Stand development shifts nitrogen cycling strategies and supply-demand balance in larch plantations

Stand development shifts nitrogen cycling strategies and supply-demand balance in larch plantations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Stand development shifts nitrogen cycling strategies and supply-demand balance in larch plantations Xiaotong Chen, Zhaoxuan Ge, Yue Pang, Qiang Liu, Zhidong Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9084654/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract Nitrogen (N) often constrains forest productivity; however, how N-use strategies and the ecosystem N balance are reorganized during stand development remains poorly understood in cold-temperate plantations. In this study, N stocks and key fluxes were quantified across vegetation, litter, and soil in larch ( Larix principis-rupprechtii ) plantations with four stand ages (11, 23, 37, and 47 years) in northern China. Age-related shifts in N-use strategies were evaluated, and piecewise structural equation modeling (pSEM) was applied to identify pathways linking stand age to ecosystem N cycling. The results showed that vegetation biomass and N stocks were found to increase significantly with stand age, whereas ecosystem N storage was dominated by soil (> 87%) across all stand ages. Soil available N supply was consistently larger than annual plant N uptake, indicating no evidence of N limitation during stand development. An age-dependent shift was observed from a resource-acquisitive strategy in young stands, characterized by stronger reliance on soil N acquisition, to a resource-conservative strategy in older stands, characterized by increased litter return and enhanced plant N resorption. N use efficiency was maximized at the mid-aged stage (37 years). Ecosystem N uptake and cycling were indirectly regulated by stand age through its effects on N status in plants, litter, and soil. Overall, a relatively stable balance between N supply and demand was maintained throughout stand development, and an increasingly internal cycling-dominated nutrient-use strategy was formed. These findings highlight the importance of stand age-mediated N nutritional strategies in sustaining larch plantation productivity. Nutrient recycling Nitrogen use efficiency Larch plantation Stand age Supply-demand balance Plant-soil interactions Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Nitrogen (N) is a fundamental element regulating plant growth and ecosystem primary productivity. As a key component of proteins, nucleic acids, and chlorophyll, N directly supports essential physiological processes such as photosynthesis and respiration [1–3]. However, the availability of bioavailable N in soils often fails to match plant demand, making N one of the most pervasive constraints on ecosystem productivity. Numerous studies have shown that N limitation is widespread across forest ecosystems globally, with particularly strong effects in boreal and temperate forests where limited N supply can markedly restrict biomass accumulation and carbon sequestration [2, 4]. During stand development, growth rates, biomass allocation, and soil nutrient status are continuously altered, and stage-dependent variations in the intensity and ecological consequences of N limitation are therefore expected [5]. At the ecosystem scale, N limitation is not determined solely by the magnitude of soil N pool, but instead depends on the balance between soil N supply and plant N demand (i.e., the N supply-demand balance) [6]. This balance has been regarded as a core indicator for diagnosing N limitation in forest ecosystems [7]. When supply and demand are mismatched, tree growth may be reduced, litter decomposition may be constrained, and soil acidification may be intensified. Because most soil N occurs in organic forms that are not directly available to plants, total soil N storage alone cannot adequately reflect actual N availability. In contrast, available N pools (e.g., alkali-hydrolysable N) have been considered to better approximate the effective N supply available to plants [8]. Consistent with this view, pronounced adjustments in soil N supply capacity and its coordination with plant demand have been reported across stand developmental stages [9]. From a process-based perspective, the ecosystem N supply-demand balance is jointly regulated by coupled fluxes, including plant N uptake, internal retention, litter return to soil, and N resorption prior to senescence [10–13]. Plant N demand is influenced not only by growth rate, but also by N use efficiency (NUE) and the capacity for internal N recycling [14–16]. When soil available N becomes limiting or stands approach maturity, higher N resorption efficiency is often induced, internal N recycling is strengthened, and biomass allocation is adjusted, thereby reducing reliance on external N inputs [17, 18]. Consequently, stand development is typically accompanied by a shift from a resource-acquisitive strategy toward a resource-conservative strategy [19]. In parallel, N cycling is often transitioned from a relatively open system to a more closed system that increasingly depends on litter-microbe-mediated internal recycling to maintain nutrient balance[20]. N cycling is inherently a complex, multi-component system involving vegetation, litter, and soil, which are tightly coupled through both direct and indirect pathways [21]. During stand development, N distribution and cycling among ecosystem components may be reorganized through changes in vegetation biomass accumulation, litter inputs, and soil nutrient turnover, rather than through changes in total N storage alone [22]. Therefore, the multi-path mechanisms by which stand age regulates N cycling need to be resolved to advance a mechanistic understanding of forest nutrient dynamics. Piecewise structural equation modeling (pSEM) provides a powerful framework for disentangling such multivariate pathways by partitioning direct effects of stand age from indirect effects mediated by vegetation, litter, and soil properties [23]. Larch (Larix principis - rupprechtii ), a dominant afforestation species in cold-temperate regions of northern China, is characterized by rapid growth and strong environmental adaptability, and is widely recognized for its contributions to timber production and ecosystem functioning [24]. However, productivity decline and site degradation have been frequently reported in near-mature and mature larch plantations. These declines have been closely linked to shifts in nutrient availability, particularly changes in N supply-demand relationships [5]. To date, research has largely emphasized soil C:N ratios or individual N pool characteristics, whereas integrated quantification of ecosystem N supply-demand balance and its regulatory mechanisms across stand development remains limited [13, 20]. This gap has constrained a comprehensive understanding of N cycling dynamics in these plantations. Against this background, larch plantations with four stand ages (11, 23, 37, and 47 years) were investigated. Biomass and N stocks in vegetation, litter, and soil were quantified; ecosystem-scale N fluxes (uptake, retention, litter return, and resorption) were estimated; and indices describing N acquisition and cycling strategies were calculated. In addition, pSEM was applied to clarify the multiple pathways by which stand age affects ecosystem N cycling. Specifically, this study aimed to: (1) characterize variations in N cycling fluxes and N nutritional strategies across stand ages; (2) evaluate ecosystem-scale N supply-demand status during stand development; and (3) identify key processes underlying the stand age-driven transition from external N acquisition to internally regulated N cycling. 2. Materials and Methods 2.1 Study area and plot establishment The study area is located in the Saihanba Forest Center, Hebei Province, China (42°02′−42°36′ N, 116°51′−117°39′ E)[25], at elevations of 750 − 1998 m. The region is typified by a semi-arid to semi-humid, cold-temperate continental monsoon climate. The mean annual temperature is -1.3°C, with extreme temperatures ranging from − 43.2 to 33.4°C. The mean annual precipitation is approximately 460 mm, of which 65.8% occurred during the growing season (June−August). The average frost-free period is approximately 64 days per year [26]. Extensive overgrazing during the early twentieth century resulted in severe degradation of natural forests in this region. In response, large-scale afforestation programs were launched in 1962 using larch and other cold- and drought-tolerant species (e.g., spruce). Larch plantations were initially established at a density of approximately 5,000 trees ha − ¹ [27]. Since 1983, forest management has shifted from afforestation to stand tending and structural regulation [28]. To date, five large-scale thinning interventions have been implemented, which have reduced the stand density of mature forests to about 600 − 900 trees·ha − ¹. Currently, larch plantations cover approximately 38,000 ha in the study region, with a total standing volume of 6.59 million m³. Vegetation in the study area comprises coniferous and broadleaved forests, shrublands, and meadow ecosystems. The main plantation species include Larix principis-rupprechtii , Pinus sylvestris var. mongolica , and Betula platyphylla . The shrub layer is dominated by Rhododendron mucronulatum , Spiraea salicifolia , and Rosa davurica , while the herb layer is characterized by Trollius chinensis , Taraxacum mongolicum and Picris hieracioides . In June 2023, larch plantations with four stand-age stages (11, 23, 37, and 47 years) were selected. To reduce potential bias associated with the chronosequence design, plots were established under similar topographic conditions, soil types, and management histories. Three replicate plots (30 m × 30 m) were established for each stand age (n = 12). Adjacent plots were separated by > 100 m [29] (Fig. 1 ). A complete tree inventory was conducted in each plot (Table 1 ). Table 1 Basic information of the larch plots with different stand ages Age (year) Elevation (m) Number of plots Aspect Slope (°) DBH (cm) Average height (m) Stand density (tree·ha − 1 ) 11 1606 − 1616 3 North 0 − 1 7.31 ± 2.46 7.29 ± 1.15 2006 ± 59 23 1624 − 1635 3 North 1 − 5 15.22 ± 2.60 14.75 ± 1.28 1511 ± 169 37 1639 − 1652 3 North 4 − 8 23.22 ± 4.76 20.56 ± 3.06 903 ± 73 47 1664 − 1672 3 North 0 − 3 24.06 ± 4.11 21.63 ± 3.48 737 ± 23 All plant materials used in this study were obtained from larch ( Larix principis-rupprechtii ) plantations located in Saihanba Mechanical Forest Farm, Hebei Province, China. The stands were established using locally sourced seeds, with local seed collection, seedling cultivation, and outplanting, and were naturally regenerated through seed dispersal. All tree, shrub, and herb species recorded in the study plots are native to the region and were not associated with any introduced or invasive species. Sample collection was conducted with permission from the Saihanba Mechanical Forest Farm administration. Field sampling complied with relevant institutional, national, and international guidelines, as well as local legislation. The studied species is not listed as a protected species under Chinese regulations. Species identification was carried out by a qualified forestry expert from Saihanba Mechanical Forest Farm based on morphological characteristics and standard taxonomic references. Representative samples were documented photographically during field sampling. No voucher specimens were deposited, as the study focused on ecological processes in managed plantation stands rather than taxonomic verification. 2.2 Sample collection and laboratory analysis In each tree layer plot, three shrub quadrats (3 m × 3 m) were randomly established along the plot diagonal. In each shrub quadrat, one 1 m × 1 m herb plot was further randomly selected. To quantify tree growth, 10 healthy trees were randomly selected in each plot, and dendrometer bands were installed at breast height (1.3m) to monitor radial growth from July 2023 to July 2024. Measurements were conducted monthly during the growing season (late April to early September) and at three-month intervals during the non-growing season. In addition, three healthy trees with mean DBH and height were selected per plot as sample trees. Approximately 200 g of tissue samples from stem, branch, leaf, and coarse root were collected from each sample tree. Fine roots were sampled from the sampled soil layer around each sample tree using a soil auger (10 cm diameter). Litterfall was collected at three evenly distributed points within each plot. At each point, a litter trap (0.75 m × 0.75 m; 0.5625 m²) was installed using nylon mesh supported by a PVC frame and suspended 0.75 m above the ground. Litterfall was collected periodically in October and December 2023 and May 2024. In addition, a 20 cm × 20 cm forest floor quadrat was established adjacent to each trap to collect accumulated surface litter. All litter samples were sorted, oven-dried, and analyzed for N concentration. Soil was sampled adjacent to each litter collection point. After removing surface litter, soil cores were obtained at 0 − 10, 10 − 20, and 20 − 30 cm using a cutting-ring corer (100 cm 3 ) to determine bulk density. Additional soil samples (approximately 500 g) from the same depth intervals were collected using a 10 cm diameter auger for physicochemical analyses. Moreover, organic-layer samples (0 − 1 cm) were collected to determine organic matter. For each plot, soils from the same depth were composited, air-dried, sieved, and cleared of roots and stones prior to the determination of total N and alkali-hydrolysable N. 2.3 Estimation of nitrogen stocks Biomass of different tree organs (stem, branches, leaves, and coarse roots) was estimated using species-specific allometric equations [30] (Formula S1). N stocks (t·ha − ¹) in tree, shrub, and herbaceous components, as well as in different litter fractions, were estimated by multiplying biomass by the corresponding N concentration (g·kg − ¹). Total N stock for each ecosystem component was then obtained by summing the corresponding N pools in each plot. Calculations of total N and alkali-hydrolysable N stocks in different soil layers are provided in Formula S2 in the Supplementary Materials. 2.4 Calculation of nitrogen fluxes, nitrogen use efficiency, and nitrogen cycling indices At the ecosystem scale, N fluxes were quantified as annual N uptake, annual N retention, annual N return, and annual N resorption (NRE)[29]. Annual N uptake was defined as the total amount of N absorbed from the soil and assimilated into plant organs within one year [31]. It was assumed to equal to the sum of NRE and annual N return [32]. Annual N retention was defined as the annual increase in N stocks of tree organs (t·ha − ¹) [33]. For belowground N return, annual fine-root turnover was assumed; thus, fine-root N stocks was used to represent belowground N inputs. Annual N return was calculated as the sum of N input from aboveground litterfall and fine-root turnover. During July 2023–July 2024, litterfall was collected throughout the year, and fine roots in the 0–20 cm soil layer were sampled in July 2023. N stocks of litter fractions and fine roots were determined and summed to estimate annual N return. N resorption represents an important internal nutrient-conservation strategy whereby N is withdrawn from senescing leaves and reallocated to perennial tissues (e.g., branches, stems, and roots) prior to abscission [34]. NRE (t·ha − ¹) was derived from the difference in N concentration between mature and senesced needles, adjusted for mass loss during senescence to ensure accuracy [35] (Formulas S3 − S4). NUE characterizes the organic biomass yield per unit of absorbed N [36]. In addition, the N cycling coefficient (NCC) was calculated to represent the proportion of plant-acquired N that is returned to the soil via litterfall internally recycled, rather than being sustained by continued external N inputs (Formulas S5 − S6). 2.5 Calculation of nitrogen nutritional strategy indices To characterize plant N nutritional strategies, indicators were selected to represent N acquisition and N cycling, following Lang et al. [37]. N uptake efficiency (NUpE), N enrichment in topsoil, and the proportion of available nitrogen in soil were used to quantify N acquisition strategies, accumulation of N in forest floor litter, turnover rate of forest floor litter (%), and the internal N cycling ratio were used to quantify N cycling strategies[29] (Formulas S7 − S12). 2.6 Statistical analysis Statistical analyses were conducted using R 4.3.3 [38]. Before statistical analyses, the data were tested for normality and homogeneity of variances. The study uses ANOVA to perform one-way analysis of variance and to test two-way interaction effects. The analysis then applies Tukey’s HSD test for multiple comparisons. The study examines whether biomass, nutrient concentration, nutrient storage, nutrient flux, and nutrient strategy indices differ among forest age classes. The study sets the significance level at p < 0.05. PCA was performed separately for plant nutrients, litter nutrients, soil nutrients, N uptake, and N cycling variables. Scores of the first principal component (PC1) were extracted and used as composite indicators of plant nutrient status (Plant_N), litter nutrient status (Litter_N), soil nutrient status (Soil_N), N acquisition status (N_acquisition), and N cycling status (N_cycling) in subsequent analyses (Table S1 ). A pSEM approach was applied to quantify the multi-path mechanisms by which stand age regulates N cycling. Before model construction, all variables were standardized. Correlation analysis and redundancy screening were conducted to reduce collinearity and avoid model overparameterization. In the pSEM framework, stand age was specified as an exogenous variable, whereas nutrient status in plant, litter, and soil, together with N acquisition and internal cycling processes, were specified as endogenous variables. Model fit was evaluated using Fisher’s C statistic, and standardized path coefficients and coefficient of determination (R 2 ) were used to quantify the strength of relationships among variables. 3. Results 3.1 Nitrogen concentrations of ecosystem components across stand ages Significant differences in N concentrations among tree organs were detected among stand age gradient (Table 2 ). Across all stands, leaves consistently showed the highest N concentration, and did not vary significantly with stand age ( p > 0.05). By contrast, N concentrations in stems, branches, fine roots, and coarse roots were significantly higher in the 11- and 47-year-old stands than in the 23- and 37-year-old stands. Understory vegetation and surface litter showed only minor variation in N concentration across stand ages, with significant differences observed only for the herbaceous layer among certain age classes. Soil N concentrations showed limited variation among stand ages, and significant differences occurred only in the 10 − 20 cm layer, where the 11-year-old stand had a lower N concentration than the other stands ( p < 0.05). Table 2 N concentration (g·kg⁻¹) in different parts of L. principis-rupprechtii plantations across stand ages. Organs Stand age (year) 11 23 37 47 Tree Tree stem 3.59 ± 0.22a 1.61 ± 0.18b 1.58 ± 0.15b 3.04 ± 0.21a Tree branch 2.99 ± 0.04ab 1.18 ± 0.25c 1.97 ± 0.17bc 3.55 ± 0.38a Tree leaf 21.10 ± 0.57a 23.47 ± 1.00a 21.58 ± 0.98a 24.35 ± 1.23a Tree coarse root 5.85 ± 0.74a 3.81 ± 0.37ab 3.09 ± 0.42b 5.10 ± 0.08ab Tree fine root 10.85 ± 0.42ab 8.37 ± 0.08c 9.18 ± 0.35bc 11.64 ± 0.60a Shrub-herbs Shrub 10.99 ± 0.31a 12.73 ± 1.16a 11.25 ± 0.85a 13.93 ± 0.44a Herbs 12.91 ± 0.72b 17.85 ± 1.14a 16.30 ± 0.19ab 19.44 ± 0.80a Forest floor litter 11.92 ± 0.73a 11.01 ± 0.56a 11.85 ± 0.34a 11.23 ± 1.33a Soil 0 − 1 cm organic horizon 5.29 ± 0.03a 5.02 ± 0.33a 6.97 ± 0.25a 5.50 ± 0.81a 0 − 10 cm mineral 2.84 ± 0.31a 3.45 ± 0.61a 3.81 ± 0.17a 3.40 ± 0.15a 10 − 20 cm mineral 1.86 ± 0.11b 3.06 ± 0.34a 3.08 ± 0.12a 2.47 ± 0.03ab 20 − 30 cm mineral 2.41 ± 0.39a 2.10 ± 0.06a 3.64 ± 0.47a 3.03 ± 0.22a Note : Values in the table are showed as mean ± standard deviation (n = 3). Different lowercase letters indicate significant differences among stand ages at the p < 0.05 level. 3.2 Biomass, nitrogen stocks and nitrogen allocation across stand ages Significant stand-age effects were observed for the biomass and N stocks of vegetation components (Fig. 2 ). Both biomass and N stocks in the tree layer increased continuously with stand development and have dominated the vegetation N pool across all ages. A significant unimodal pattern was observed in the forest floor litter layer. In contrast, biomass in the shrub-herb layer showed a significant decline from 11 to 23 years. At the ecosystem scale, soil was consistently identified as the largest N pool, accounting for > 87% of total ecosystem N stocks across all stand ages (Table S1 ). Significant differences were found in the allocation of biomass and N stocks among organs in the tree-shrub-herb layers (Fig. 3 ). In the tree layer, biomass and N stocks of all organs were increased significantly with stand age ( p < 0.001). Both biomass and N storage were consistently dominated by stems, whereas leaves contributed relatively little throughout stand development (Fig. 3 a,d). In the shrub layer, organ biomass and N stocks were decreased sharply from the young stage (11 years) to the middle-aged stage (23 years) and were followed by only a slight recovery thereafter ( p 0.05) (Fig. 3 c, f). 3.3 Nitrogen fluxes, nitrogen use efficiency, nitrogen cycling coefficient and soil nitrogen supply status Annual N uptake and annual N retention all increased with stand age but the differences among stands were not statistically significant ( p > 0.05) (Fig. 4 ). The annual N return in the 11-year-old stand is significantly lower than that in the 47-year-old stand. NRE exhibited a similar trend, increasing from 11 to 37 years and remaining relatively stable thereafter ( p > 0.05). NUE increased significantly from the 11-year to the 23-year stands and reached its maximum in the 37-year stand (Table S3). A similar pattern was observed for the NCC, which increased from 11 to 37 years and decreased slightly at 47 years. Soil available N stocks and annual N uptake exhibited a unimodal pattern across the stand-age gradient, with an initial increase followed by a decline (Fig. 5 ). Across all stand ages, soil available N stocks were consistently and significantly higher than the corresponding annual N uptake. Across the four stand ages, the surplus of soil available N over annual N uptake was lowest at 11 years and peaked at 37 years. As stand age further increased to 47 years, the surplus showed a gradual decline. 3.4 Nitrogen nutrition strategy indicators Among the N acquisition indices, NUpE and the proportion available nitrogen in soil were increased significantly with stand age ( p 0.05) (Fig. 6 b). For N cycling indices, accumulation of N in forest floor litter, turnover rate of forest floor litter, and the internal N cycling ratio were all increased significantly with stand age ( p < 0.05) (Fig. 6 d − f). 3.5 Multivariate controls of nitrogen cycling In the pSEM, stand age exerted a significant positive effect on plant nutrient status, which subsequently influenced litter and soil nutrient status (Fig. 7 ). N acquisition was primarily regulated by plant nutrient status. In contrast, N cycling status was driven directly by stand age and indirectly through N acquisition and litter nutrient status. Soil nutrient status had a negative effect on N cycling. Overall, the model showed a good fit to the data (Fisher’s C = 8.04, p = 0.43) (Table S4 − S5). 4. Discussion 4.1 Stand development reshapes nitrogen allocation across ecosystem components Stand development drove a systematic reorganization of N allocation among ecosystem components in larch plantations. N stock in ecosystem plant components increased steadily across stand development and peaked at 47 years, which is consistent with reported stand-age patterns in N balance for larch plantations [39]. Meanwhile, the proportional contribution of the tree layer to total plant biomass and N stocks increased continuously with stand age. This pattern indicates that the tree layer progressively became the dominant and relatively stable long-term N pool during stand development. Similar shifts have been observed in temperate and boreal coniferous forests, where forest maturation is accompanied by nutrient transfer from rapidly cycling pools to structural and storage compartments [40]. At the organ scale, stage-dependent differentiation in N accumulation was evident. Leaf tissues consistently maintained the highest N concentrations, reflecting their central role in photosynthesis and N metabolism, particularly during early development when carbon acquisition and growth are rapidly initiated [20]. Although N accumulation increased with stand age in most organs, its trajectory was not fully synchronized with structural growth, suggesting stage-dependent adjustments in resource allocation. During early development, N was preferentially allocated to functional organs to sustain rapid growth, resulting in relative N dilution in woody tissues [41]. As stands approached mid and late development, growth rates declined after structural construction had largely been completed, and greater N allocation to woody tissues and long-term storage pools was indicated [42]. This pattern is consistent with a transition from a resource-acquisitive phase to a more conservative phase in which internal recycling is strengthened. Comparable shifts have been reported in other temperate coniferous forests [43] and may be facilitated by increased litter inputs, stabilization of soil N supply, and improved N resorption and redistribution in plants [44]. Although the shrub-herb layer contributed only a small fraction of total ecosystem biomass and N stocks, its marked decline after the young stage likely reflected progressive light limitation associated with canopy closure [45]. Understory vegetation often exhibits relatively high N concentrations and rapid turnover, and may therefore function as a catalytic component of ecosystem N cycling despite its small biomass [46]. In particular, during early to middle development, understory turnover may contribute disproportionately to nutrient fluxes and productivity, and its ecological role should not be inferred solely from pool magnitude [47]. Beyond vegetation, distinct yet complementary roles were indicated for litter and soil in shaping ecosystem N dynamics. Surface litter, characterized by relatively high N concentration and rapid accumulation, formed an important transient N pool during the middle stage (23 years), likely reflecting a temporary imbalance between litter inputs and decomposition. From an ecosystem development perspective, a shift from rapid nutrient accumulation to more efficient recycling is widely regarded as a hallmark of forest maturation, and higher NUE has frequently been observed in mature stands [48]. Throughout stand development, soil remained the overwhelmingly dominant N pool (> 87% of total ecosystem N), underscoring the foundational role of soil organic matter in sustaining long-term productivity and nutrient stability in plantations [49]. 4.2 Nitrogen supply-demand balance and age-dependent nitrogen use efficiency in larch plantations Across the stand-age gradient, soil available N stocks consistently exceeded annual plant N uptake, and the supply-demand surplus was greatest at the mid-aged stage (37 years). These patterns suggest that strong N limitation was unlikely during stand development in the study area. Although plant N demand was increased with stand age, a large soil organic N pool (> 87% of total ecosystem N), together with sustained litter inputs and internal soil transformations, appeared to maintain a relatively stable N supply and to prevent persistent supply-demand imbalance [48]. This result further suggests that N limitation should not be inferred from plant biomass or total soil N alone; instead, ecosystem diagnosis is better supported when supply-demand relationships are quantified. Given the relatively limited sample size, further studies are required to verify the supply–demand dynamics across a broader stand-age gradient. Against this background, NUE and NCC exhibited unimodal patterns, with maxima at 37 years, indicating that the mid-aged stage represented the most economical phase of N utilization. At this stage, N reuse was maximized through enhanced resorption and internal cycling, thereby reducing dependence on external soil N inputs and promoting a closer coupling between growth demand and nutrient recycling [50, 51]. The co-occurrence of high utilization efficiency and sufficient N supply may explain the optimal nutrient balance observed at 37 years. In the near-mature stage (47 years), NUE was moderately reduced, potentially because growth was slowed, maintenance respiration was increased, and competition for nutrients between plants and soil microorganisms was intensified [52]. Similar age-related declines in NUE have been reported for coniferous forests (e.g., Scots pine and Norway spruce) [53], consistent with physiological aging and diminishing marginal returns of nutrient use in mature trees [54]. The NCC was increased from the young (11 years) to mid-aged (37 years) stands, indicating that an increasingly large fraction of acquired N was returned to soil via litter inputs, thereby strengthening ecosystem N retention and internal recycling. A slight decline from 37 to 47 years was observed, potentially reflecting stagnation in litter production or reduced litter quality. However, the coefficient remained relatively high, indicating that cycling efficiency was largely maintained and that the risk of nutrient loss remained low in mature stands [51]. Overall, larch plantations were characterized by an N-use pattern of adequate supply and efficient cycling, which likely explains the absence of evident N limitation in this region [41]. 4.3 Shifts in nitrogen nutrition strategies along stand development Stage-dependent changes in N fluxes and strategy indices indicated a clear shift in N utilization during stand development. NUE, NRE, and NCC all peaked at the mid-aged stage [51], suggesting that N was used most efficiently when growth demand, soil N supply, and internal recycling were likely most closely coordinated [30, 55]. At the acquisition level, NUpE showed a positive but non-significant trend with stand age, implying that intrinsic plant N acquisition capacity was not substantially altered over development. Because NUpE is jointly regulated by root morphology, mycorrhizal associations, and physiological uptake capacity [52, 56], the absence of a significant increase suggests that stronger acquisition was not required. Consistently, the proportion available nitrogen in soil increased significantly with stand age, indicating enhanced N availability during forest development [57]. This increase was likely promoted by greater litter inputs and accelerated mineralization, which would have stabilized external N supply and reduced reliance on improved uptake efficiency. The slight decline in the N enrichment in topsoil may have been driven by deeper rooting and sustained nutrient uptake, although this effect was not sufficiently strong to yield significant differences [58, 59]. In contrast, N cycling strategies were adjusted more strongly than acquisition traits. With increasing stand age, both forest floor N accumulation and litter turnover rate increased significantly, indicating an intensification of litter-mediated recycling. In mid-aged and mature stands, faster litter decomposition may promote more rapid N release and re-entry into plant uptake pathways, thereby tightening internal cycling [48]. Such litter-driven enhancement of N cycling is considered a key indicator of ecosystem maturation and reflects improved self-maintenance and nutrient retention capacity [60]. Overall, larch plantations exhibited a progressive shift from acquisition-dominated to recycling-dominated N strategies, highlighting an age-driven reorganization of N cycling pathways. 4.4 Multivariate pathways regulating nitrogen cycling revealed by piecewise structural equation modeling The pSEM elucidated the multiple pathways through which stand age regulates N cycling. Stand age was identified as the primary integrative driver, with both direct effects and indirect effects mediated through biomass accumulation, internal N storage, litter inputs, and soil development. Along the N acquisition pathway, plant nutrient status exerted a stronger positive effect on N uptake than stand age, indicating that acquisition was mainly demand-driven rather than directly constrained by developmental stage[61]. Accordingly, expansion of the vegetation N pool during stand development appeared to be supported primarily by demand-mediated increases in uptake and internal retention, rather than by age alone. Notably, greater N uptake was not necessarily associated with faster ecosystem N turnover, suggesting that enhanced acquisition does not inevitably accelerate cycling rates [62, 63]. Along the N cycling pathway, a significant positive direct effect of stand age was detected and was further strengthened by litter nutrient status. With stand maturation, biomass accumulation, enhanced uptake capacity, and stronger internal retention were jointly promoted, thereby facilitating vegetation N pool expansion [64]. Although the litter-to-soil N pathway was not statistically significant, the positive direction suggested that litter inputs may still act as an important mediator of soil N accumulation, potentially via decomposition and N release processes [65, 66]. Conversely, a negative effect of soil nutrient status on N cycling was observed, which may reflect a transient reduction in readily available soil N under intensified plant uptake, followed by compensation through litter return and decomposition [48]. This pattern may reflect temporary depletion of available soil N under increased plant uptake. Overall, the pSEM results offered a mechanistic synthesis that was consistent with the observed patterns of N allocation, supply-demand balance, and nutritional strategy shifts. A stage-dependent transition from acquisition-dominated to internally regulated N cycling was indicated for larch plantations, implying reduced sensitivity of mature stands to external N inputs and short-term disturbances. The satisfactory model fit further supported the ecological plausibility of the hypothesized stand age-plant-litter-soil pathways and provided insight into nutrient dynamics and potential constraints across developmental stages. 5. Conclusions Across a 11–47-year chronosequence of larch plantations, stand development increased vegetation biomass and N stocks, while soil remained the dominant ecosystem N pool (> 87%). The soil alkali-hydrolysable N pool consistently exceeded annual plant N uptake, indicating no evidence of acute N shortage based on available N pools. Stand development was associated with a strategic shift from soil-acquisition dependence in young stands toward recycling-centered N use in older stands, with NUE peaking at the mid-aged stage. The pSEM further suggested that N acquisition was mainly linked to plant nutrient status, whereas N cycling was driven by stand age and reinforced by litter nutrient status. Management of mature larch plantations should therefore prioritize maintaining litter-mediated internal cycling (e.g., conserving the forest floor and avoiding practices that disrupt litter decomposition) rather than relying primarily on external N inputs. Abbreviation RNE annual nitrogen resorption NUE nitrogen use efficiency NCC nitrogen cycling coefficient NUpE nitrogen uptake efficiency SANP proportion available nitrogen in soil FFNA accumulation of nitrogen in forest floor LTR turnover rate of forest floor litter INC internal nitrogen cycling Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Research involving plants All experimental research and field studies on plants conducted in this work adhere to Chinese institutional, national, and international guidelines and legislation. Funding This work was supported by the State Key Research and Development Program (2023YFD2200803), and Major Science and Technology Support Program of Hebei Province (252L6802D, 252L6801D). Author contributions X.C., writing—original draft, visualization, methodology, investigation, and data curation; Z.G., writing—review and editing, conceptualization, and visualization; Q.L., performed investigation and data curation; Y.P., investigation and conceptualization; Z.Z., writing—review and editing, project administration, funding acquisition, and validation. All authors have read and agreed to the published version of the manuscript. Data availability The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Acknowledgements We are deeply grateful to the editor and reviewers for their comments and suggestions on the manuscript. All authors would like to thank all the staff of Saihanba Forest Farm for their support to the research work. Clinical trial number Not applicable. References Rennenberg H, Schmidt S: Perennial lifestyle-an adaptation to nutrient limitation? Tree Physiol 2010, 30 (9):1047-1049. LeBauer DS, Treseder KK: Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed . Ecology 2008, 89 (2):371-379. Hu YF, Shu XY, He J, Zhang YL, Xiao HH, Tang XY, Gu YF, Lan T, Xia JG, Ling J et al : Storage of C, N, and P affected by afforestation with Salix cupularis in an alpine semiarid desert ecosystem . Land Degrad Dev 2018, 29 (1):188-198. Hjelm K, Romans E, Högbom L, Ring E: Tree growth and ground vegetation 17 years after disc trenching and preharvest nitrogen fertilization . For Ecol Manag 2025, 597 :123145. Zhang P, Lü XT, Li MH, Wu TG, Jin GZ: N limitation increases along a temperate forest succession: evidences from leaf stoichiometry and nutrient resorption . J Plant Ecol 2022b, 15 (5):1021-1035. Du EZ, Terrer C, Pellegrini AFA, Ahlström A, van Lissa CJ, Zhao X, Xia N, Wu XH, Jackson RB: Global patterns of terrestrial nitrogen and phosphorus limitation . Nat Geosci 2020, 13 (3):221-226. Ziegler SE, Billings SA, Podrebarac FA, Edwards KA, Skinner A, Buckeridge KM, Vandenboer TC: Biogeochemical evidence raises questions on the longevity of warming-induced growth enhancements in wet boreal forests . Ecosphere 2024, 15 (12):e70109. Li YB, Zhu Q, Zhang Y, Liu S, Wang XT, Wang EH: Impact of winter cover crops on total and microbial carbon and nitrogen in black soil . Agronomy-Basel 2024, 14 (3):603. Mao L, He XX, Ye SM, Wang SQ: Soil aggregate-associated carbon-cycle and nitrogen-cycle enzyme activities as affected by stand age in Chinese fir plantations . J Soil Sci Plant Nutr 2023, 23 (3):4361-4372. Jha KK: Temporal patterns of storage and flux of N and P in young Teak plantations of tropical moist deciduous forest, India . J For Res 2014, 25 (1):75-86. Ranger J, Allie S, Gelhaye D, Pollier B, Turpault MP, Granier A: Nutrient budgets for a rotation of a Douglas-fir plantation in the Beaujolais (France) based on a chronosequence study . For Ecol Manag 2002, 171 (1-2):3-16. Zhou LL, Shalom ADD, Wu PF, He ZM, Liu CH, Ma XQ: Biomass production, nutrient cycling and distribution in age-sequence Chinese fir ( Cunninghamia lanceolate ) plantations in subtropical China . J For Res 2016, 27 (2):357-368. Zhou LL, Li SB, Jia YY, Heal K, He ZM, Wu PF, Ma XQ: Spatiotemporal distribution of canopy litter and nutrient resorption in a chronosequence of different development stages of Cunninghamia lanceolata in Southeast China . Sci Total Environ 2021, 762 :143153. Reich PB, Hobbie SE, Lee T, Ellsworth DS, West JB, Tilman D, Knops JMH, Naeem S, Trost J: Nitrogen limitation constrains sustainability of ecosystem response to CO 2 . Nature 2006, 440 (7086):922-925. Perchlik M, Tegeder M: Leaf amino acid supply affects photosynthetic and plant nitrogen use efficiency under nitrogen stress . Plant Physiol 2018, 178 (1):174-188. Wu HL, Xiang WH, Ouyang S, Xiao WF, Li SG, Chen L, Lei PF, Deng XW, Zeng YL, Zeng LX et al : Tree growth rate and soil nutrient status determine the shift in nutrient-use strategy of Chinese fir plantations along a chronosequence . For Ecol Manag 2020, 460 :117896. Feng HL, Guo JH, Peng CH, Kneeshaw D, Roberge G, Pan C, Ma XH, Zhou D, Wang WF: Nitrogen addition promotes terrestrial plants to allocate more biomass to aboveground organs: a global meta-analysis . Global Change Biol 2023, 29 (14):3970-3989. Killingbeck KT: Nutrients in senesced leaves: keys to the search for potential resorption and resorption proficiency . Ecology 1996, 77 (6):1716-1727. Zhang X, Li BY, Penuelas J, Sardans J, Cheng DL, Yu H, Zhong QL: Resource-acquisitive species have greater plasticity in leaf functional traits than resource-conservative species in response to nitrogen addition in subtropical China . Sci Total Environ 2023, 903 :166177. Yan T, Fang YT, Wang JS, Song HH, Zhong TY, Wang PL: Effects of long-term nitrogen addition on the shift of nitrogen cycle from open to closed along an age gradient of larch plantations in North China . Soil Biol Biochem 2024, 191 :109295. Asaadi A, Arora VK: Implementation of nitrogen cycle in the CLASSIC land model . Biogeosciences 2021, 18 (2):669-706. Nie YX, Han XG, Chen J, Wang MC, Shen WJ: The simulated N deposition accelerates net N mineralization and nitrification in a tropical forest soil . Biogeosciences 2019, 16 (21):4277-4291. Chen XL, Taylor AR, Reich PB, Hisano M, Chen HYH, Chang SX: Tree diversity increases decadal forest soil carbon and nitrogen accrual . Nature 2023, 618 (7963):94-101. Costa AD, Torres FTP, Lima GS, de Melo FR, Torres C, Schettini BLS, Neto VPS, de Faria ALL: Influence of fire on woody vegetation of savanna and forest formations in the Cerrado biome . J For Res 2023, 34 (5):1207-1216. Qiu XC, Wang HB, Peng DL, Liu X, Yang F, Li Z, Cheng S: Thinning drives C:N:P stoichiometry and nutrient resorption in Larix principis-rupprechtii plantations in North China . For Ecol Manag 2020, 462 . Zhang JF, Li MH, Liu Q, Pang Y, Zhang ZD: Ecosystem service synergies and trade-offs in poplar-birch mixed natural forests across different developmental stages . Forests 2025, 16 (5):867. Jin J, Wang HR, Zhang ZD, Gao Y, Liu Q, Fu LH, Chen DS, Dong LH, Xie HT, Lu DL: Optimizing understory afforestation of shade-tolerant conifer Picea asperata across canopy transmittance gradients . Eur J For Res 2026, 145 (2):29. Ge ZX, Peng B, Chen XT, Zhang JF, Wang ZY, Pang Y, Zhang ZD: Plant functional traits and soil properties shape soil microbial communities in Larix principis-rupprechtii mixed plantations . Biology 2026, 15 (3):259. Wu HL, Chen L, Ouyang S, Zhou WN, Wu MG, Zeng LX, Lei PF, Zeng YL, Deng XW, Li SG et al : Phosphorus cycling and supply-demand balance across a chronosequence of Chinese fir plantations . Catena 2023, 228 :107117. Zhou GY, Yin GC, Tang Xl, Wen DZ, Liu CP, Kuang YD, Wang WT: Carbon stocks in Chinese forest ecosystems: the biomass equation . Beijing: Science Press; 2018. Schimel JP, Bennett J: Nitrogen mineralization: challenges of a changing paradigm . Ecology 2004, 85 (3):591-602. Fang YT, Gundersen P, Mo JM, Zhu WX: Input and output of dissolved organic and inorganic nitrogen in subtropical forests of South China under high air pollution . Biogeosciences 2008, 5 (2):339-352. Liu GC, Yin ZW, Yan GY, Liu S, Wang XC, Xing YJ, Wang QG: Effects of long-term nitrogen addition on the δ 15 N and δ 13 C of Larix gmelinii and soil in a boreal forest . Ecological Processes 2022, 11 (1):37. Yuan ZY, Chen HYH: Global-scale patterns of nutrient resorption associated with latitude, temperature and precipitation . Global Ecol Biogeogr 2009, 18 (1):11-18. Vergutz L, Manzoni S, Porporato A, Novais RF, Jackson RB: Global resorption efficiencies and concentrations of carbon and nutrients in leaves of terrestrial plants . Ecol Monogr 2012, 82 (2):205-220. Hirel B, Le Gouis J, Ney B, Gallais A: The challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches . J Exp Bot 2007, 58 (9):2369-2387. Lang F, Krüger J, Amelung W, Willbold S, Frossard E, Bünemann EK, Bauhus J, Nitschke R, Kandeler E, Marhan S et al : Soil phosphorus supply controls P nutrition strategies of beech forest ecosystems in Central Europe . Biogeochemistry 2017, 136 (1):5-29. R Core Team: R: A language and environment for statistical computing . In . , 4.3.3 edn. Vienna: R Foundation for Statistical Computing; 2024. Frisman EY, Zhdanova OL, Kulakov MP, Neverova GP, Revutskaya OL: Mathematical modeling of population dynamics based on recurrent equations: results and prospects, part I . Biol Bull 2021, 48 (1):1-15. Luyssaert S, Schulze ED, Börner A, Knohl A, Hessenmöller D, Law BE, Ciais P, Grace J: Old-growth forests as global carbon sinks . Nature 2008, 455 (7210):213-215. Liu WL, Zu JX, Liu B, Qi L, Huang W, Fang YT, Yang J: Wildfire effects on the fate of deposited nitrogen in a boreal larch forest . Biogeochemistry 2024, 167 (5):681-693. Millard P, Grelet GA: Nitrogen storage and remobilization by trees: ecophysiological relevance in a changing world . Tree Physiol 2010, 30 (9):1083-1095. Bertiller MB, Sain CL, Carrera AL, Vargas DN: Patterns of nitrogen and phosphorus conservation in dominant perennial grasses and shrubs across an aridity gradient in Patagonia, Argentina . J Arid Environ 2005, 62 (2):209-223. Van Langenhove L, Depaepe T, Vicca S, van den Berge J, Stahl C, Courtois E, Weedon J, Urhina I, Grau O, Asensio D et al : Regulation of nitrogen fixation from free-living organisms in soil and leaf litter of two tropical forests of the Guiana shield . Plant Soil 2020, 450 (1-2):93-110. Barbier S, Gosselin F, Balandier P: Influence of tree species on understory vegetation diversity and mechanisms involved-a critical review for temperate and boreal forests . For Ecol Manag 2008, 254 (1):1-15. Grogan P, Jonasson S: Controls on annual nitrogen cycling in the understory of a subarctic birch forest . Ecology 2003, 84 (1):202-218. Cui ER, Xia JY, Luo YQ: Nitrogen use strategy drives interspecific differences in plant photosynthetic CO 2 acclimation . Global Change Biol 2023, 29 (13):3667-3677. Xia Q, Chen L, Xiang WH, Ouyang S, Wu HL, Lei PF, Xiao WF, Li SG, Zeng LX, Kuzyakov Y: Increase of soil nitrogen availability and recycling with stand age of Chinese-fir plantations . For Ecol Manag 2021, 480 :118643. Fang HJ, Yu GR, Cheng SL, Zhu TH, Zheng JJ, Mo JM, Yan JH, Luo YQ: Nitrogen-15 signals of leaf-litter-soil continuum as a possible indicator of ecosystem nitrogen saturation by forest succession and N loads . Biogeochemistry 2011, 102 (1-3):251-263. Zhu LQ, Sun J, Yao XD, Wang XH, Huang JX, Xiong DC, Chen GS: Fine root nutrient foraging ability in relation to carbon availability along a chronosequence of Chinese fir plantations . For Ecol Manag 2022, 507 :120003. Zhang H, Sun M, Wen YX, Tong R, Wang G, Wu QQ, Li Y, Wu TG: The effects of stand age on leaf N:P cannot be neglected: a global synthesis . For Ecol Manag 2022a, 518 :120294. Gessler A, Schaub M, McDowell NG: The role of nutrients in drought-induced tree mortality and recovery . New Phytol 2017, 214 (2):513-520. Mäkinen H, Ilvesniemi H, Lindroos AJ, Smolander A: Effects of wood ash, nitrogen, and biosolids fertilisation on the growth and soil properties of Scots pine and Norway spruce stands . For Ecol Manag 2025, 578 :122467. Tang JW, Luyssaert S, Richardson AD, Kutsch W, Janssens IA: Steeper declines in forest photosynthesis than respiration explain age-driven decreases in forest growth . Proc Natl Acad Sci USA 2014, 111 (24):8856-8860. Leduc SD, Rothstein DE: Plant-available organic and mineral nitrogen shift in dominance with forest stand age . Ecology 2010, 91 (3):708-720. Read DJ, Perez-Moreno J: Mycorrhizas and nutrient cycling in ecosystems: A journey towards relevance? New Phytol 2003, 157 (3):475-492. Zhang Y, Tigabu M, Yi ZG, Li HT, Zhuang Z, Yang Z, Ma XQ: Soil parent material and stand development stage effects on labile soil C and N pools in Chinese fir plantations . Geoderma 2019, 338 :247-258. McCulley RL, Jobbágy EG, Pockman WT, Jackson RB: Nutrient uptake as a contributing explanation for deep rooting in arid and semi-arid ecosystems . Oecologia 2004, 141 (4):620-628. Peng S, Zhang YK, Chen HYH: Plant functional trait dissimilarity drives plant mixture effects on fine root biomass and trait variations . New Phytol 2026, 249 (2):764-776. Wardle DA, Bardgett RD, Klironomos JN, Setälä H, Putten WHvd, Wall DH: Ecological linkages between aboveground and belowground biota . Science 2004, 304 (5677):1629-1633. Zhu XM, Lambers H, Guo WJ, Chen DD, Liu ZF, Zhang ZL, Yin HJ: Extraradical hyphae exhibit more plastic nutrient-acquisition strategies than roots under nitrogen enrichment in ectomycorrhiza-dominated forests . Global Change Biol 2023, 29 (16):4605-4619. Hewitt RE, Alexander HD, Miller SN, Mack MC: Root-associated fungi not tree density influences stand nitrogen dynamics at the larch forest-tundra ecotone . J Ecol 2022, 110 (6):1419-1431. Henriksson N, Lim H, Marshall J, Franklin O, McMurtrie RE, Lutter R, Magh R, Lundmark T, Näsholm T: Tree water uptake enhances nitrogen acquisition in a fertilized boreal forest - but not under nitrogen-poor conditions . New Phytol 2021, 232 (1):113-122. Johnson DW, Turner J: Nutrient cycling in forests: a historical look and newer developments . For Ecol Manag 2019, 444 :344-373. Zheng P, Zhao RA, Jiang LC, Yang GJ, Wang YL, Wang RZ, Han XG, Ning QS: Increasing nitrogen addition rates suppressed long-term litter decomposition in a temperate meadow steppe . J Plant Ecol 2023, 16 (3):rtac078. Gao JB, Zhou WJ, Liu YT, Sha LQ, Song QH, Lin YX, Yu GR, Zhang JH, Zheng XH, Fang YT et al : Litter-derived nitrogen reduces methane uptake in tropical rainforest soils . Sci Total Environ 2022, 849 :157891. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials..docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 14 May, 2026 Reviews received at journal 13 May, 2026 Reviews received at journal 12 May, 2026 Reviews received at journal 07 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviewers agreed at journal 01 May, 2026 Reviewers agreed at journal 30 Apr, 2026 Reviewers invited by journal 29 Apr, 2026 Editor invited by journal 26 Mar, 2026 Editor assigned by journal 26 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 25 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9084654","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":636340481,"identity":"c222f8c4-e6bc-495c-b597-b38c69f08cfd","order_by":0,"name":"Xiaotong Chen","email":"","orcid":"","institution":"Hebei Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xiaotong","middleName":"","lastName":"Chen","suffix":""},{"id":636340482,"identity":"1430fb54-e317-4d7d-a27c-804db60ddbd8","order_by":1,"name":"Zhaoxuan Ge","email":"","orcid":"","institution":"Hebei Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Zhaoxuan","middleName":"","lastName":"Ge","suffix":""},{"id":636340483,"identity":"e29fb6a3-8992-4d6a-84fe-549a932ea1b1","order_by":2,"name":"Yue Pang","email":"","orcid":"","institution":"Hebei Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Pang","suffix":""},{"id":636340484,"identity":"b915f6b3-7ce3-4267-ab69-3c89ec3c1621","order_by":3,"name":"Qiang Liu","email":"","orcid":"","institution":"Hebei Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Qiang","middleName":"","lastName":"Liu","suffix":""},{"id":636340485,"identity":"3a9165eb-7b7a-4d34-9b6a-d463fe07b88a","order_by":4,"name":"Zhidong Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYDACCTDJLGfAwANmMTYQq8WYdC2JG4jWIj+7+dnDL3+s07ez9x78zMNgI7vhAPOzB/i0MM45Zm4sw5Oeu7PnXLI0D0Oa8YYDbOYG+LQwSySYSUtIHM7dcCPHAKjlcOKGAzxsEvi0sEmkf5OWMDicbnD/jfFvHob/hLXwSOSYSX5IOJxgcIPHDGjLAcJaJCRyyqQZDqQbbjiTl2Y5xyDZeOZhNjO8WuRnpG+T/PHHWt7g+NnDN95U2Mn2HW9+hlcLCDDzwJmgoGImpB4IGH8QoWgUjIJRMApGMAAAdAxFPucX2+8AAAAASUVORK5CYII=","orcid":"","institution":"Hebei Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Zhidong","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2026-03-10 13:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9084654/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9084654/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108975959,"identity":"564c6f4e-fbe8-4878-bb3e-6f20261a18d4","added_by":"auto","created_at":"2026-05-11 10:58:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":361464,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the sample plots.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9084654/v1/b0c2b380e1ac1d4d92b65b16.png"},{"id":108801776,"identity":"bead3338-5cba-4fa4-beff-c2a04bcabd4b","added_by":"auto","created_at":"2026-05-08 14:20:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":84850,"visible":true,"origin":"","legend":"\u003cp\u003eBiomass (t·ha\u003csup\u003e−\u003c/sup\u003e¹) and N stocks (t·ha\u003csup\u003e−\u003c/sup\u003e¹) of vegetation components in \u003cem\u003eL. principis-rupprechtii \u003c/em\u003eplantations across stand ages.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9084654/v1/f91b41de6cca3d8316c26db4.png"},{"id":108801775,"identity":"8d8078f4-6de6-4a67-ad21-3c0f69691130","added_by":"auto","created_at":"2026-05-08 14:20:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":251707,"visible":true,"origin":"","legend":"\u003cp\u003eBiomass (t·ha\u003csup\u003e−\u003c/sup\u003e¹) and N stocks (t·ha\u003csup\u003e−\u003c/sup\u003e¹) of different organs in the tree, shrub, and herb layers of \u003cem\u003eL. principis-rupprechtii \u003c/em\u003eplantations across stand ages.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e A: stand age; O: organ; A × O: interaction. *\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.001; ns, not significant. Differences in stand age (A), organ (O), and their interaction (A × O) were analyzed using two-way ANOVA followed by Tukey’s HSD test.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9084654/v1/203b6b4b39037fb9bd98f05f.png"},{"id":108801778,"identity":"992874a9-49e7-4436-b0f8-7d6687ba8ea8","added_by":"auto","created_at":"2026-05-08 14:20:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":363775,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in annual N uptake (t·ha\u003csup\u003e−\u003c/sup\u003e¹), annual N retention (t·ha\u003csup\u003e−\u003c/sup\u003e¹), annual N return (t·ha\u003csup\u003e−\u003c/sup\u003e¹), and annual N resorption (t·ha\u003csup\u003e−\u003c/sup\u003e¹) across stand ages in \u003cem\u003eL. principis-rupprechtii \u003c/em\u003eplantations. The bar charts represent the mean values for each stand age.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9084654/v1/fc46351bc804c9175fb1ec0a.png"},{"id":108801779,"identity":"81b33bf4-ed3d-48d6-9c37-bfe25b5454de","added_by":"auto","created_at":"2026-05-08 14:20:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":84965,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between soil alkali-hydrolysable N stocks and annual N uptake across stand ages in \u003cem\u003eL. principis-rupprechtii \u003c/em\u003eplantations.***\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9084654/v1/f43714879ecfc2689235efbd.png"},{"id":108801780,"identity":"7faa3f71-1bd0-4864-8144-5a66e33e75dd","added_by":"auto","created_at":"2026-05-08 14:20:40","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":156861,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between stand age and N nutritional strategy indices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e: Solid lines represent linear regressions, and shaded areas indicate the 95% confidence intervals. Significant correlations (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) indicate age-related changes in soil N availability and litter-mediated N cycling, whereas non-significant trends suggest that plant N uptake efficiency and internal N cycling remained relatively stable along the stand age gradient.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9084654/v1/acd1dcc862492b54df2a88bc.png"},{"id":108975957,"identity":"87f86a53-87fe-4f5d-ab9f-bd5d92b16012","added_by":"auto","created_at":"2026-05-11 10:58:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":64106,"visible":true,"origin":"","legend":"\u003cp\u003ePiecewise structural equation model (pSEM) illustrating the pathways through which stand age regulates N cycling in \u003cem\u003eL. principis-rupprechtii \u003c/em\u003eplantations, as well as the direct and indirect effects of different factors on N cycling. Solid arrows indicate significant ecological pathways, whereas dashed arrows represent supplementary or non-dominant relationships (i.e., non-significant ecological pathways). Numbers adjacent to the arrows represent standardized path coefficients. Gray and blue arrows indicate positive and negative effects, respectively. Bar plots show the total standardized effects. The definitions of the composite variables in the figure are consistent with those described in Statistical analysis.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-9084654/v1/654f6ad04d9540272b7cb79b.png"},{"id":108978863,"identity":"27147e15-b39d-4395-ba0b-c73275c4366b","added_by":"auto","created_at":"2026-05-11 11:49:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1654586,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9084654/v1/5fa3df51-351f-495c-bcee-6249999b5892.pdf"},{"id":108975960,"identity":"9ce2e28b-6f68-4382-9d73-a32ff1b19442","added_by":"auto","created_at":"2026-05-11 10:58:32","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":34448,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials..docx","url":"https://assets-eu.researchsquare.com/files/rs-9084654/v1/d355701b92c2e96c46b32125.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Stand development shifts nitrogen cycling strategies and supply-demand balance in larch plantations","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNitrogen (N) is a fundamental element regulating plant growth and ecosystem primary productivity. As a key component of proteins, nucleic acids, and chlorophyll, N directly supports essential physiological processes such as photosynthesis and respiration [1\u0026ndash;3]. However, the availability of bioavailable N in soils often fails to match plant demand, making N one of the most pervasive constraints on ecosystem productivity. Numerous studies have shown that N limitation is widespread across forest ecosystems globally, with particularly strong effects in boreal and temperate forests where limited N supply can markedly restrict biomass accumulation and carbon sequestration [2, 4]. During stand development, growth rates, biomass allocation, and soil nutrient status are continuously altered, and stage-dependent variations in the intensity and ecological consequences of N limitation are therefore expected [5].\u003c/p\u003e \u003cp\u003eAt the ecosystem scale, N limitation is not determined solely by the magnitude of soil N pool, but instead depends on the balance between soil N supply and plant N demand (i.e., the N supply-demand balance) [6]. This balance has been regarded as a core indicator for diagnosing N limitation in forest ecosystems [7]. When supply and demand are mismatched, tree growth may be reduced, litter decomposition may be constrained, and soil acidification may be intensified. Because most soil N occurs in organic forms that are not directly available to plants, total soil N storage alone cannot adequately reflect actual N availability. In contrast, available N pools (e.g., alkali-hydrolysable N) have been considered to better approximate the effective N supply available to plants [8]. Consistent with this view, pronounced adjustments in soil N supply capacity and its coordination with plant demand have been reported across stand developmental stages [9].\u003c/p\u003e \u003cp\u003eFrom a process-based perspective, the ecosystem N supply-demand balance is jointly regulated by coupled fluxes, including plant N uptake, internal retention, litter return to soil, and N resorption prior to senescence [10\u0026ndash;13]. Plant N demand is influenced not only by growth rate, but also by N use efficiency (NUE) and the capacity for internal N recycling [14\u0026ndash;16]. When soil available N becomes limiting or stands approach maturity, higher N resorption efficiency is often induced, internal N recycling is strengthened, and biomass allocation is adjusted, thereby reducing reliance on external N inputs [17, 18]. Consequently, stand development is typically accompanied by a shift from a resource-acquisitive strategy toward a resource-conservative strategy [19]. In parallel, N cycling is often transitioned from a relatively open system to a more closed system that increasingly depends on litter-microbe-mediated internal recycling to maintain nutrient balance[20].\u003c/p\u003e \u003cp\u003eN cycling is inherently a complex, multi-component system involving vegetation, litter, and soil, which are tightly coupled through both direct and indirect pathways [21]. During stand development, N distribution and cycling among ecosystem components may be reorganized through changes in vegetation biomass accumulation, litter inputs, and soil nutrient turnover, rather than through changes in total N storage alone [22]. Therefore, the multi-path mechanisms by which stand age regulates N cycling need to be resolved to advance a mechanistic understanding of forest nutrient dynamics. Piecewise structural equation modeling (pSEM) provides a powerful framework for disentangling such multivariate pathways by partitioning direct effects of stand age from indirect effects mediated by vegetation, litter, and soil properties [23].\u003c/p\u003e \u003cp\u003eLarch \u003cem\u003e(Larix principis\u003c/em\u003e-\u003cem\u003erupprechtii\u003c/em\u003e), a dominant afforestation species in cold-temperate regions of northern China, is characterized by rapid growth and strong environmental adaptability, and is widely recognized for its contributions to timber production and ecosystem functioning [24]. However, productivity decline and site degradation have been frequently reported in near-mature and mature larch plantations. These declines have been closely linked to shifts in nutrient availability, particularly changes in N supply-demand relationships [5]. To date, research has largely emphasized soil C:N ratios or individual N pool characteristics, whereas integrated quantification of ecosystem N supply-demand balance and its regulatory mechanisms across stand development remains limited [13, 20]. This gap has constrained a comprehensive understanding of N cycling dynamics in these plantations.\u003c/p\u003e \u003cp\u003eAgainst this background, larch plantations with four stand ages (11, 23, 37, and 47 years) were investigated. Biomass and N stocks in vegetation, litter, and soil were quantified; ecosystem-scale N fluxes (uptake, retention, litter return, and resorption) were estimated; and indices describing N acquisition and cycling strategies were calculated. In addition, pSEM was applied to clarify the multiple pathways by which stand age affects ecosystem N cycling. Specifically, this study aimed to: (1) characterize variations in N cycling fluxes and N nutritional strategies across stand ages; (2) evaluate ecosystem-scale N supply-demand status during stand development; and (3) identify key processes underlying the stand age-driven transition from external N acquisition to internally regulated N cycling.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area and plot establishment\u003c/h2\u003e \u003cp\u003eThe study area is located in the Saihanba Forest Center, Hebei Province, China (42\u0026deg;02\u0026prime;\u0026minus;42\u0026deg;36\u0026prime; N, 116\u0026deg;51\u0026prime;\u0026minus;117\u0026deg;39\u0026prime; E)[25], at elevations of 750\u0026thinsp;\u0026minus;\u0026thinsp;1998 m. The region is typified by a semi-arid to semi-humid, cold-temperate continental monsoon climate. The mean annual temperature is -1.3\u0026deg;C, with extreme temperatures ranging from \u0026minus;\u0026thinsp;43.2 to 33.4\u0026deg;C. The mean annual precipitation is approximately 460 mm, of which 65.8% occurred during the growing season (June\u0026minus;August). The average frost-free period is approximately 64 days per year [26].\u003c/p\u003e \u003cp\u003eExtensive overgrazing during the early twentieth century resulted in severe degradation of natural forests in this region. In response, large-scale afforestation programs were launched in 1962 using larch and other cold- and drought-tolerant species (e.g., spruce). Larch plantations were initially established at a density of approximately 5,000 trees ha\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1; [27]. Since 1983, forest management has shifted from afforestation to stand tending and structural regulation [28]. To date, five large-scale thinning interventions have been implemented, which have reduced the stand density of mature forests to about 600\u0026thinsp;\u0026minus;\u0026thinsp;900 trees\u0026middot;ha\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;. Currently, larch plantations cover approximately 38,000 ha in the study region, with a total standing volume of 6.59\u0026nbsp;million m\u0026sup3;.\u003c/p\u003e \u003cp\u003eVegetation in the study area comprises coniferous and broadleaved forests, shrublands, and meadow ecosystems. The main plantation species include \u003cem\u003eLarix principis-rupprechtii\u003c/em\u003e, \u003cem\u003ePinus sylvestris\u003c/em\u003e var. \u003cem\u003emongolica\u003c/em\u003e, and \u003cem\u003eBetula platyphylla\u003c/em\u003e. The shrub layer is dominated by \u003cem\u003eRhododendron mucronulatum\u003c/em\u003e, \u003cem\u003eSpiraea salicifolia\u003c/em\u003e, and \u003cem\u003eRosa davurica\u003c/em\u003e, while the herb layer is characterized by \u003cem\u003eTrollius chinensis\u003c/em\u003e, \u003cem\u003eTaraxacum mongolicum\u003c/em\u003e and \u003cem\u003ePicris hieracioides\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eIn June 2023, larch plantations with four stand-age stages (11, 23, 37, and 47 years) were selected. To reduce potential bias associated with the chronosequence design, plots were established under similar topographic conditions, soil types, and management histories. Three replicate plots (30 m \u0026times; 30 m) were established for each stand age (n\u0026thinsp;=\u0026thinsp;12). Adjacent plots were separated by \u0026gt;\u0026thinsp;100 m [29] (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A complete tree inventory was conducted in each plot (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic information of the larch plots with different stand ages\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003cp\u003e(year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElevation\u003c/p\u003e \u003cp\u003e(m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of plots\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAspect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSlope\u003c/p\u003e \u003cp\u003e(\u0026deg;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDBH\u003c/p\u003e \u003cp\u003e(cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAverage height (m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStand density (tree\u0026middot;ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e1606\u0026thinsp;\u0026minus;\u0026thinsp;1616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e7.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e7.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e2006\u0026thinsp;\u0026plusmn;\u0026thinsp;59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e1624\u0026thinsp;\u0026minus;\u0026thinsp;1635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e15.22\u0026thinsp;\u0026plusmn;\u0026thinsp;2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e14.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e1511\u0026thinsp;\u0026plusmn;\u0026thinsp;169\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e1639\u0026thinsp;\u0026minus;\u0026thinsp;1652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u0026thinsp;\u0026minus;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e23.22\u0026thinsp;\u0026plusmn;\u0026thinsp;4.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e20.56\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e903\u0026thinsp;\u0026plusmn;\u0026thinsp;73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e1664\u0026thinsp;\u0026minus;\u0026thinsp;1672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e24.06\u0026thinsp;\u0026plusmn;\u0026thinsp;4.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e21.63\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e737\u0026thinsp;\u0026plusmn;\u0026thinsp;23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll plant materials used in this study were obtained from larch (\u003cem\u003eLarix principis-rupprechtii\u003c/em\u003e) plantations located in Saihanba Mechanical Forest Farm, Hebei Province, China. The stands were established using locally sourced seeds, with local seed collection, seedling cultivation, and outplanting, and were naturally regenerated through seed dispersal. All tree, shrub, and herb species recorded in the study plots are native to the region and were not associated with any introduced or invasive species.\u003c/p\u003e \u003cp\u003e Sample collection was conducted with permission from the Saihanba Mechanical Forest Farm administration. Field sampling complied with relevant institutional, national, and international guidelines, as well as local legislation. The studied species is not listed as a protected species under Chinese regulations. Species identification was carried out by a qualified forestry expert from Saihanba Mechanical Forest Farm based on morphological characteristics and standard taxonomic references. Representative samples were documented photographically during field sampling. No voucher specimens were deposited, as the study focused on ecological processes in managed plantation stands rather than taxonomic verification.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Sample collection and laboratory analysis\u003c/h2\u003e \u003cp\u003eIn each tree layer plot, three shrub quadrats (3 m \u0026times; 3 m) were randomly established along the plot diagonal. In each shrub quadrat, one 1 m \u0026times; 1 m herb plot was further randomly selected. To quantify tree growth, 10 healthy trees were randomly selected in each plot, and dendrometer bands were installed at breast height (1.3m) to monitor radial growth from July 2023 to July 2024. Measurements were conducted monthly during the growing season (late April to early September) and at three-month intervals during the non-growing season. In addition, three healthy trees with mean DBH and height were selected per plot as sample trees. Approximately 200 g of tissue samples from stem, branch, leaf, and coarse root were collected from each sample tree. Fine roots were sampled from the sampled soil layer around each sample tree using a soil auger (10 cm diameter).\u003c/p\u003e \u003cp\u003eLitterfall was collected at three evenly distributed points within each plot. At each point, a litter trap (0.75 m \u0026times; 0.75 m; 0.5625 m\u0026sup2;) was installed using nylon mesh supported by a PVC frame and suspended 0.75 m above the ground. Litterfall was collected periodically in October and December 2023 and May 2024. In addition, a 20 cm \u0026times; 20 cm forest floor quadrat was established adjacent to each trap to collect accumulated surface litter. All litter samples were sorted, oven-dried, and analyzed for N concentration.\u003c/p\u003e \u003cp\u003eSoil was sampled adjacent to each litter collection point. After removing surface litter, soil cores were obtained at 0\u0026thinsp;\u0026minus;\u0026thinsp;10, 10\u0026thinsp;\u0026minus;\u0026thinsp;20, and 20\u0026thinsp;\u0026minus;\u0026thinsp;30 cm using a cutting-ring corer (100 cm\u003csup\u003e3\u003c/sup\u003e) to determine bulk density. Additional soil samples (approximately 500 g) from the same depth intervals were collected using a 10 cm diameter auger for physicochemical analyses. Moreover, organic-layer samples (0\u0026thinsp;\u0026minus;\u0026thinsp;1 cm) were collected to determine organic matter. For each plot, soils from the same depth were composited, air-dried, sieved, and cleared of roots and stones prior to the determination of total N and alkali-hydrolysable N.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Estimation of nitrogen stocks\u003c/h2\u003e \u003cp\u003eBiomass of different tree organs (stem, branches, leaves, and coarse roots) was estimated using species-specific allometric equations [30] (Formula S1). N stocks (t\u0026middot;ha\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;) in tree, shrub, and herbaceous components, as well as in different litter fractions, were estimated by multiplying biomass by the corresponding N concentration (g\u0026middot;kg\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;). Total N stock for each ecosystem component was then obtained by summing the corresponding N pools in each plot. Calculations of total N and alkali-hydrolysable N stocks in different soil layers are provided in Formula S2 in the Supplementary Materials.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Calculation of nitrogen fluxes, nitrogen use efficiency, and nitrogen cycling indices\u003c/h2\u003e \u003cp\u003eAt the ecosystem scale, N fluxes were quantified as annual N uptake, annual N retention, annual N return, and annual N resorption (NRE)[29]. Annual N uptake was defined as the total amount of N absorbed from the soil and assimilated into plant organs within one year [31]. It was assumed to equal to the sum of NRE and annual N return [32]. Annual N retention was defined as the annual increase in N stocks of tree organs (t\u0026middot;ha\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;) [33]. For belowground N return, annual fine-root turnover was assumed; thus, fine-root N stocks was used to represent belowground N inputs. Annual N return was calculated as the sum of N input from aboveground litterfall and fine-root turnover. During July 2023\u0026ndash;July 2024, litterfall was collected throughout the year, and fine roots in the 0\u0026ndash;20 cm soil layer were sampled in July 2023. N stocks of litter fractions and fine roots were determined and summed to estimate annual N return.\u003c/p\u003e \u003cp\u003eN resorption represents an important internal nutrient-conservation strategy whereby N is withdrawn from senescing leaves and reallocated to perennial tissues (e.g., branches, stems, and roots) prior to abscission [34]. NRE (t\u0026middot;ha\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;) was derived from the difference in N concentration between mature and senesced needles, adjusted for mass loss during senescence to ensure accuracy [35] (Formulas S3\u0026thinsp;\u0026minus;\u0026thinsp;S4).\u003c/p\u003e \u003cp\u003eNUE characterizes the organic biomass yield per unit of absorbed N [36]. In addition, the N cycling coefficient (NCC) was calculated to represent the proportion of plant-acquired N that is returned to the soil via litterfall internally recycled, rather than being sustained by continued external N inputs (Formulas S5\u0026thinsp;\u0026minus;\u0026thinsp;S6).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Calculation of nitrogen nutritional strategy indices\u003c/h2\u003e \u003cp\u003eTo characterize plant N nutritional strategies, indicators were selected to represent N acquisition and N cycling, following Lang et al. [37]. N uptake efficiency (NUpE), N enrichment in topsoil, and the proportion of available nitrogen in soil were used to quantify N acquisition strategies, accumulation of N in forest floor litter, turnover rate of forest floor litter (%), and the internal N cycling ratio were used to quantify N cycling strategies[29] (Formulas S7\u0026thinsp;\u0026minus;\u0026thinsp;S12).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using R 4.3.3 [38]. Before statistical analyses, the data were tested for normality and homogeneity of variances. The study uses ANOVA to perform one-way analysis of variance and to test two-way interaction effects. The analysis then applies Tukey\u0026rsquo;s HSD test for multiple comparisons. The study examines whether biomass, nutrient concentration, nutrient storage, nutrient flux, and nutrient strategy indices differ among forest age classes. The study sets the significance level at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003ePCA was performed separately for plant nutrients, litter nutrients, soil nutrients, N uptake, and N cycling variables. Scores of the first principal component (PC1) were extracted and used as composite indicators of plant nutrient status (Plant_N), litter nutrient status (Litter_N), soil nutrient status (Soil_N), N acquisition status (N_acquisition), and N cycling status (N_cycling) in subsequent analyses (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA pSEM approach was applied to quantify the multi-path mechanisms by which stand age regulates N cycling. Before model construction, all variables were standardized. Correlation analysis and redundancy screening were conducted to reduce collinearity and avoid model overparameterization. In the pSEM framework, stand age was specified as an exogenous variable, whereas nutrient status in plant, litter, and soil, together with N acquisition and internal cycling processes, were specified as endogenous variables. Model fit was evaluated using Fisher\u0026rsquo;s C statistic, and standardized path coefficients and coefficient of determination (R\u003csup\u003e2\u003c/sup\u003e) were used to quantify the strength of relationships among variables.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Nitrogen concentrations of ecosystem components across stand ages\u003c/h2\u003e\n \u003cp\u003eSignificant differences in N concentrations among tree organs were detected among stand age gradient (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Across all stands, leaves consistently showed the highest N concentration, and did not vary significantly with stand age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). By contrast, N concentrations in stems, branches, fine roots, and coarse roots were significantly higher in the 11- and 47-year-old stands than in the 23- and 37-year-old stands. Understory vegetation and surface litter showed only minor variation in N concentration across stand ages, with significant differences observed only for the herbaceous layer among certain age classes. Soil N concentrations showed limited variation among stand ages, and significant differences occurred only in the 10\u0026thinsp;\u0026minus;\u0026thinsp;20 cm layer, where the 11-year-old stand had a lower N concentration than the other stands (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eN concentration (g\u0026middot;kg⁻\u0026sup1;) in different parts of \u003cem\u003eL. principis-rupprechtii\u003c/em\u003e plantations across stand ages.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eOrgans\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\n \u003cp\u003eStand age (year)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTree stem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e3.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e1.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTree branch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTree leaf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e21.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e23.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e21.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e24.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTree coarse root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e5.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e3.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e5.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTree fine root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e10.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e8.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e9.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e11.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eShrub-herbs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eShrub\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e10.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e12.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e11.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e13.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHerbs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e12.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e17.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e16.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e19.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eForest floor litter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e11.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e11.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e11.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e11.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;1 cm organic horizon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e5.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e5.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e6.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e5.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;10 cm mineral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e3.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e10\u0026thinsp;\u0026minus;\u0026thinsp;20 cm mineral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e1.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e3.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e20\u0026thinsp;\u0026minus;\u0026thinsp;30 cm mineral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e2.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e2.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e: Values in the table are showed as mean \u0026plusmn; standard deviation (n = 3). Different lowercase letters indicate significant differences among stand ages at the \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 level.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Biomass, nitrogen stocks and nitrogen allocation across stand ages\u003c/h2\u003e\n \u003cp\u003eSignificant stand-age effects were observed for the biomass and N stocks of vegetation components (Fig. \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Both biomass and N stocks in the tree layer increased continuously with stand development and have dominated the vegetation N pool across all ages. A significant unimodal pattern was observed in the forest floor litter layer. In contrast, biomass in the shrub-herb layer showed a significant decline from 11 to 23 years. At the ecosystem scale, soil was consistently identified as the largest N pool, accounting for \u0026gt;\u0026thinsp;87% of total ecosystem N stocks across all stand ages (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eSignificant differences were found in the allocation of biomass and N stocks among organs in the tree-shrub-herb layers (Fig. \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In the tree layer, biomass and N stocks of all organs were increased significantly with stand age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Both biomass and N storage were consistently dominated by stems, whereas leaves contributed relatively little throughout stand development (Fig. \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea,d). In the shrub layer, organ biomass and N stocks were decreased sharply from the young stage (11 years) to the middle-aged stage (23 years) and were followed by only a slight recovery thereafter (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, e). In the herb layer, organ biomass and N stocks showed a decreasing trend with increasing stand age; however, these differences were not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig. \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, f).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Nitrogen fluxes, nitrogen use efficiency, nitrogen cycling coefficient and soil nitrogen supply status\u003c/h2\u003e\n \u003cp\u003eAnnual N uptake and annual N retention all increased with stand age but the differences among stands were not statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig. \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The annual N return in the 11-year-old stand is significantly lower than that in the 47-year-old stand. NRE exhibited a similar trend, increasing from 11 to 37 years and remaining relatively stable thereafter (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). NUE increased significantly from the 11-year to the 23-year stands and reached its maximum in the 37-year stand (Table S3). A similar pattern was observed for the NCC, which increased from 11 to 37 years and decreased slightly at 47 years.\u003c/p\u003e\n \u003cp\u003eSoil available N stocks and annual N uptake exhibited a unimodal pattern across the stand-age gradient, with an initial increase followed by a decline (Fig. \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Across all stand ages, soil available N stocks were consistently and significantly higher than the corresponding annual N uptake. Across the four stand ages, the surplus of soil available N over annual N uptake was lowest at 11 years and peaked at 37 years. As stand age further increased to 47 years, the surplus showed a gradual decline.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Nitrogen nutrition strategy indicators\u003c/h2\u003e\n \u003cp\u003eAmong the N acquisition indices, NUpE and the proportion available nitrogen in soil were increased significantly with stand age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea,c). By contrast, N enrichment in topsoil tended to decrease along the stand-age gradient, although this trend was not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig. \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). For N cycling indices, accumulation of N in forest floor litter, turnover rate of forest floor litter, and the internal N cycling ratio were all increased significantly with stand age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed\u0026thinsp;\u0026minus;\u0026thinsp;f).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 Multivariate controls of nitrogen cycling\u003c/h2\u003e\n \u003cp\u003eIn the pSEM, stand age exerted a significant positive effect on plant nutrient status, which subsequently influenced litter and soil nutrient status (Fig. \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). N acquisition was primarily regulated by plant nutrient status. In contrast, N cycling status was driven directly by stand age and indirectly through N acquisition and litter nutrient status. Soil nutrient status had a negative effect on N cycling. Overall, the model showed a good fit to the data (Fisher\u0026rsquo;s C\u0026thinsp;=\u0026thinsp;8.04, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.43) (Table S4\u0026thinsp;\u0026minus;\u0026thinsp;S5).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Stand development reshapes nitrogen allocation across ecosystem components\u003c/h2\u003e \u003cp\u003eStand development drove a systematic reorganization of N allocation among ecosystem components in larch plantations. N stock in ecosystem plant components increased steadily across stand development and peaked at 47 years, which is consistent with reported stand-age patterns in N balance for larch plantations [39]. Meanwhile, the proportional contribution of the tree layer to total plant biomass and N stocks increased continuously with stand age. This pattern indicates that the tree layer progressively became the dominant and relatively stable long-term N pool during stand development. Similar shifts have been observed in temperate and boreal coniferous forests, where forest maturation is accompanied by nutrient transfer from rapidly cycling pools to structural and storage compartments [40].\u003c/p\u003e \u003cp\u003eAt the organ scale, stage-dependent differentiation in N accumulation was evident. Leaf tissues consistently maintained the highest N concentrations, reflecting their central role in photosynthesis and N metabolism, particularly during early development when carbon acquisition and growth are rapidly initiated [20]. Although N accumulation increased with stand age in most organs, its trajectory was not fully synchronized with structural growth, suggesting stage-dependent adjustments in resource allocation. During early development, N was preferentially allocated to functional organs to sustain rapid growth, resulting in relative N dilution in woody tissues [41]. As stands approached mid and late development, growth rates declined after structural construction had largely been completed, and greater N allocation to woody tissues and long-term storage pools was indicated [42]. This pattern is consistent with a transition from a resource-acquisitive phase to a more conservative phase in which internal recycling is strengthened. Comparable shifts have been reported in other temperate coniferous forests [43] and may be facilitated by increased litter inputs, stabilization of soil N supply, and improved N resorption and redistribution in plants [44].\u003c/p\u003e \u003cp\u003eAlthough the shrub-herb layer contributed only a small fraction of total ecosystem biomass and N stocks, its marked decline after the young stage likely reflected progressive light limitation associated with canopy closure [45]. Understory vegetation often exhibits relatively high N concentrations and rapid turnover, and may therefore function as a catalytic component of ecosystem N cycling despite its small biomass [46]. In particular, during early to middle development, understory turnover may contribute disproportionately to nutrient fluxes and productivity, and its ecological role should not be inferred solely from pool magnitude [47].\u003c/p\u003e \u003cp\u003eBeyond vegetation, distinct yet complementary roles were indicated for litter and soil in shaping ecosystem N dynamics. Surface litter, characterized by relatively high N concentration and rapid accumulation, formed an important transient N pool during the middle stage (23 years), likely reflecting a temporary imbalance between litter inputs and decomposition. From an ecosystem development perspective, a shift from rapid nutrient accumulation to more efficient recycling is widely regarded as a hallmark of forest maturation, and higher NUE has frequently been observed in mature stands [48]. Throughout stand development, soil remained the overwhelmingly dominant N pool (\u0026gt;\u0026thinsp;87% of total ecosystem N), underscoring the foundational role of soil organic matter in sustaining long-term productivity and nutrient stability in plantations [49].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Nitrogen supply-demand balance and age-dependent nitrogen use efficiency in larch plantations\u003c/h2\u003e \u003cp\u003eAcross the stand-age gradient, soil available N stocks consistently exceeded annual plant N uptake, and the supply-demand surplus was greatest at the mid-aged stage (37 years). These patterns suggest that strong N limitation was unlikely during stand development in the study area. Although plant N demand was increased with stand age, a large soil organic N pool (\u0026gt;\u0026thinsp;87% of total ecosystem N), together with sustained litter inputs and internal soil transformations, appeared to maintain a relatively stable N supply and to prevent persistent supply-demand imbalance [48]. This result further suggests that N limitation should not be inferred from plant biomass or total soil N alone; instead, ecosystem diagnosis is better supported when supply-demand relationships are quantified. Given the relatively limited sample size, further studies are required to verify the supply\u0026ndash;demand dynamics across a broader stand-age gradient.\u003c/p\u003e \u003cp\u003eAgainst this background, NUE and NCC exhibited unimodal patterns, with maxima at 37 years, indicating that the mid-aged stage represented the most economical phase of N utilization. At this stage, N reuse was maximized through enhanced resorption and internal cycling, thereby reducing dependence on external soil N inputs and promoting a closer coupling between growth demand and nutrient recycling [50, 51]. The co-occurrence of high utilization efficiency and sufficient N supply may explain the optimal nutrient balance observed at 37 years. In the near-mature stage (47 years), NUE was moderately reduced, potentially because growth was slowed, maintenance respiration was increased, and competition for nutrients between plants and soil microorganisms was intensified [52]. Similar age-related declines in NUE have been reported for coniferous forests (e.g., Scots pine and Norway spruce) [53], consistent with physiological aging and diminishing marginal returns of nutrient use in mature trees [54].\u003c/p\u003e \u003cp\u003eThe NCC was increased from the young (11 years) to mid-aged (37 years) stands, indicating that an increasingly large fraction of acquired N was returned to soil via litter inputs, thereby strengthening ecosystem N retention and internal recycling. A slight decline from 37 to 47 years was observed, potentially reflecting stagnation in litter production or reduced litter quality. However, the coefficient remained relatively high, indicating that cycling efficiency was largely maintained and that the risk of nutrient loss remained low in mature stands [51]. Overall, larch plantations were characterized by an N-use pattern of adequate supply and efficient cycling, which likely explains the absence of evident N limitation in this region [41].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Shifts in nitrogen nutrition strategies along stand development\u003c/h2\u003e \u003cp\u003eStage-dependent changes in N fluxes and strategy indices indicated a clear shift in N utilization during stand development. NUE, NRE, and NCC all peaked at the mid-aged stage [51], suggesting that N was used most efficiently when growth demand, soil N supply, and internal recycling were likely most closely coordinated [30, 55].\u003c/p\u003e \u003cp\u003eAt the acquisition level, NUpE showed a positive but non-significant trend with stand age, implying that intrinsic plant N acquisition capacity was not substantially altered over development. Because NUpE is jointly regulated by root morphology, mycorrhizal associations, and physiological uptake capacity [52, 56], the absence of a significant increase suggests that stronger acquisition was not required. Consistently, the proportion available nitrogen in soil increased significantly with stand age, indicating enhanced N availability during forest development [57]. This increase was likely promoted by greater litter inputs and accelerated mineralization, which would have stabilized external N supply and reduced reliance on improved uptake efficiency. The slight decline in the N enrichment in topsoil may have been driven by deeper rooting and sustained nutrient uptake, although this effect was not sufficiently strong to yield significant differences [58, 59].\u003c/p\u003e \u003cp\u003eIn contrast, N cycling strategies were adjusted more strongly than acquisition traits. With increasing stand age, both forest floor N accumulation and litter turnover rate increased significantly, indicating an intensification of litter-mediated recycling. In mid-aged and mature stands, faster litter decomposition may promote more rapid N release and re-entry into plant uptake pathways, thereby tightening internal cycling [48]. Such litter-driven enhancement of N cycling is considered a key indicator of ecosystem maturation and reflects improved self-maintenance and nutrient retention capacity [60]. Overall, larch plantations exhibited a progressive shift from acquisition-dominated to recycling-dominated N strategies, highlighting an age-driven reorganization of N cycling pathways.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Multivariate pathways regulating nitrogen cycling revealed by piecewise structural equation modeling\u003c/h2\u003e \u003cp\u003eThe pSEM elucidated the multiple pathways through which stand age regulates N cycling. Stand age was identified as the primary integrative driver, with both direct effects and indirect effects mediated through biomass accumulation, internal N storage, litter inputs, and soil development. Along the N acquisition pathway, plant nutrient status exerted a stronger positive effect on N uptake than stand age, indicating that acquisition was mainly demand-driven rather than directly constrained by developmental stage[61]. Accordingly, expansion of the vegetation N pool during stand development appeared to be supported primarily by demand-mediated increases in uptake and internal retention, rather than by age alone. Notably, greater N uptake was not necessarily associated with faster ecosystem N turnover, suggesting that enhanced acquisition does not inevitably accelerate cycling rates [62, 63]. Along the N cycling pathway, a significant positive direct effect of stand age was detected and was further strengthened by litter nutrient status. With stand maturation, biomass accumulation, enhanced uptake capacity, and stronger internal retention were jointly promoted, thereby facilitating vegetation N pool expansion [64]. Although the litter-to-soil N pathway was not statistically significant, the positive direction suggested that litter inputs may still act as an important mediator of soil N accumulation, potentially via decomposition and N release processes [65, 66]. Conversely, a negative effect of soil nutrient status on N cycling was observed, which may reflect a transient reduction in readily available soil N under intensified plant uptake, followed by compensation through litter return and decomposition [48]. This pattern may reflect temporary depletion of available soil N under increased plant uptake.\u003c/p\u003e \u003cp\u003eOverall, the pSEM results offered a mechanistic synthesis that was consistent with the observed patterns of N allocation, supply-demand balance, and nutritional strategy shifts. A stage-dependent transition from acquisition-dominated to internally regulated N cycling was indicated for larch plantations, implying reduced sensitivity of mature stands to external N inputs and short-term disturbances. The satisfactory model fit further supported the ecological plausibility of the hypothesized stand age-plant-litter-soil pathways and provided insight into nutrient dynamics and potential constraints across developmental stages.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eAcross a 11\u0026ndash;47-year chronosequence of larch plantations, stand development increased vegetation biomass and N stocks, while soil remained the dominant ecosystem N pool (\u0026gt;\u0026thinsp;87%). The soil alkali-hydrolysable N pool consistently exceeded annual plant N uptake, indicating no evidence of acute N shortage based on available N pools. Stand development was associated with a strategic shift from soil-acquisition dependence in young stands toward recycling-centered N use in older stands, with NUE peaking at the mid-aged stage. The pSEM further suggested that N acquisition was mainly linked to plant nutrient status, whereas N cycling was driven by stand age and reinforced by litter nutrient status. Management of mature larch plantations should therefore prioritize maintaining litter-mediated internal cycling (e.g., conserving the forest floor and avoiding practices that disrupt litter decomposition) rather than relying primarily on external N inputs.\u003c/p\u003e"},{"header":"Abbreviation ","content":"\u003cp\u003eRNE annual nitrogen resorption\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNUE nitrogen use efficiency\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNCC nitrogen cycling coefficient\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNUpE nitrogen uptake efficiency\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSANP proportion available nitrogen in soil\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFFNA accumulation of nitrogen in forest floor\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLTR turnover rate of forest floor litter\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eINC internal nitrogen cycling\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch involving plants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experimental research and field studies on plants conducted in this work adhere to Chinese institutional, national, and international guidelines and legislation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the State Key Research and Development Program (2023YFD2200803), and Major Science and Technology Support Program of Hebei Province (252L6802D, 252L6801D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX.C., writing—original draft, visualization, methodology, investigation, and data curation; Z.G., writing—review and editing, conceptualization, and visualization; Q.L., performed investigation and data curation; Y.P., investigation and conceptualization; Z.Z., writing—review and editing, project administration, funding acquisition, and validation. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are deeply grateful to the editor and reviewers for their comments and\u0026nbsp;\u003c/p\u003e\n\u003cp\u003esuggestions on the manuscript. All authors would like to thank all the staff of Saihanba Forest Farm for their support to the research work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eRennenberg H, Schmidt S: \u003cstrong\u003ePerennial lifestyle-an adaptation to nutrient limitation?\u003c/strong\u003e \u003cem\u003eTree Physiol\u0026nbsp;\u003c/em\u003e2010, \u003cstrong\u003e30\u003c/strong\u003e(9):1047-1049.\u003c/li\u003e\n \u003cli\u003eLeBauer DS, Treseder KK: \u003cstrong\u003eNitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed\u003c/strong\u003e. \u003cem\u003eEcology\u0026nbsp;\u003c/em\u003e2008, \u003cstrong\u003e89\u003c/strong\u003e(2):371-379.\u003c/li\u003e\n \u003cli\u003eHu YF, Shu XY, He J, Zhang YL, Xiao HH, Tang XY, Gu YF, Lan T, Xia JG, Ling J\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eStorage of C, N, and P affected by afforestation with \u003cem\u003eSalix cupularis\u003c/em\u003e in an alpine semiarid desert ecosystem\u003c/strong\u003e. \u003cem\u003eLand Degrad Dev\u0026nbsp;\u003c/em\u003e2018, \u003cstrong\u003e29\u003c/strong\u003e(1):188-198.\u003c/li\u003e\n \u003cli\u003eHjelm K, Romans E, H\u0026ouml;gbom L, Ring E: \u003cstrong\u003eTree growth and ground vegetation 17 years after disc trenching and preharvest nitrogen fertilization\u003c/strong\u003e. \u003cem\u003eFor Ecol Manag\u0026nbsp;\u003c/em\u003e2025, \u003cstrong\u003e597\u003c/strong\u003e:123145.\u003c/li\u003e\n \u003cli\u003eZhang P, L\u0026uuml; XT, Li MH, Wu TG, Jin GZ: \u003cstrong\u003eN limitation increases along a temperate forest succession: evidences from leaf stoichiometry and nutrient resorption\u003c/strong\u003e. \u003cem\u003eJ Plant Ecol\u0026nbsp;\u003c/em\u003e2022b, \u003cstrong\u003e15\u003c/strong\u003e(5):1021-1035.\u003c/li\u003e\n \u003cli\u003eDu EZ, Terrer C, Pellegrini AFA, Ahlstr\u0026ouml;m A, van Lissa CJ, Zhao X, Xia N, Wu XH, Jackson RB: \u003cstrong\u003eGlobal patterns of terrestrial nitrogen and phosphorus limitation\u003c/strong\u003e. \u003cem\u003eNat Geosci\u0026nbsp;\u003c/em\u003e2020, \u003cstrong\u003e13\u003c/strong\u003e(3):221-226.\u003c/li\u003e\n \u003cli\u003eZiegler SE, Billings SA, Podrebarac FA, Edwards KA, Skinner A, Buckeridge KM, Vandenboer TC: \u003cstrong\u003eBiogeochemical evidence raises questions on the longevity of warming-induced growth enhancements in wet boreal forests\u003c/strong\u003e. \u003cem\u003eEcosphere\u0026nbsp;\u003c/em\u003e2024, \u003cstrong\u003e15\u003c/strong\u003e(12):e70109.\u003c/li\u003e\n \u003cli\u003eLi YB, Zhu Q, Zhang Y, Liu S, Wang XT, Wang EH: \u003cstrong\u003eImpact of winter cover crops on total and microbial carbon and nitrogen in black soil\u003c/strong\u003e. \u003cem\u003eAgronomy-Basel\u0026nbsp;\u003c/em\u003e2024, \u003cstrong\u003e14\u003c/strong\u003e(3):603.\u003c/li\u003e\n \u003cli\u003eMao L, He XX, Ye SM, Wang SQ: \u003cstrong\u003eSoil aggregate-associated carbon-cycle and nitrogen-cycle enzyme activities as affected by stand age in Chinese fir plantations\u003c/strong\u003e. \u003cem\u003eJ Soil Sci Plant Nutr\u0026nbsp;\u003c/em\u003e2023, \u003cstrong\u003e23\u003c/strong\u003e(3):4361-4372.\u003c/li\u003e\n \u003cli\u003eJha KK: \u003cstrong\u003eTemporal patterns of storage and flux of N and P in young Teak plantations of tropical moist deciduous forest, India\u003c/strong\u003e. \u003cem\u003eJ For Res\u0026nbsp;\u003c/em\u003e2014, \u003cstrong\u003e25\u003c/strong\u003e(1):75-86.\u003c/li\u003e\n \u003cli\u003eRanger J, Allie S, Gelhaye D, Pollier B, Turpault MP, Granier A: \u003cstrong\u003eNutrient budgets for a rotation of a Douglas-fir plantation in the Beaujolais (France) based on a chronosequence study\u003c/strong\u003e. \u003cem\u003eFor Ecol Manag\u0026nbsp;\u003c/em\u003e2002, \u003cstrong\u003e171\u003c/strong\u003e(1-2):3-16.\u003c/li\u003e\n \u003cli\u003eZhou LL, Shalom ADD, Wu PF, He ZM, Liu CH, Ma XQ: \u003cstrong\u003eBiomass production, nutrient cycling and distribution in age-sequence Chinese fir (\u003cem\u003eCunninghamia lanceolate\u003c/em\u003e) plantations in subtropical China\u003c/strong\u003e. \u003cem\u003eJ For Res\u0026nbsp;\u003c/em\u003e2016, \u003cstrong\u003e27\u003c/strong\u003e(2):357-368.\u003c/li\u003e\n \u003cli\u003eZhou LL, Li SB, Jia YY, Heal K, He ZM, Wu PF, Ma XQ: \u003cstrong\u003eSpatiotemporal distribution of canopy litter and nutrient resorption in a chronosequence of different development stages of \u003cem\u003eCunninghamia lanceolata\u003c/em\u003e in Southeast China\u003c/strong\u003e. \u003cem\u003eSci Total Environ\u0026nbsp;\u003c/em\u003e2021, \u003cstrong\u003e762\u003c/strong\u003e:143153.\u003c/li\u003e\n \u003cli\u003eReich PB, Hobbie SE, Lee T, Ellsworth DS, West JB, Tilman D, Knops JMH, Naeem S, Trost J: \u003cstrong\u003eNitrogen limitation constrains sustainability of ecosystem response to CO\u003csub\u003e2\u003c/sub\u003e\u003c/strong\u003e. \u003cem\u003eNature\u0026nbsp;\u003c/em\u003e2006, \u003cstrong\u003e440\u003c/strong\u003e(7086):922-925.\u003c/li\u003e\n \u003cli\u003ePerchlik M, Tegeder M: \u003cstrong\u003eLeaf amino acid supply affects photosynthetic and plant nitrogen use efficiency under nitrogen stress\u003c/strong\u003e. \u003cem\u003ePlant Physiol\u0026nbsp;\u003c/em\u003e2018, \u003cstrong\u003e178\u003c/strong\u003e(1):174-188.\u003c/li\u003e\n \u003cli\u003eWu HL, Xiang WH, Ouyang S, Xiao WF, Li SG, Chen L, Lei PF, Deng XW, Zeng YL, Zeng LX\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eTree growth rate and soil nutrient status determine the shift in nutrient-use strategy of Chinese fir plantations along a chronosequence\u003c/strong\u003e. \u003cem\u003eFor Ecol Manag\u0026nbsp;\u003c/em\u003e2020, \u003cstrong\u003e460\u003c/strong\u003e:117896.\u003c/li\u003e\n \u003cli\u003eFeng HL, Guo JH, Peng CH, Kneeshaw D, Roberge G, Pan C, Ma XH, Zhou D, Wang WF: \u003cstrong\u003eNitrogen addition promotes terrestrial plants to allocate more biomass to aboveground organs: a global meta-analysis\u003c/strong\u003e. \u003cem\u003eGlobal Change Biol\u0026nbsp;\u003c/em\u003e2023, \u003cstrong\u003e29\u003c/strong\u003e(14):3970-3989.\u003c/li\u003e\n \u003cli\u003eKillingbeck KT: \u003cstrong\u003eNutrients in senesced leaves: keys to the search for potential resorption and resorption proficiency\u003c/strong\u003e. \u003cem\u003eEcology\u0026nbsp;\u003c/em\u003e1996, \u003cstrong\u003e77\u003c/strong\u003e(6):1716-1727.\u003c/li\u003e\n \u003cli\u003eZhang X, Li BY, Penuelas J, Sardans J, Cheng DL, Yu H, Zhong QL: \u003cstrong\u003eResource-acquisitive species have greater plasticity in leaf functional traits than resource-conservative species in response to nitrogen addition in subtropical China\u003c/strong\u003e. \u003cem\u003eSci Total Environ\u0026nbsp;\u003c/em\u003e2023, \u003cstrong\u003e903\u003c/strong\u003e:166177.\u003c/li\u003e\n \u003cli\u003eYan T, Fang YT, Wang JS, Song HH, Zhong TY, Wang PL: \u003cstrong\u003eEffects of long-term nitrogen addition on the shift of nitrogen cycle from open to closed along an age gradient of larch plantations in North China\u003c/strong\u003e. \u003cem\u003eSoil Biol Biochem\u0026nbsp;\u003c/em\u003e2024, \u003cstrong\u003e191\u003c/strong\u003e:109295.\u003c/li\u003e\n \u003cli\u003eAsaadi A, Arora VK: \u003cstrong\u003eImplementation of nitrogen cycle in the CLASSIC land model\u003c/strong\u003e. \u003cem\u003eBiogeosciences\u0026nbsp;\u003c/em\u003e2021, \u003cstrong\u003e18\u003c/strong\u003e(2):669-706.\u003c/li\u003e\n \u003cli\u003eNie YX, Han XG, Chen J, Wang MC, Shen WJ: \u003cstrong\u003eThe simulated N deposition accelerates net N mineralization and nitrification in a tropical forest soil\u003c/strong\u003e. \u003cem\u003eBiogeosciences\u0026nbsp;\u003c/em\u003e2019, \u003cstrong\u003e16\u003c/strong\u003e(21):4277-4291.\u003c/li\u003e\n \u003cli\u003eChen XL, Taylor AR, Reich PB, Hisano M, Chen HYH, Chang SX: \u003cstrong\u003eTree diversity increases decadal forest soil carbon and nitrogen accrual\u003c/strong\u003e. \u003cem\u003eNature\u0026nbsp;\u003c/em\u003e2023, \u003cstrong\u003e618\u003c/strong\u003e(7963):94-101.\u003c/li\u003e\n \u003cli\u003eCosta AD, Torres FTP, Lima GS, de Melo FR, Torres C, Schettini BLS, Neto VPS, de Faria ALL: \u003cstrong\u003eInfluence of fire on woody vegetation of savanna and forest formations in the Cerrado biome\u003c/strong\u003e. \u003cem\u003eJ For Res\u0026nbsp;\u003c/em\u003e2023, \u003cstrong\u003e34\u003c/strong\u003e(5):1207-1216.\u003c/li\u003e\n \u003cli\u003eQiu XC, Wang HB, Peng DL, Liu X, Yang F, Li Z, Cheng S: \u003cstrong\u003eThinning drives C:N:P stoichiometry and nutrient resorption in Larix principis-rupprechtii plantations in North China\u003c/strong\u003e. \u003cem\u003eFor Ecol Manag\u0026nbsp;\u003c/em\u003e2020, \u003cstrong\u003e462\u003c/strong\u003e.\u003c/li\u003e\n \u003cli\u003eZhang JF, Li MH, Liu Q, Pang Y, Zhang ZD: \u003cstrong\u003eEcosystem service synergies and trade-offs in poplar-birch mixed natural forests across different developmental stages\u003c/strong\u003e. \u003cem\u003eForests\u0026nbsp;\u003c/em\u003e2025, \u003cstrong\u003e16\u003c/strong\u003e(5):867.\u003c/li\u003e\n \u003cli\u003eJin J, Wang HR, Zhang ZD, Gao Y, Liu Q, Fu LH, Chen DS, Dong LH, Xie HT, Lu DL: \u003cstrong\u003eOptimizing understory afforestation of shade-tolerant conifer \u003cem\u003ePicea asperata\u003c/em\u003e across canopy transmittance gradients\u003c/strong\u003e. \u003cem\u003eEur J For Res\u0026nbsp;\u003c/em\u003e2026, \u003cstrong\u003e145\u003c/strong\u003e(2):29.\u003c/li\u003e\n \u003cli\u003eGe ZX, Peng B, Chen XT, Zhang JF, Wang ZY, Pang Y, Zhang ZD: \u003cstrong\u003ePlant functional traits and soil properties shape soil microbial communities in \u003cem\u003eLarix principis-rupprechtii\u003c/em\u003e mixed plantations\u003c/strong\u003e. \u003cem\u003eBiology\u0026nbsp;\u003c/em\u003e2026, \u003cstrong\u003e15\u003c/strong\u003e(3):259.\u003c/li\u003e\n \u003cli\u003eWu HL, Chen L, Ouyang S, Zhou WN, Wu MG, Zeng LX, Lei PF, Zeng YL, Deng XW, Li SG\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003ePhosphorus cycling and supply-demand balance across a chronosequence of Chinese fir plantations\u003c/strong\u003e. \u003cem\u003eCatena\u0026nbsp;\u003c/em\u003e2023, \u003cstrong\u003e228\u003c/strong\u003e:107117.\u003c/li\u003e\n \u003cli\u003eZhou GY, Yin GC, Tang Xl, Wen DZ, Liu CP, Kuang YD, Wang WT: \u003cstrong\u003eCarbon stocks in Chinese forest ecosystems: the biomass equation\u003c/strong\u003e. Beijing: Science Press; 2018.\u003c/li\u003e\n \u003cli\u003eSchimel JP, Bennett J: \u003cstrong\u003eNitrogen mineralization: challenges of a changing paradigm\u003c/strong\u003e. \u003cem\u003eEcology\u0026nbsp;\u003c/em\u003e2004, \u003cstrong\u003e85\u003c/strong\u003e(3):591-602.\u003c/li\u003e\n \u003cli\u003eFang YT, Gundersen P, Mo JM, Zhu WX: \u003cstrong\u003eInput and output of dissolved organic and inorganic nitrogen in subtropical forests of South China under high air pollution\u003c/strong\u003e. \u003cem\u003eBiogeosciences\u0026nbsp;\u003c/em\u003e2008, \u003cstrong\u003e5\u003c/strong\u003e(2):339-352.\u003c/li\u003e\n \u003cli\u003eLiu GC, Yin ZW, Yan GY, Liu S, Wang XC, Xing YJ, Wang QG: \u003cstrong\u003eEffects of long-term nitrogen addition on the \u0026delta;\u003csup\u003e15\u003c/sup\u003eN and \u0026delta;\u003csup\u003e13\u003c/sup\u003eC of \u003cem\u003eLarix gmelinii\u003c/em\u003e and soil in a boreal forest\u003c/strong\u003e. \u003cem\u003eEcological Processes\u0026nbsp;\u003c/em\u003e2022, \u003cstrong\u003e11\u003c/strong\u003e(1):37.\u003c/li\u003e\n \u003cli\u003eYuan ZY, Chen HYH: \u003cstrong\u003eGlobal-scale patterns of nutrient resorption associated with latitude, temperature and precipitation\u003c/strong\u003e. \u003cem\u003eGlobal Ecol Biogeogr\u0026nbsp;\u003c/em\u003e2009, \u003cstrong\u003e18\u003c/strong\u003e(1):11-18.\u003c/li\u003e\n \u003cli\u003eVergutz L, Manzoni S, Porporato A, Novais RF, Jackson RB: \u003cstrong\u003eGlobal resorption efficiencies and concentrations of carbon and nutrients in leaves of terrestrial plants\u003c/strong\u003e. \u003cem\u003eEcol Monogr\u0026nbsp;\u003c/em\u003e2012, \u003cstrong\u003e82\u003c/strong\u003e(2):205-220.\u003c/li\u003e\n \u003cli\u003eHirel B, Le Gouis J, Ney B, Gallais A: \u003cstrong\u003eThe challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches\u003c/strong\u003e. \u003cem\u003eJ Exp Bot\u0026nbsp;\u003c/em\u003e2007, \u003cstrong\u003e58\u003c/strong\u003e(9):2369-2387.\u003c/li\u003e\n \u003cli\u003eLang F, Kr\u0026uuml;ger J, Amelung W, Willbold S, Frossard E, B\u0026uuml;nemann EK, Bauhus J, Nitschke R, Kandeler E, Marhan S\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eSoil phosphorus supply controls P nutrition strategies of beech forest ecosystems in Central Europe\u003c/strong\u003e. \u003cem\u003eBiogeochemistry\u0026nbsp;\u003c/em\u003e2017, \u003cstrong\u003e136\u003c/strong\u003e(1):5-29.\u003c/li\u003e\n \u003cli\u003eR Core Team: \u003cstrong\u003eR: A language and environment for statistical computing\u003c/strong\u003e. In\u003cem\u003e.\u003c/em\u003e, 4.3.3 edn. Vienna: R Foundation for Statistical Computing; 2024.\u003c/li\u003e\n \u003cli\u003eFrisman EY, Zhdanova OL, Kulakov MP, Neverova GP, Revutskaya OL: \u003cstrong\u003eMathematical modeling of population dynamics based on recurrent equations: results and prospects, part I\u003c/strong\u003e. \u003cem\u003eBiol Bull\u0026nbsp;\u003c/em\u003e2021, \u003cstrong\u003e48\u003c/strong\u003e(1):1-15.\u003c/li\u003e\n \u003cli\u003eLuyssaert S, Schulze ED, B\u0026ouml;rner A, Knohl A, Hessenm\u0026ouml;ller D, Law BE, Ciais P, Grace J: \u003cstrong\u003eOld-growth forests as global carbon sinks\u003c/strong\u003e. \u003cem\u003eNature\u0026nbsp;\u003c/em\u003e2008, \u003cstrong\u003e455\u003c/strong\u003e(7210):213-215.\u003c/li\u003e\n \u003cli\u003eLiu WL, Zu JX, Liu B, Qi L, Huang W, Fang YT, Yang J: \u003cstrong\u003eWildfire effects on the fate of deposited nitrogen in a boreal larch forest\u003c/strong\u003e. \u003cem\u003eBiogeochemistry\u0026nbsp;\u003c/em\u003e2024, \u003cstrong\u003e167\u003c/strong\u003e(5):681-693.\u003c/li\u003e\n \u003cli\u003eMillard P, Grelet GA: \u003cstrong\u003eNitrogen storage and remobilization by trees: ecophysiological relevance in a changing world\u003c/strong\u003e. \u003cem\u003eTree Physiol\u0026nbsp;\u003c/em\u003e2010, \u003cstrong\u003e30\u003c/strong\u003e(9):1083-1095.\u003c/li\u003e\n \u003cli\u003eBertiller MB, Sain CL, Carrera AL, Vargas DN: \u003cstrong\u003ePatterns of nitrogen and phosphorus conservation in dominant perennial grasses and shrubs across an aridity gradient in Patagonia, Argentina\u003c/strong\u003e. \u003cem\u003eJ Arid Environ\u0026nbsp;\u003c/em\u003e2005, \u003cstrong\u003e62\u003c/strong\u003e(2):209-223.\u003c/li\u003e\n \u003cli\u003eVan Langenhove L, Depaepe T, Vicca S, van den Berge J, Stahl C, Courtois E, Weedon J, Urhina I, Grau O, Asensio D\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eRegulation of nitrogen fixation from free-living organisms in soil and leaf litter of two tropical forests of the Guiana shield\u003c/strong\u003e. \u003cem\u003ePlant Soil\u0026nbsp;\u003c/em\u003e2020, \u003cstrong\u003e450\u003c/strong\u003e(1-2):93-110.\u003c/li\u003e\n \u003cli\u003eBarbier S, Gosselin F, Balandier P: \u003cstrong\u003eInfluence of tree species on understory vegetation diversity and mechanisms involved-a critical review for temperate and boreal forests\u003c/strong\u003e. \u003cem\u003eFor Ecol Manag\u0026nbsp;\u003c/em\u003e2008, \u003cstrong\u003e254\u003c/strong\u003e(1):1-15.\u003c/li\u003e\n \u003cli\u003eGrogan P, Jonasson S: \u003cstrong\u003eControls on annual nitrogen cycling in the understory of a subarctic birch forest\u003c/strong\u003e. \u003cem\u003eEcology\u0026nbsp;\u003c/em\u003e2003, \u003cstrong\u003e84\u003c/strong\u003e(1):202-218.\u003c/li\u003e\n \u003cli\u003eCui ER, Xia JY, Luo YQ: \u003cstrong\u003eNitrogen use strategy drives interspecific differences in plant photosynthetic CO\u003csub\u003e2\u003c/sub\u003e acclimation\u003c/strong\u003e. \u003cem\u003eGlobal Change Biol\u0026nbsp;\u003c/em\u003e2023, \u003cstrong\u003e29\u003c/strong\u003e(13):3667-3677.\u003c/li\u003e\n \u003cli\u003eXia Q, Chen L, Xiang WH, Ouyang S, Wu HL, Lei PF, Xiao WF, Li SG, Zeng LX, Kuzyakov Y: \u003cstrong\u003eIncrease of soil nitrogen availability and recycling with stand age of Chinese-fir plantations\u003c/strong\u003e. \u003cem\u003eFor Ecol Manag\u0026nbsp;\u003c/em\u003e2021, \u003cstrong\u003e480\u003c/strong\u003e:118643.\u003c/li\u003e\n \u003cli\u003eFang HJ, Yu GR, Cheng SL, Zhu TH, Zheng JJ, Mo JM, Yan JH, Luo YQ: \u003cstrong\u003eNitrogen-15 signals of leaf-litter-soil continuum as a possible indicator of ecosystem nitrogen saturation by forest succession and N loads\u003c/strong\u003e. \u003cem\u003eBiogeochemistry\u0026nbsp;\u003c/em\u003e2011, \u003cstrong\u003e102\u003c/strong\u003e(1-3):251-263.\u003c/li\u003e\n \u003cli\u003eZhu LQ, Sun J, Yao XD, Wang XH, Huang JX, Xiong DC, Chen GS: \u003cstrong\u003eFine root nutrient foraging ability in relation to carbon availability along a chronosequence of Chinese fir plantations\u003c/strong\u003e. \u003cem\u003eFor Ecol Manag\u0026nbsp;\u003c/em\u003e2022, \u003cstrong\u003e507\u003c/strong\u003e:120003.\u003c/li\u003e\n \u003cli\u003eZhang H, Sun M, Wen YX, Tong R, Wang G, Wu QQ, Li Y, Wu TG: \u003cstrong\u003eThe effects of stand age on leaf N:P cannot be neglected: a global synthesis\u003c/strong\u003e. \u003cem\u003eFor Ecol Manag\u0026nbsp;\u003c/em\u003e2022a, \u003cstrong\u003e518\u003c/strong\u003e:120294.\u003c/li\u003e\n \u003cli\u003eGessler A, Schaub M, McDowell NG: \u003cstrong\u003eThe role of nutrients in drought-induced tree mortality and recovery\u003c/strong\u003e. \u003cem\u003eNew Phytol\u0026nbsp;\u003c/em\u003e2017, \u003cstrong\u003e214\u003c/strong\u003e(2):513-520.\u003c/li\u003e\n \u003cli\u003eM\u0026auml;kinen H, Ilvesniemi H, Lindroos AJ, Smolander A: \u003cstrong\u003eEffects of wood ash, nitrogen, and biosolids fertilisation on the growth and soil properties of Scots pine and Norway spruce stands\u003c/strong\u003e. \u003cem\u003eFor Ecol Manag\u0026nbsp;\u003c/em\u003e2025, \u003cstrong\u003e578\u003c/strong\u003e:122467.\u003c/li\u003e\n \u003cli\u003eTang JW, Luyssaert S, Richardson AD, Kutsch W, Janssens IA: \u003cstrong\u003eSteeper declines in forest photosynthesis than respiration explain age-driven decreases in forest growth\u003c/strong\u003e. \u003cem\u003eProc Natl Acad Sci USA\u0026nbsp;\u003c/em\u003e2014, \u003cstrong\u003e111\u003c/strong\u003e(24):8856-8860.\u003c/li\u003e\n \u003cli\u003eLeduc SD, Rothstein DE: \u003cstrong\u003ePlant-available organic and mineral nitrogen shift in dominance with forest stand age\u003c/strong\u003e. \u003cem\u003eEcology\u0026nbsp;\u003c/em\u003e2010, \u003cstrong\u003e91\u003c/strong\u003e(3):708-720.\u003c/li\u003e\n \u003cli\u003eRead DJ, Perez-Moreno J: \u003cstrong\u003eMycorrhizas and nutrient cycling in ecosystems: A journey towards relevance?\u003c/strong\u003e \u003cem\u003eNew Phytol\u0026nbsp;\u003c/em\u003e2003, \u003cstrong\u003e157\u003c/strong\u003e(3):475-492.\u003c/li\u003e\n \u003cli\u003eZhang Y, Tigabu M, Yi ZG, Li HT, Zhuang Z, Yang Z, Ma XQ: \u003cstrong\u003eSoil parent material and stand development stage effects on labile soil C and N pools in Chinese fir plantations\u003c/strong\u003e. \u003cem\u003eGeoderma\u0026nbsp;\u003c/em\u003e2019, \u003cstrong\u003e338\u003c/strong\u003e:247-258.\u003c/li\u003e\n \u003cli\u003eMcCulley RL, Jobb\u0026aacute;gy EG, Pockman WT, Jackson RB: \u003cstrong\u003eNutrient uptake as a contributing explanation for deep rooting in arid and semi-arid ecosystems\u003c/strong\u003e. \u003cem\u003eOecologia\u0026nbsp;\u003c/em\u003e2004, \u003cstrong\u003e141\u003c/strong\u003e(4):620-628.\u003c/li\u003e\n \u003cli\u003ePeng S, Zhang YK, Chen HYH: \u003cstrong\u003ePlant functional trait dissimilarity drives plant mixture effects on fine root biomass and trait variations\u003c/strong\u003e. \u003cem\u003eNew Phytol\u0026nbsp;\u003c/em\u003e2026, \u003cstrong\u003e249\u003c/strong\u003e(2):764-776.\u003c/li\u003e\n \u003cli\u003eWardle DA, Bardgett RD, Klironomos JN, Set\u0026auml;l\u0026auml; H, Putten WHvd, Wall DH: \u003cstrong\u003eEcological linkages between aboveground and belowground biota\u003c/strong\u003e. \u003cem\u003eScience\u0026nbsp;\u003c/em\u003e2004, \u003cstrong\u003e304\u003c/strong\u003e(5677):1629-1633.\u003c/li\u003e\n \u003cli\u003eZhu XM, Lambers H, Guo WJ, Chen DD, Liu ZF, Zhang ZL, Yin HJ: \u003cstrong\u003eExtraradical hyphae exhibit more plastic nutrient-acquisition strategies than roots under nitrogen enrichment in ectomycorrhiza-dominated forests\u003c/strong\u003e. \u003cem\u003eGlobal Change Biol\u0026nbsp;\u003c/em\u003e2023, \u003cstrong\u003e29\u003c/strong\u003e(16):4605-4619.\u003c/li\u003e\n \u003cli\u003eHewitt RE, Alexander HD, Miller SN, Mack MC: \u003cstrong\u003eRoot-associated fungi not tree density influences stand nitrogen dynamics at the larch forest-tundra ecotone\u003c/strong\u003e. \u003cem\u003eJ Ecol\u0026nbsp;\u003c/em\u003e2022, \u003cstrong\u003e110\u003c/strong\u003e(6):1419-1431.\u003c/li\u003e\n \u003cli\u003eHenriksson N, Lim H, Marshall J, Franklin O, McMurtrie RE, Lutter R, Magh R, Lundmark T, N\u0026auml;sholm T: \u003cstrong\u003eTree water uptake enhances nitrogen acquisition in a fertilized boreal forest - but not under nitrogen-poor conditions\u003c/strong\u003e. \u003cem\u003eNew Phytol\u0026nbsp;\u003c/em\u003e2021, \u003cstrong\u003e232\u003c/strong\u003e(1):113-122.\u003c/li\u003e\n \u003cli\u003eJohnson DW, Turner J: \u003cstrong\u003eNutrient cycling in forests: a historical look and newer developments\u003c/strong\u003e. \u003cem\u003eFor Ecol Manag\u0026nbsp;\u003c/em\u003e2019, \u003cstrong\u003e444\u003c/strong\u003e:344-373.\u003c/li\u003e\n \u003cli\u003eZheng P, Zhao RA, Jiang LC, Yang GJ, Wang YL, Wang RZ, Han XG, Ning QS: \u003cstrong\u003eIncreasing nitrogen addition rates suppressed long-term litter decomposition in a temperate meadow steppe\u003c/strong\u003e. \u003cem\u003eJ Plant Ecol\u0026nbsp;\u003c/em\u003e2023, \u003cstrong\u003e16\u003c/strong\u003e(3):rtac078.\u003c/li\u003e\n \u003cli\u003eGao JB, Zhou WJ, Liu YT, Sha LQ, Song QH, Lin YX, Yu GR, Zhang JH, Zheng XH, Fang YT\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eLitter-derived nitrogen reduces methane uptake in tropical rainforest soils\u003c/strong\u003e. \u003cem\u003eSci Total Environ\u0026nbsp;\u003c/em\u003e2022, \u003cstrong\u003e849\u003c/strong\u003e:157891.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Nutrient recycling, Nitrogen use efficiency, Larch plantation, Stand age, Supply-demand balance, Plant-soil interactions","lastPublishedDoi":"10.21203/rs.3.rs-9084654/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9084654/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNitrogen (N) often constrains forest productivity; however, how N-use strategies and the ecosystem N balance are reorganized during stand development remains poorly understood in cold-temperate plantations. In this study, N stocks and key fluxes were quantified across vegetation, litter, and soil in larch (\u003cem\u003eLarix principis-rupprechtii\u003c/em\u003e) plantations with four stand ages (11, 23, 37, and 47 years) in northern China. Age-related shifts in N-use strategies were evaluated, and piecewise structural equation modeling (pSEM) was applied to identify pathways linking stand age to ecosystem N cycling. The results showed that vegetation biomass and N stocks were found to increase significantly with stand age, whereas ecosystem N storage was dominated by soil (\u0026gt;\u0026thinsp;87%) across all stand ages. Soil available N supply was consistently larger than annual plant N uptake, indicating no evidence of N limitation during stand development. An age-dependent shift was observed from a resource-acquisitive strategy in young stands, characterized by stronger reliance on soil N acquisition, to a resource-conservative strategy in older stands, characterized by increased litter return and enhanced plant N resorption. N use efficiency was maximized at the mid-aged stage (37 years). Ecosystem N uptake and cycling were indirectly regulated by stand age through its effects on N status in plants, litter, and soil. Overall, a relatively stable balance between N supply and demand was maintained throughout stand development, and an increasingly internal cycling-dominated nutrient-use strategy was formed. These findings highlight the importance of stand age-mediated N nutritional strategies in sustaining larch plantation productivity.\u003c/p\u003e","manuscriptTitle":"Stand development shifts nitrogen cycling strategies and supply-demand balance in larch plantations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-08 14:20:29","doi":"10.21203/rs.3.rs-9084654/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-14T05:14:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T09:01:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T07:35:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T15:45:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316334168205144733081077522430932882580","date":"2026-05-05T06:06:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46104175245111636339182692399765424897","date":"2026-05-01T12:32:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"14127011279535069458310707439688119403","date":"2026-04-30T06:56:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-30T02:52:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-26T07:34:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-26T07:32:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-25T14:09:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2026-03-25T14:00:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2fd5b91c-009f-4333-96e6-18fc6f6791f2","owner":[],"postedDate":"May 8th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-14T05:14:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T09:01:38+00:00","index":80,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T07:35:39+00:00","index":79,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T15:45:55+00:00","index":78,"fulltext":""},{"type":"reviewerAgreed","content":"316334168205144733081077522430932882580","date":"2026-05-05T06:06:21+00:00","index":76,"fulltext":""},{"type":"reviewerAgreed","content":"46104175245111636339182692399765424897","date":"2026-05-01T12:32:46+00:00","index":70,"fulltext":""},{"type":"reviewerAgreed","content":"14127011279535069458310707439688119403","date":"2026-04-30T06:56:42+00:00","index":66,"fulltext":""},{"type":"reviewersInvited","content":"29","date":"2026-04-30T02:52:06+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T05:25:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-08 14:20:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9084654","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9084654","identity":"rs-9084654","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}