher basal and specific respiration, and greater cation exchange capacity, base saturation, and magnesium content compared to exotic-conditioned soils. Contrary to expectations, phylogenetic distance did not influence PSFs, regardless of conditioning species origin. Our findings suggest that co-evolution drives native plants to foster microbial communities with low carbon-use efficiency, highlighting soil biota’s critical role in PSFs. This advances our understanding of interactions between plant species origin and microbial communities and underlines the importance of microbial management for promoting native species and controlling invasives. The lack of phylogenetic distance effects aligns with prior studies, indicating evolutionary relatedness alone does not reliably predict PSF outcomes.

Trade-offs have long been recognized as a crucial ecological strategy for plant species in response to environmental stresses and disturbances. However, it remains unclear whether trade-offs exist among different structures (or functions) of clonal plants in response to aeolian activities in sandy environments. We examined the growth (reproductive vs. vegetative), reproduction (sexual vs. asexual), and bud bank (tiller buds and rhizome buds, representing vertical and horizontal growth potential) characteristics of two dominant rhizomatous grasses (Psammochloa villosa and Phragmites australis) in the arid sand dunes of northwestern China. Our results showed that these two rhizomatous clonal species exhibited significant trade-offs in their adaptation strategies in response to changes in sand burial depth. Specifically, as sand burial depth increased, the clonal species tended to reduce their reproductive growth, sexual reproductive capacity, and horizontal growth potential, as evidenced by reductions in reproductive ramet number and proportion, panicles number, biomass, and their proportions, as well as rhizome bud number, biomass, and their proportions. Conversely, they increased vegetative growth, reproduction, and vertical growth potential, as evidenced by enhancements in vegetative ramet number and proportion, belowground bud number, biomass, and their proportions, and in tiller bud number, biomass, and their proportions. Our study underscores the importance of trade-offs in the adaptation strategies of rhizomatous clonal species in sandy environments where drought stress and aeolian disturbance coexist. Those trade-offs could ensure the population persistence and stability of pioneering psammophytes in sand dunes, which should be considered during sand-fixing and vegetation restoration efforts in arid sand dunes.

Understanding the driving mechanisms of forest changes is of great significance for developing effective adaptation strategies to mitigate the impacts of climate change and human activities on ecosystems. This study used Theil–Sen median trend analysis, Mann–Kendall test, contribution rate decomposition, partial least squares, geodetector and residual analysis to explore the impact of climate change and human activities on the forest coverage area and NDVI of the Altai Mountains. Results show that changes in forest cover are driven by both forest management policies and climate change. Among them, forest management policy is the main factor. However, there are differences in the driving mechanisms in different altitude zones: in the alpine and subalpine zones, the promoting effects of natural death and climate change bring the forest coverage area toward a dynamic balance, while under the combined effects of human activities and climate change, the forest coverage area in the low mountain zones shows an expansion trend. For forest NDVI, the analysis results of the six scenarios show that the joint action of climate change and human activities promotes the growth of forest NDVI in the largest proportion (50.20%); the impact of climate change on forest NDVI is greater than that of human activities, and most of it is a promotion effect (30.28%). Forest degradation is mainly caused by human activities (19.39%), especially in the edge areas of the forest. Among climate factors, precipitation and snowmelt water are the main controlling factors for forest growth. Snowmelt water from March to April is an important water source before the growing season. This study provides the important scientific basis for forest management and strategic planning in the Altai Mountains.

The decomposition of deadwood is a crucial process for the accumulation and sequestration of soil organic carbon (SOC) in forest ecosystems. However, the response of SOC to different decay classes of deadwood and the underlying mechanisms remain poorly understood. Here, we investigated the dynamics of SOC, soil properties, extracellular enzyme activities, and phospholipid fatty acid biomarkers across five decay classes (ranging from 1 to 5) of Masson pine (Pinus massoniana Lamb.) downed deadwood in a subtropical–temperate ecotone forest in Central China. Our results revealed a nonlinear response pattern of SOC along the deadwood decomposition gradient, with the maximum value at the decay class 4. Soil available nitrogen content, bacterial biomass, fungal biomass, the ratio of fungal-to-bacterial biomass, cellulase, activity and ligninase activity all increased with the intensification of deadwood decay, while soil pH decreased. The increase in SOC content was associated with a direct positive effect of bacteria and both direct and indirect positive effects of fungi by cellulose activity, but ligninase activity showed no significant relationship with SOC content. These findings suggest that cellulose and microbial biomass are key determinants of soil C formation and sequestration during deadwood decomposition. This study highlights the importance of the nonlinear response of SOC to deadwood decay, providing valuable insights for predicting future carbon-climate feedbacks.

Warming has been consistently observed to reduce soil carbon (C) storage by accelerating the decomposition of soil organic matter. While different soil C fraction may respond differentially to warming, microbial necromass has been considered as an important contributor to the persistent soil C pool. However, the mechanisms by which warming regulates microbial necromass formation and its potential contribution to new soil organic carbon (SOC) fractions remain poorly understood. In this study, we examined the effects of elevated temperature on newly formed amino sugar C (an indicator of fungal and bacterial-derived microbial necromass C) and its allocation in particulate organic matter (POM) and mineral-associated organic matter (MAOM) fractions in alpine soils of Southwest China, based on a 37-day incubation experiment at 15 °C and 25 °C by adding ¹³C labeled glucose and oxalic acid. The results showed that warming significantly reduced the formation of new SOC by lowering the incorporation of new C into both POM and MAOM fractions. Glucose addition was more effective than oxalic acid in promoting new SOC formation, regardless of temperature. Warming also significantly decreased the new microbial necromass in both soil fractions with more bacterial necromass associated with mineral particles, which was primarily attributed to the higher abundance of bacterial community. In addition, glucose addition significantly promoted contribution of the fungal necromass to newly formed SOC. Overall, this study reveals that warming significantly alters the allocation of newly formed SOC and microbial necromass, highlighting the differential microbial responses in soil C sequestration. These findings have important implications for predicting and managing soil C stocks in forest ecosystems under climate change.

The field of ecology has been greatly enhanced by the integration of computational tools and statistical methods, with the programming language R emerging as a pivotal and flexible tool for ecological research. As ecological studies accelerate, understanding the prevalent trends and specific usage patterns of R in recent research is crucial. This study investigated the use of R and its packages in 125 494 scholarly articles published in 40 ecology journals from 2008 to 2023. A total of 52 658 articles (42%) designated R as their principal analytical tool, demonstrating a steady linear growth in its utilization from 10.3% in 2008 to 66.9% in 2023. Twelve R packages, including ‘lme4’, ‘vegan’, ‘nlme’, ‘MuMIn’, ‘ape’, ‘ggplot2’, ‘car’, ‘mgcv’, ‘MASS’, ‘raster’, ‘multcomp’ and ‘lmerTest’, each played a pivotal role in contributing to more than 1000 scholarly articles. The highest usage rate of the 'lme4' package indicates that mixed-effect models have a particularly important role in ecological research, and the application of these models has helped ecologists solve many important scientific problems. Journal-specific package preferences aligned with their scientific domains, while the rise in the average number of R packages per article indicates a trend towards more complex and diverse analytical methods in ecology. Our findings reveal a reciprocal relationship between the development of R and ecological research, underscoring the need for collaboration among quantitative ecologists, R developers and ecologists to further advance both the language and the field. Such collaboration will not only enhance the functionality and versatility of R but also provide robust technical support for the continued progress of ecological research.

Invasive plants alter soil microbial communities and physicochemical properties through chemical inputs from litter, root exudates and leachate, impacting a range of soil processes, but precise effects are poorly understood. We investigated the little effects of Solidago canadensis, a common invasive species in China, on soil microbial communities under natural conditions. Experimental treatments included S. canadensis seedling density (1 and 2 plants/pot) and litter quantity (10 and 20 g/pot), with control groups containing no plants or litter. After 120 days, soil samples were analyzed for physico-chemical properties, GC–MS chemical composition, and bacterial community composition using high-throughput sequencing. Results showed that S. canadensis seedlings and litter inputs significantly increased soil pH, soil organic matter (SOM), and total nitrogen (TN), while phosphorus and potassium remained unchanged. We identified 66 chemical compounds, predominantly ketones, alcohol, aldehyde, hydrocarbon, ester, acid, terpenoids and alkaloids, associated with the presence of S. canadensis, alongside shifts in dominant bacterial genera including Sphingomonas, Acidobacteriales and Gemmatimonas. Rarer genera under the invasive treatment species, such as Candidatus, Rhodoplanes and Novosphingobium, were positively correlated with soil TN, pH, and SOM. Collectively, these findings demonstrate that allelochemical inputs from S. canadensis litter and root exudates significantly reshape soil properties and microbial communities, with potential implications for ecosystem dynamics and invasion success.

Accurate estimation of vegetation biomass is a critical component for estimating terrestrial ecosystem carbon stocks. However, research on biomass estimation for herbaceous marshes remains limited. In this study, we collected 270 paired above-ground biomass (AGB) and trait data from reed marshes in Northeast China to estimate AGB, and 70 paired AGB and below-ground biomass (BGB) data from global literature to estimate BGB. The results showed that classifying reed marshes into saltwater and freshwater marshes greatly improved the model fit (R2 values of classified vs. overall models: >0.50 vs. >0.31 for AGB estimation and >0.50 vs. >0.10 for BGB estimation, respectively). A power-law allometric model using plant height as the sole predictor was optimal for AGB estimation, and the inclusion of plant density did not markedly enhance prediction accuracy. The power function also effectively described the relationship between AGB and BGB, with scaling exponents of 1.13 and 0.60 for saltwater and freshwater marshes, respectively. Our results indicate that saltwater and freshwater marsh classification is necessary for accurate wetland vegetation carbon estimation. These findings provide valuable insights into the prediction of carbon dynamics in wetland ecosystem and supports a better understanding of wetland carbon sequestration.

The significance of microbes for ecosystem functioning is well known; however, within a single system, the relative contributions of keystone and rare taxa to soil microbial functions are less well quantified, as are their shared or unique responses to abiotic conditions. Furthermore, their associations with tree community composition in natural forest ecosystems are not well understood. In this study, a total of 1287 soil samples were collected from a 20-ha subtropical forest plot and analyzed using high-throughput sequencing. Based on co-occurrence network analyses, we conducted a comparison of the associations between keystone and rare taxa with the structure, functions and stability of soil microbial communities. Additionally, we examined their associations with tree community composition. Results showed that keystone taxa made a significantly greater contribution than rare taxa in all comparisons of microbial functions and stability. Keystone taxa had direct effects on microbial community structure and also mediated indirect effects of abiotic conditions. Neither effect was evident for rare taxa. The importance of keystone taxa also extended to aboveground composition, where tree community composition was more closely associated with keystone taxa than with rare taxa. While it may still be premature to establish causality, our study represents one of the initial attempts to compare the relative importance of keystone and rare microbial taxa in forest soils. These findings offer the potential to improve natural forest ecosystem functioning and tree diversity through the manipulation of a small number of keystone soil microbial taxa, as has been demonstrated in agroecosystems.

Leaf functional traits reflect the ecological strategies of plants and influence their growth and distribution. While variation in leaf traits has been extensively documented across species in terrestrial ecosystems, studies in wetland ecosystems can enhance the understanding of leaf trait variation along environmental gradients. Intraspecific studies are particularly valuable for exploring trait variation and its underlying mechanism. Coastal wetlands have become hotspots for studying trait variation, and the invasive Spartina alterniflora, distributed along China’s coastline, is an ideal species for investigating leaf traits variation. We examined the geographical variation and abiotic drivers of six leaf functional traits and explored the roles of phenotypic plasticity and genetic differentiation through a two-year common garden experiment. We also analyzed the relationships between leaf traits and growth performance in both field and common garden. All leaf traits exhibited significant geographical variation, which were affected by both climatic and sedimentary variables. Common garden experiment exhibited trait-dependent response, with different leaf traits showing varying degrees of plastic response or genetic differentiation. Variation in leaf size, leaf thickness and specific leaf area was primarily driven by genetic differentiation, while variation in leaf density and leaf dry matter content was largely due to phenotypic plasticity. Leaf size and thickness were positively correlated with growth performance in both field and common garden. This study advances the understanding of leaf trait variation in terrestrial ecosystems and highlights how multiple abiotic variables shape latitudinal patterns in leaf traits. The resource acquisition strategy at high latitudes in the northern hemisphere contributes to the strong growth performance of S. alterniflora, potentially facilitating its northward expansion. In contrast, the resource conservation strategy at low latitudes may hinder its southward expansion.

Fine root dynamics are crucial for terrestrial ecosystem productivity and nutrient cycling. However, the effects of nitrogen (N) deposition on fine root dynamics in temperate ecosystems remain poorly understood. In this study, we used a meta-analysis to explore the general patterns and key drivers of fine root biomass and turnover in temperate forests and grasslands in response to N application. We found that N application significantly reduced fine root biomass compared to the control group (no N application), with notable differences across N forms. However, the impact of N application on fine root biomass remained consistent across ecosystem types, soil depths and root diameters. In terms of fine root turnover rate, N application had no significant overall effect, and the response did not vary across N forms, ecosystem types, soil depths or root diameters. However, significant differences were observed across methods for estimating fine root turnover rate. Multiple regression analysis showed that mean annual temperature (MAT) and experimental factors (including duration and N application rates) were the primary determinants of fine root biomass response to N application. In contrast, fine root turnover was not significantly influenced by any of the factors analyzed. Overall, our findings highlight the negative impact of N application on fine root biomass and the neutral effect on fine root turnover, and also suggest that find root dynamics are closely associated with experimental factors, including experiment duration and N application rate. This study provides an important advancement in understanding the feedback between root dynamics and global change, offering insights for developing management strategies to address belowground ecological processes under global change scenarios.

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) monoculture plantations account for 17.4% of the total plantation area in China. The decomposition of Chinese fir litter plays a fundamental role in maintaining nutrient cycling and soil fertility in these plantations. Here, we conducted a continental synthesis based on 64 studies to estimate the mass loss and release rates of carbon (C) and nutrients (including nitrogen (N), phosphorous (P), potassium (K), calcium (Ca) and magnesium (Mg)) during the first year of Chinese fir litter decomposition. The average mass loss rates of needle, twig, root and cone litter were 0.503, 0.319, 0.551 and 0.372 year^-1, respectively. The decomposition rates of C and cellulose for needle litter were 0.649 and 0.801 year^-1, respectively, while those of K, Ca and Mg were 2.27, 0.852 and 0.551 year^-1, respectively. Decomposition rates were strongly influenced by mean annual temperature, soil N concentration and the initial C/N ratio of the litter. Climate warming and elevated ultraviolet-B radiation accelerated mass loss of Chinese fir litter, while increased N deposition and acid rain reduced it. However, elevated N deposition facilitated nutrient release from decomposing Chinese fir litter. These results provided a comprehensive assessment of Chinese fir litter decomposition, which is crucial for understanding soil biogeochemical cycles and improving soil fertility in Chinese fir plantations under global change scenarios.

Fruit type influences seed dispersal mode and its effectiveness, reflecting plant adaptability to their environments. However, the large-scale patterns of fruit type distribution in forest communities and differences in the drivers of various fruit types remain unclear. We present a large-scale biogeographic model of woody plant fruit types along a latitudinal gradient through the data analysis of 30 forest dynamic plots. Results showed the following: (1) Fleshy and dry fruits exhibited distinct distribution patterns in large-scale space. The distribution of fleshy fruits was greater in tropical and subtropical zones, while dry fruits were more common in temperate zones. (2) Climatic factors primarily drove the geographical distribution of the fruit types of woody plants. Climatic and spatial factors exerted greater effects on the species richness of dry fruits compared with that of fleshy fruits. These results demonstrated the difference in the latitudinal gradient patterns of fleshy and dry fruits and identified the major abiotic environmental factors that drove their large-scale distribution, demonstrating the biogeography of the fruit types of woody plants.

Ecological theories and field observations indicate a strong allometric relationship between plant biomass and leaf area. Here, we aimed to rigorously investigate how this allometry can predict the biomass responses to global warming. We conducted a global synthesis on a dataset of 188 species from warming experiments. The reliability of metabolic scaling theory (MST) and functional equilibrium theory (FET) was tested by estimating an allometric coefficient (β) under a Bayesian framework. The results showed that the high β in areas suffering low precipitation was consistent with both theories, while the high β in areas suffering low-temperature stress was consistent with the MST but not the FET. These differences in β between ambient and stressed environments might be derived from the hydraulic constraints in stressed environments. Using general allometry across all species explained 58% of the total variance in the warming responses of plant biomass. The predictive power was not largely improved when factors, such as plant functional type, mean annual temperature and precipitation, warming magnitude, and other experimental treatments, were considered. The predictive error was primarily due to the theoretical assumptions that are based on long-term adaptation failing to capture the changes in specific leaf area (SLA) under rapid global warming. Fortunately, integrating the information on plant traits such as SLA and leaf biomass fraction in the ambient environment effectively improved the predictive power from 58% to 81%, highlighting the necessity of incorporating plant traits into ecosystem models for better predicting the ecosystem carbon cycle in a changing world.

Canopy properties (e.g. canopy structure and spectral variables) strongly influence forest above-ground biomass (AGB). However, the importance of these canopy properties in driving AGB in natural forests, especially relative to other drivers such as plant species diversity and environmental conditions, remains poorly understood. We assessed the relative importance of canopy properties (structure and spectral variables) and plant species diversity (multidimensional diversity metrics and trait composition) in regulating AGB along environmental gradients (topography and soil nutrients) in a temperate forest in Northeast China, using UAV-based LiDAR and hyperspectral data. We found that the explanatory power of environmental conditions, plant species diversity, canopy spectral properties and canopy structure on temperate old-growth forests AGB was 3.8%, 8.0%, 4.1% and 13.3%, respectively. AGB increased with increasing canopy height and structural complexity. Canopy spectral diversity was a better predictor of AGB than traditional diversity metrics in old-growth forests. Canopy spectral composition also played an important role in explaining AGB in the secondary forests. In addition, plant phylogeny, functional diversity and the community-weighted mean of acquisitive traits had significant direct positive effects on AGB. Finally, topography and soil nutrient content indirectly influenced AGB through canopy properties and plant species diversity. Our study highlights the key role of canopy properties in influencing AGB. For future monitoring, regular monitoring with spectral and LiDAR data should be emphasized to provide real-time insights for forest management.

Peatlands store one-third of the Earth’s carbon. Climate warming-induced peatlands vegetation shifted from Sphagnum to shrub, however, it is controversial whether this change leads to increased carbon losses. Through sequencing of the rhizosphere microbiome (vertically), measuring peat properties (vertically), a 35-day incubation experiment and a 35-day cross-inoculation experiment (only the upper layer), we investigated the ecosystem functions and the role of microbial communities and substrates in influencing the ecosystem functions of Sphagnum- and shrub-dominated peatlands in three locations in south China. The carbon dioxide (CO₂) emission from shrub-dominated peatlands was significantly lower than that from Sphagnum-dominated peatlands. The slow-growing fungi: Archaeorhizomyces, Hyphodiscus and Acidobacteria: Bryobacter, Occallatibacter were identified as keystone taxa in shrub-dominated peatlands, which mainly explained the effects of shrub microbial communities on CO₂ emission. The recalcitrant carbon content was the key substrate associated with CO₂ emission and the community composition of the plant rhizosphere microbiome. Furthermore, microbes fixed carbon in shrub-dominated peatlands was significantly higher than in Sphagnum-dominated peatlands, as the CO₂ emission reversed between Sphagnum- and shrub-dominated peatlands after soil sterilization. Overall, the relative abundance of keystone microbial taxa and nutrient levels decreased with peatland depth. Our study provided new evidence that climate change-induced peatland vegetation shift from Sphagnum to shrub leads to a higher accumulation of recalcitrant carbon, and does not deteriorate ecosystem functions. This study has implications for predicting the future influence of climate change on peatland ecosystems.

Terrestrial plants are colonized by various microorganisms in the rhizosphere, phyllosphere and endosphere. Variations of microorganisms between these niches could affect plant performance. While studies have indicated that microorganisms associated with invasive plants may facilitate their invasion success, niche effects on the composition, function and co-occurrence network of invasive plant microbiomes remain poorly understood. In this study, we investigated the bacterial and fungal communities in the rhizosphere soil, root and leaf endospheres of two invasive plants, Flaveria bidentis and Eclipta prostrata. Flaveria bidentis is a recently introduced species (introduced in 2001), whereas E. prostrata has been invaded in China for over 1000 years. We found that microbial community of F. bidentis and E. prostrata harbored more specialists, fewer unique amplicon sequence variants (ASVs), and lower diversity and network complexity in the leaf endosphere than that in the rhizosphere soil. Moreover, the bacterial and fungal communities in the rhizosphere soil, root and leaf endospheres of F. bidentis were more diverse, included more unique ASVs, and had a higher network complexity than those of E. prostrata. Predicted functional profiles revealed that there were more beneficial bacteria and fewer pathogenic fungi associated with F. bidentis than those with E. prostrata. These results demonstrate that there is a significant niche differentiation in the two invasive plant microbiotas, and this work may also indicate potential impact of residence time of invasive plants on plant-microbe interactions.

Closely related and co-distributed species usually share a common phylogeographic history, but it remains unclear whether ecologically interacting species can respond synchronously to historical climate changes. Here, we focused on a fig–pollinator mutualism comprising Ficus pumila var. pumila and its obligate pollinators (morphospecies Wiebesia pumilae), and collected samples across most of their distribution ranges. We employed cytoplasmic DNA sequences and nuclear microsatellite loci to reveal the species composition within the pollinators and to test whether the two mutualists exhibited similar postglacial phylogeographic patterns. We identified three cryptic pollinator species, with two dominant cryptic species exhibiting parapatric distributions in the northern and southern parts of the plant’s range, respectively. Similar current spatial genetic structures were detected in the two dominant cryptic pollinator species and the host plant, with both showing eastern and western genetic clusters. Moreover, evidence for postglacial expansion was found for all three species, and their potential refugia during the Last Glacial Maximum were located in the eastern and western parts of their distribution ranges. These results suggest synchronous responses to historical climate changes. Our study demonstrates congruent phylogeographic patterns between obligate mutualists and highlights the role of biogeographic factors in shaping the current biodiversity across trophic levels.

The stability mechanisms of ecosystem functions have been a hot topic in ecology. However, in wetland ecosystems, the mechanisms by which biotic and abiotic factors interact to affect ecosystem stability in changing environments remain largely unclear. This study investigated the key factors and underlying mechanisms that regulate the spatial variability of wetland productivity by measuring community productivity, multiple components of biodiversity (i.e. species diversity, community functional composition and diversity) and environmental factors along a well-characterized gradient of wetland degradation in the lower reaches of the Yellow River. The results showed that the spatial variability of productivity in wetlands increased with intensified degradation. The spatial variability of wetland productivity was not related to species richness but was mainly affected by changes in community functional composition and diversity. Furthermore, degradation-induced changes in soil nutrients drove the spatial variability of productivity to increase with shifts in functional composition towards more conservative traits (i.e. higher leaf dry matter content and root tissue density), and to decrease with higher functional trait diversity. These findings reveal the driving mechanism of spatial variability in wetland productivity under degradation, and suggest that reduced nutrient availability, by altering plant resource strategies, can affect the spatial reliability of key ecosystem functions in wetlands.

China represents a significant global hotspot for species in the family Fagaceae, which are widely distributed across the country and play a crucial role in various ecological and social systems. As the global cliamte is changing rapidly, predicting the future distribution and richness of these species in China holds substantial importance. This study presents the first national-scale assessment of the future distribution of 243 Fagaceae species in China, utilizing ensemble species distribution models (SDMs) for the 2050s and 2070s under various climate change scenarios. The SDM projections indicate notable changes in the distribution of Fagaceae species, characterizing with an overall decline in the distribution area, an upward migration in elevation and a northeastward shift in their range. These changes are expected to significantly alter the spatial pattern of species richness, creating possible refugia in the southwestern mountainous regions and the western Qinling Mountains. We further revealed that a considerable amount of China’s natural reserves will show decreased richness of Fagaceae under climate change. Our study systematically evaluates the impact of future climate change on the distribution of Fagaceae species in China, potentially helpful for conservation planning of these species in China.

Grasslands are highly diverse ecosystems providing important ecosystem services, but they currently face a variety of anthropogenic stressors simultaneously. Quantifying grassland responses to global change factors (GCFs) is crucial for developing effective strategies to mitigate the negative impacts of global change on grassland communities and to promote their resilience in the face of future environmental challenges. We conducted a field experiment in the Songnen grassland, northeastern China, to test the combined effects of 0, 1, 2, 4, 6, and 8 GCFs, including fungicide, herbicide, insecticide, antibiotic stress, heavy metal pollution, light pollution, microplastic pollution, nitrogen deposition, tillage disturbance, and increased precipitation. We found that within one year, the increasing number of GCFs negatively impacts both the productivity and diversity of grassland communities. In comparison to exposure to a single GCF, exposure to 8 GCFs led to a reduction in productivity and species richness by 42.8% and 42.9%, respectively. Furthermore, these negative effects seem to be linked to the reduction of dominant species and the concurrent increase in neonative species (i.e., species that have expanded their geographic range into a new area without direct human assistance, but as an indirect consequence of human-induced environmental changes). The results of hierarchical diversity-interaction modeling suggested that the adverse impacts of an increasing number of GCFs on community productivity and diversity are attributable to both the specific identities of GCFs involved and their unique pairwise interactions. The results suggest that grasslands may quickly lose stability and degrade more rapidly in response to multiple co-occurring GCFs. Greater efforts should be made to conserve the functions and services of grassland ecosystems by reducing the impacts of human activities.

Floodplain wetlands have a signifcant capacity for carbon sequestration but are vulnerable to land use changes. Poplars are extensively planted in wetlands due to the increasing demand for wood products and bioenergy. Although the large biomass of poplar may increase the carbon stock in wetlands, their high transpiration rates may reduce soil moisture, thereby improving the aeration and facilitating the oxidation of organic materials. Therefore, the impact of poplars on wetland carbon stock remains uncertain and unexplored. Here, we investigated the effects of poplar plantations on biomass carbon stock (BCS) and soil organic carbon (SOC) stock in Dongting Lake wetlands, China, using native Miscanthus lutarioriparius vegetation as a control. Our results indicated that the BCS of middle-aged and near-mature poplar plantations (36.47–81.34 t ha⁻¹) was higher than that of M. lutarioriparius (8.31 t ha⁻¹), and it increased with stand age. The SOC stock within the 0–60 cm depth in young, middle-aged, and near-mature poplar plantations (130.32–152.58 t ha⁻¹) were higher than those in M. lutarioriparius (70.48 t ha⁻¹), but they did not increase with stand age. The BCS was positively associated with soil bulk density, while SOC stock was negatively associated with soil sand content. Overall, our fndings indicate that poplar plantations increase carbon stock in the Dongting Lake wetlands. Nevertheless, the longterm effect of poplar plantation on carbon sequestration in foodplain wetlands should be further investigated.

Phenological models are valuable tools for predicting vegetation phenology and investigating the relationships between vegetation dynamics and climate. However, compared to temperate and boreal ecosystems, phenological modeling in alpine regions has received limited attention. In this study, we developed a semi-mechanistic phenological model, the Alpine Growing Season Index (AGSI), which incorporates the differential impacts of daily maximum and minimum air temperatures, as well as the constraints of precipitation and photoperiod, to predict foliar phenology in alpine grasslands on the Qinghai–Tibetan Plateau (QTP). The AGSI model is driven by daily minimum temperature (T_min), daily maximum temperature (T_max), precipitation averaged over the previous month (PA), and daily photoperiod (Photo). Based on the AGSI model, we further assessed the impacts of T_min, T_max, PA, and Photo on modeling accuracy, and identified the predominant climatic controls over foliar phenology across the entire QTP. Results showed that the AGSI model had higher accuracy than other GSI models. The total root mean square error (RMSE) of predicted leaf onset and offset dates, when evaluated using ground observations, was 12.9 ± 5.7 days, representing a reduction of 10.9%–54.1% compared to other models. The inclusion of T_max and PA in the AGSI model improved the total modeling accuracy of leaf onset and offset dates by 20.2%. Overall, PA and T_min showed more critical and extensive constraints on foliar phenology in alpine grasslands. The limiting effect of T_max was also considerable, particularly during July–November. This study provides a simple and effective tool for predicting foliar phenology in alpine grasslands and evaluating the climatic effects on vegetation phenological development in alpine regions.

Plant crown can affect the seed dispersal process. Clarifying the influence of plant crown type on seed dispersal kernel is important for predicting species distribution. However, the effects of different plant crown types on seed dispersal have rarely been tested. To address this, we conducted wind tunnel experiments to investigate the average seed dispersal distance, range, kurtosis and skewness of 29 species with varying diaspore traits (e.g., appendage type, mass, projected area, shape index, wing loading and terminal velocity) under 3 wind speeds (2, 4 and 6 m s⁻¹). We examined seeds passing through different crown types, classified based on crown size, branch density, and the presence or absence of leaves. We fitted functions to the seed dispersal distance and found that the Gaussian function provided the best fit. Our results showed that plant crown type had significant effects on dispersal kurtosis and skewness but not on the average dispersal distance or range under low wind speed conditions. Specifically, crown width and branch density influenced dispersal kurtosis, while the presence of leaves affected both kurtosis and skewness. Increasing wind speed reduced the influence of plant crowns on dispersal kurtosis and skewness. Although plant crowns did not significantly affect average seed dispersal distance, they altered the shape of the seed dispersal kernel. Consequently, while the dispersal range of seeds through different crowns remained relatively invariant, the density of dispersal varied significantly. These findings provide valuable insights into plant metapopulation dynamics and highlight the importance of considering crown architecture in seed dispersal studies.

During the restoration of degraded ecosystems, different shrub species often segregate along environmental water gradients. However, the physiological mechanisms driving this segregation remain unclear. To address this gap, we conducted a drought stress experiment (70%–80% field water holding capacity, CK; 40%–50% field water holding capacity, MD; 20%–30% field water holding capacity, SD) to explore the physiological mechanisms driving the dominance of different shrub species at various stages of ecosystem restoration. Salix gordejevii, a species dominant in the early stages of restoration with high water availability, and Caragana microphylla, a species dominant in the later stages under low water availability, were studied. The results showed that the living state index (LSI) of S. gordejevii was significantly lower than that of C. microphylla under drought stress (P < 0.05). Differences in plant hydraulics and water-use strategies explained how these species adapt to varying soil moisture conditions. Salix gordejevii employed a proactive water-use strategy with lower water-use efficiency (WUE) and reduced resistance to xylem embolism (xylem water potentials corresponding to 50% loss of conductivity, P₅₀), making it better suited to environments with more abundant water. In contrast, C. microphylla adopted a conservative water-use strategy. This strategy was characterized by increased WUE and enhanced resistance to drought-induced xylem embolism, which allowed it to thrive under more drought-prone conditions. Importantly, hydraulic efficiency (⁠K_leaf, K_s, and K₁) emerged as the primary determinant of living state in both S. gordejevii (47.30%) and C. microphylla (62.20%). The lower embolism resistance of S. gordejevii (⁠P₅₀ = 1.3 MPa) made it more susceptible to xylem cavitation, leading to a decline in hydraulic efficiency under SD. In contrast, C. microphylla’s higher embolism resistance (⁠P₅₀ = 2.3 MPa) enabled it to maintain stable hydraulic conductance across all drought treatments. These differences in hydraulic efficiency, driven by xylem embolism resistance, were key factors influencing shifts in shrub dominance during ecosystem restoration. These findings provide a physiological explanation for the replacement of shrub species during ecosystem restoration, where soil moisture is the main limiting factor.

Precipitation significantly influences the composition and structure of grassland ecosystems, particularly in arid desert steppes. Stipa breviflora, as a keystone species, plays a crucial role in maintaining the stability of the desert steppe. However, the response of S. breviflora’s succession strategy to changes in precipitation within the community remains uncertain. Since 2016, this research was conducted in a desert steppe in Inner Mongolia, China, involving control precipitation (PCK), and increases of 50% (P50) and 100% (P100) in natural precipitation. We measured biomass, height and canopy cover, calculated the importance value (IV) by species, and assessed the photosynthetic parameters and leaf elemental content of S. breviflora in 2021 and 2022. Results showed that the increase of precipitation significantly reduced the IV of S. breviflora. The net photosynthetic rate, transpiration rate, stomatal conductance, aboveground biomass carbon content and aboveground biomass nitrogen of S. breviflora leaves grew considerably in experimental plots receiving more precipitation, while δ¹³C value of leaves decreased significantly. Linear regression analysis and structural equation model showed that although the increase of precipitation improved the adaptability of S. breviflora functional traits and increased its IV, a higher transpiration rate significantly contributed to the decrease in its IV. Consequently, our research reveals the succession strategy of S. breviflora and provides a theoretical basis for studying the response mechanisms of desert steppe plant communities to climate change.

Leaf construction cost (LCC), a proxy for the energetic investment plants make to construct leaf biomass, indicates carbon investment strategies of plants across diverse habitats. However, large-scale variations in LCC and their correlations with climate and soil factors have yet been fully explored. To address this knowledge gap, here, we compiled a dataset comprising 442 species-site combinations, spanning nearly all vegetation types in China. We found that LCC exhibited substantial variation, ranging from 0.72 g glucose g⁻¹ to 1.93 g glucose g⁻¹, with an average of 1.25 g glucose g⁻¹. LCC was significantly higher in woody species compared to nonwoody species; however, there was no significant difference in LCC between evergreen and deciduous plants. LCC decreased with increasing latitude and longitude but increased with increasing altitude. Among bivariate LCC-environment relationships, LCC was positively correlated with mean annual precipitation and temperature but negatively correlated with temperature seasonality, precipitation seasonality, soil potassium content, and soil silt content. Collectively, climate and soil factors account for over 54% of the variance in LCC, with soil exerting a more significant influence than climate on LCC. This study offers an exhaustive analysis of the evident pattern of LCC over a large spatial scale, fostering a fresh perspective on functional biogeography and establishing the foundation for exploring the interplay between LCC, ecological functions, and macroevolutionary implications.

Atmospheric carbon dioxide (CO₂) concentrations have been increasing dramatically due to human activities and land use changes, and the CO₂ fertilization effect significantly increases global net primary productivity. However, whether the decomposition of surplus litter input on the soil surface is facilitated by elevated CO₂ (eCO₂) across a broad range of terrestrial ecosystems is not fully understood. We compiled 227, 85 and 131 paired observations (with and without eCO₂) for litter mass loss, carbon (C) and nitrogen (N) release, respectively, during litter decomposition to assess the fate of decomposing litter and C and N release under eCO₂ across terrestrial ecosystems. Litter mass loss was decreased by 4.5%, and C and N release were significantly reduced by 6.7% and 3.4%, respectively, under eCO₂. This eCO₂ effect on litter mass loss was greater in forests (decreased by 7.2%) than in croplands and grasslands. In forests, eCO₂ had a greater effect on the decomposition rate of broadleaved than coniferous litter, and root litter was more sensitive than leaf and stem litter. Changes in litter lignin concentration and edaphic factors under eCO₂ contributed to these differences in litter decomposition. Greater decreases in litter mass loss and C and N release were found after longer time (6–12 months) than short-term (less than 6 months) CO₂ enrichment. A possible consequence is that more litter accumulates on the soil surface without being decomposed due to eCO₂ in terrestrial ecosystems over longer time periods, resulting in a negative loop in biogeochemical cycles with increasing atmospheric CO₂ concentration.

Plant root-associated fungal communities play a pivotal role in enhancing plant growth, nutrient absorption, disease resistance and environmental stress adaptation. Despite their importance, the assembly processes of these communities remain inadequately explored. In this study, we utilizzzed high-throughput sequencing, co-occurrence network analysis and null models to examine the diversity, composition, interaction patterns and assembly mechanisms of the root-associated fungal communities of Mussaenda pubescens, a drought-tolerant shrub that thrives in stressful environments and is widely used for Chinese medicine. Our findings revealed pronounced regional and ecological niche-based variations in the diversity and assembly of total fungi and essential functional guilds, including saprotrophs, symbiotrophs and plant pathogens. Significantly, the fungal diversity of plant pathogens decreased with elevation, whereas total fungi, saprotrophs and symbiotrophs were minimally affected. Stochastic processes, such as dispersal limitation, played a significant role in fungal assembly. Furthermore, soil physicochemical properties, climatic conditions and spatial variables emerged as critical determinants of fungal community structure. This study enriches our understanding of the dynamics governing root-associated fungal community assemblies and underscores the factors essential for sustaining fungal diversity.

Soil microorganisms play a crucial role in alpine grassland ecosystem as indicators of environmental change. Rest-grazing in spring has been shown to effectively curb grassland degradation, and while the effects on plants and soil have been widely studied, the response of soil microbial communities and the underlying driving factors remain unclear. In this study, two types of winter-spring pastures, steppe meadow (StM) and swamp meadow (SwM), were conducted for rest-grazing and grazing in spring, and vegetation community characteristics, soil properties and microbial community composition were measured to investigate the response of soil microbial communities to rest-grazing and its mechanisms. The results showed that rest-grazing in spring significantly increased above-ground biomass and soil organic carbon in alpine grasslands. In the steppe meadow, microbial groups were lower in the first year of rest-grazing compared to grazing but higher in the second year. In the swamp meadow, microbial groups and the ratio of Gram-positive to Gram-negative bacteria were higher under rest-grazing than under grazing. Stress indices in both grassland types were lower under rest-grazing than under grazing. Fungi showed an increasing trend with above-ground biomass (P < 0.05), while total PLFAs, bacteria, and actinomycetes increased with below-ground biomass (P < 0.05). Variance partitioning analysis (VPA) revealed that the combination of soil and vegetation properties explained 40.87% of the variation in the soil microbial community. Redundancy analysis (RDA) indicated that species diversity (Simpson index), vegetation coverage, soil total phosphorus, and bulk density were significant influencing factors, with species diversity explaining the largest proportion of variation (60%). In summary, rest-grazing in spring can beneficially affect the soil microbial community by improving plant diversity and restoring soil properties in alpine grasslands.

Traits and their correlation networks can reflect plant adaptive strategies. However, variations in traits and trait correlation networks across heteromorphic leaves within species remain largely unexplored. In this study, we systematically quantified a diverse array of leaf traits—spanning morphology, anatomy, physiology and biochemistry—among the striped, lanceolate, ovate, and broadly ovate leaves of Populus euphratica, aiming to elucidate the adaptive differences across these various leaf types. We found that the four heteromorphic leaves showed significant differences in leaf traits. From striped leaves to broadly ovate leaves, leaf size, leaf thickness, water use efficiency and catalase content significantly increased, while specific leaf area showed the opposite pattern. Principal component analysis and cluster analysis revealed distinct aggregation and clear demarcation of the four leaf types, indicating substantial variations in trait compositions and their distinct ecological adaptations. Plant trait networks varied significantly across the four leaf types, with the broadly ovate leaves exhibiting a fragmented network structure that enhances their modularity. This suggests strong resilience to disturbances and is consistent with the characteristic foliage on mature trees. Regardless of leaf type, nitrogen and phosphorus consistently emerged as hub traits within plant trait networks, underscoring their fundamental role in driving physiological processes and influencing phenotypic expression. This study meticulously delineates the variations in both individual leaf traits and trait correlation networks across the heteromorphic leaves of P. euphratica, significantly deepening our understanding of plant adaptive strategies.

Studies on diversity–biomass relationships (DBRs) provide insights into the mechanisms underlying ecosystem functioning and services. While manipulative experiments indicate that both functional diversity and functional dominance influence biomass, with functional diversity often becoming the stronger predictor over time, their relative contributions during natural forest succession remain unclear. Here, we analysed tree data from 2010 to 2020 across early, middle and late-successional forests in subtropical China to investigate how the effect of taxonomic diversity on aboveground biomass (AGB) is related to shifts in the roles of functional diversity and functional dominance of five functional traits, corresponding to the complementarity and biomass ratio hypothesis. Our results showed that mean AGB increased with succession, reaching its highest at the middle stage. Taxonomic diversity influenced AGB primarily through its impact on functional properties rather than directly. From early to late-successional stages, functional dominance consistently emerged as the stronger predictor of AGB compared to functional diversity. Specifically, in earlier stages, the dominance of species with fast leaf economic traits directly and negatively impacted AGB, whereas, in the late stage, the dominance of tall species had a direct positive impact. Although functional diversity contributed increasingly to AGB in a positive manner during succession, its effect was primarily indirect, largely mediated through functional dominance. Overall, our findings support the biomass ratio hypothesis as the primary mechanism underlying DBRs throughout succession. This highlights the importance of functional dominance in driving forest biomass production and emphasizes the need to consider dominant species’ traits in forest management and restoration strategies.

Soil microbes play a critical role in maintaining the health and stability of these ecosystems. However, the ecological assembly processes of soil microbial communities remain poorly understood. This study explores the changes in ecological components across original and degraded patches of alpine meadows in Sanjiangyuan National Park and analyzed soil microbial community structure using high-throughput sequencing techniques. Results showed that alpine meadows degradation increased vegetation species diversity, significantly reduced aboveground productivity, and made the soil more barren and alkaline. Although the dominant phyla of soil microorganisms were similar across different degradation states, degradation significantly increased the relative abundance of oligotrophic bacteria and decreased the relative abundance of dominant fungi. Additionally, microbial communities exhibited significant β-diversity. Degradation also led to an increase in microbial α-diversity, heightened microbial taxa competition and a more complex microbial co-occurrence network. However, vegetation-soil variables explained only a small portion of the variation in soil microbes. Through the study of microbial ecological assembly processes, we found that degradation enhanced the stochastic processes of soil microbial communities, and the changes in soil microbial communities were mainly driven by the variations inherent in the microbes themselves. These findings highlight the complex ecological interactions between above- and belowground components and emphasize the critical role of microbial community dynamics in mediating ecosystem functions.

Unraveling the legacy effects of long-term climate warming is essential to for an integrated understanding of plant invasion success. However, knowledge regarding how these legacy influences invasive offspring and natural enemies remains lacking. This work was built on a long-term warming experiment established in 2012. Here, we selected invasive Solidago canadensis and performed a series of experiments to explore the effects of experimental warming on offspring S. canadensis from its native and invaded range, as well as the legacy effect of warming on three insect species, and three pathogens. The experience of long-term maternal warming facilitated the growth of offspring from invasive S. canadensis, regardless of the presence of insects or pathogens. This experience decreased insect growth when feeding on native S. canadensis, and inhibited pathogens when infecting invasive S. canadensis. Additionally, the presence of natural enemies could modulate the legacy effects of warming and population provenance. These results suggest that long-term climate warming could facilitate invasion success via coordinated increases in growth and defense, and that legacy effects of climate warming and maternal provenance are important for understanding the cascading effects of climate warming.