Background and Aims The form-function linkages and variation of fine root traits reflect adaptive strategies to cope with complex soil environments. However, their contributions to the root economics spectrum (RES) remain unclear. Methods We measured thirteen functional traits in the first four root orders of 59 subtropical woody species, including four morphology functional traits, three chemical functional traits, and six anatomical functional traits. Results A multi-dimensional RES was observed among the different order roots, including two trade-off axes, one represented by root diameter (RD) and specific root length (SRL) and another represented by root tissue density (RTD) and root nitrogen content (RNC). As the root orders increased, the root function transitioned from nutrient uptake (1st-3rd orders) to resource transport and storage (4th order). The hub traits changed accordingly. The intraspecific variation among root orders was along the RD-SRL axis, whereas the interspecific variation among the root orders was along the RTD-RNC axis in the RES. Furthermore, the data pertaining to plant life history strategies (e.g., leaf size and leaf nitrogen) had effects on the multi-dimensional RES variation. Conclusions Collectively, a multi-dimensional RES reveals intra- and interspecific variation characteristics in the fine root system. These findings provide empirical data underpinning a theoretical basis for understanding fine root form-function linkages.

Leaf respiration in the light (Rlight) is crucial for understanding the net CO2 exchange of individual plants and entire ecosystems. However, Rlight is poorly quantified and rarely discussed in the context of the leaf economic spectrum (LES), especially among woody species differing in plant functional types (PFTs) (e.g., evergreen vs. deciduous species). To address this gap in our knowledge, Rlight, respiration in the dark (Rdark), light-saturated photosynthetic rates (Asat), leaf dry mass per unit area (LMA), leaf nitrogen (N) and phosphorus (P) concentrations, and maximum carboxylation (Vcmax) and electron transport rates (Jmax) of 54 representative subtropical woody evergreen and deciduous species were measured. With the exception of LMA, the parameters quantified in this study were significantly higher in deciduous species than in evergreen species. The degree of light inhibition did not significantly differ between evergreen (52%) and deciduous (50%) species. Rlight was significantly correlated with LES traits such as Asat, Rdark, LMA, N and P. The Rlight vs. Rdark and N relationships shared common slopes between evergreen and deciduous species, but significantly differed in their y-intercepts, in which the rates of Rlight were slower or faster for any given Rdark or N in deciduous species, respectively. A model for Rlight based on three traits (i.e., Rdark, LMA and P) had an explanatory power of 84.9%. These results show that there is a link between Rlight and the LES, and highlight that PFTs is an important factor in affecting Rlight and the relationships of Rlight with Rdark and N. Thus, this study provides information that can improve the next generation of terrestrial biosphere models (TBMs).

China has been a major carbon dioxide emitter. According to the World Energy Statistics Yearbook 2021 published by British Petroleum (BP), China's total carbon emissions in 2020 were 9.899 billion tons, accounting for 30.7% of the world's total emissions and ranking first in the world. Promoting digital economy construction, new‐type urbanization construction and carbon emissions reduction is the focus of the Chinese government. Based on the decoupling model and threshold regression model, this article empirically tests the impact of digital economy and new‐type urbanization on carbon emissions by panel data from 2013–2019 in 30 provinces of China. The results show that there are 23 provinces of China having a better decoupling relationship between digital economy and carbon emissions reduction, and 20 provinces of China having a better decoupling relationship between new‐type urbanization and carbon emissions reduction. In the threshold regression models with energy intensity as the threshold variable, the digital economy has a significant threshold characteristic with a negative non‐linear effect on per capita carbon emissions. The new‐type urbanization also had a significant threshold characteristic with a two‐way non‐linear effect on per capita carbon emissions, but the negative effect is not significant. This means that, during the sample period, the improvement of China's digital economy level can effectively promote carbon emissions reduction. However, the improvement of the new‐type urbanization level curbs carbon emissions reduction.

Rising temperatures pose a threat to the stability of climate regulation by carbon metabolism in subtropical forests. Although the effects of temperature on leaf carbon metabolism traits in sun-exposed leaves are well understood, there is limited knowledge about its impacts on shade leaves and the implications for ecosystem–climate feedbacks. In this study, we measured temperature response curves of photosynthesis and respiration for 62 woody species in summer (including both evergreen and deciduous species) and 20 evergreen species in winter. The aim was to uncover the temperature dependence of carbon metabolism in both sun and shade leaves in subtropical forests. Our findings reveal that shade had no significant effects on the mean optimum photosynthetic temperatures ( T Opt ) or temperature range ( T 90 ). However, there were decreases observed in mean stomatal conductance, mean area-based photosynthetic rates at T Opt and 25 °C, as well as mean area-based dark respiration rates at 25 °C in both evergreen and deciduous species. Moreover, the respiration–temperature sensitivity ( Q 10 ) of sun leaves was higher than that of shade leaves in winter, with the reverse being true in summer. Leaf economics spectrum traits, such as leaf mass per area, and leaf concentration of nitrogen and phosphorus across species, proved to be good predictors of T Opt , T 90 , mass-based photosynthetic rate at T Opt , and mass-based photosynthetic and respiration rate at 25 °C. However, Q 10 was poorly predicted by these leaf economics spectrum traits except for shade leaves in winter. Our results suggest that model estimates of carbon metabolism in multilayered subtropical forest canopies do not necessitate independent parameterization of T 90 and T Opt temperature responses in sun and shade leaves. Nevertheless, a deeper understanding and quantification of canopy variations in Q 10 responses to temperature are necessary to confirm the generality of temperature–carbon metabolism trait responses and enhance ecosystem model estimates of carbon dynamics under future climate warming.

Evergreen and deciduous species coexist in the subtropical forests in southeastern China. It has been suggested that phosphorus (P) is the main limiting nutrient in subtropical forests, and that evergreen and deciduous species adopt different carbon capture strategies to deal with this limitation. However, these hypotheses have not been examined empirically to a sufficient degree. In order to fill this knowledge gap, we measured leaf photosynthetic and respiration rates, and nutrient traits related to P-, nitrogen (N)- and carbon (C)-use efficiencies and resorption using 75 woody species (44 evergreen and 31 deciduous species) sampled in a subtropical forest. The photosynthetic N-use efficiency (PNUE), respiration rate per unit N and P (R-d,R-N and R-d,R-P, respectively) of the deciduous species were all significantly higher than those of evergreen species, but not in the case of photosynthetic P-use efficiency. These results indicate that, for any given leaf P, evergreen species manifest higher carbon-use efficiency (CUE) than deciduous species, a speculation that is empirically confirmed. In addition, no significant differences were observed between deciduous and evergreen species for nitrogen resorption efficiency, phosphorus resorption efficiency or N:P ratios. These results indicate that evergreen species coexist with deciduous species and maintain dominance in P-limited subtropical forests by maintaining CUE. Our results also indicate that it is important to compare the PNUE of deciduous species with evergreen species in other biomes. These observations provide insights into modeling community dynamics in subtropical forests, particularly in light of future climate change.

Background Breast cancer is known as one of the high-risk malignant tumors. Our previous studies have shown that computer-assisted quantification of large-scale tumor associated collagen signaling is an important prognostic indicator of breast cancer. However, the nonlinear relationship between the data has not been effectively mined, resulting in insufficient accuracy in prognosis prediction. Methods In this retrospective and multicenter study, we included 995 patients with invasive breast cancer and divided them into three cohorts, training cohort (N=438), internal validation cohort (N=293) and external validation cohort (N=264) respectively. Firstly, we used COX and random survival forest (SRF) to explore the significance of variables. And then we combined the survival models with machine learning into eight comprehensive machine survival models in order to improve the prognosis of breast cancer. Finally, 10 new survival indicators generated from the above models were used to classify patients into low risk and high risk under Kaplan-Meier method and Log-rank test. Result The baseline data and TACS of patients not only show their own non-linear, but also have a strong nonlinear complementary effect between them, and they even interact and promote each other. It is worth noting that the effect of the comprehensive machine survival models are better than that of the clinical model (CLI). Specifically, except SRF-2 does it best in the training cohort (AUC: 0.956 [0.904,0.973]), SRFNET has the best performance in the internal validation cohort (AUC: 0.961 [0.941,0.978]) and the external validation cohort (AUC: 0.935 [0.891,0.967]). Meanwhile, 10 new survival indicators generated from the above comprehensive machine survival models are not only significantly related to DFS, but also able to effectively distinguish high and low risk patients (P < 0.0001) based on the cutoff value of the 5-year time point. Conclusion The comprehensive machine survival models proposed in this paper improve the recurrence prediction accuracy of breast cancer patients by mining the nonlinearity between patients’ characteristic, so that we will provide effective tools and reliable basis for doctors to carry out precise treatment.

Cortex radius (CR) and stele radius (SR) are important functional traits associated with the nutrient acquisition and transport functions of fine roots, respectively. However, for developmental and anatomical reasons, the resource acquisition–transport relationship of fine roots is expected to be different for different root orders. To address this issue, critical fine root anatomical traits were examined for the first three orders of roots of 59 subtropical woody plants. Designating the most distal fine roots as order one, SR scaled isometrically with respect to root radius (RR) (i.e., SR ∝ RR 1.0 ) in the three root orders, whereas CR scaled allometrically with respect to RR (i.e., CR ∝ RR >1.0 ) with the numerical values of scaling exponents increasing significantly with increasing root orders thereby indicating a disproportional increase in CR with increasing root orders. There were also differences between normalized root tissue (CR/RR and SR/RR) and RR in different root orders. A negative isometric relationship (i.e., SR/RR ∝ RR −1.0 ) existed between SR/RR and RR in three order roots, whereas the allometric exponent between CR/RR and RR increased with root order (from 0.88 to 1.55). Collectively, the data indicate that root anatomical and functional traits change as a function of RR and that these changes need to be considered when modeling fine root resource acquisition–transport functions.

The purpose of this paper is to quantify the level of new-type urbanization and unravel the spatial and nonlinear effects of new-type urbanization and technological innovation on industrial carbon emissions. Although the impact of traditional urbanization levels on carbon emissions has been widely studied, there is still a huge room for optimization, and the impact of new-type urbanization on carbon emissions has not yet been clarified. Selecting 37 cities in the Yangtze River Delta as a research sample, this paper measures the new-type urbanization based on an evaluation system we build. Consequently, we assess the spatial and nonlinear effects of new-type urbanization and technological innovation on carbon emissions by the spatial Durbin model and non-parameter addictive model, respectively. The results indicate that the new-type urbanization and low-carbon city pilot policy have significant spatial spillover effects on reducing carbon dioxide emissions, while the economic growth plays a positive role in increasing carbon emission. As for nonlinear effects, there is a significant inverted "N"-shaped relationship between the level of new-type urbanization and carbon dioxide emissions, while the nexus between technological innovation and carbon emissions is an inverted "U"-shaped relationship. This paper provides a new perspective for confirming the mechanism of the new-type urbanization on carbon emissions. Meanwhile, these findings are of significance for the relevant authorities in China to develop appropriate policy in carbon dioxide emission reduction.

The whole‐plant economics spectrum (PES) refers to the trade‐offs among the many plant functional traits that are commonly used as indicators of major adaptive strategies, thereby providing insights into plant distributions, ecosystem processes and evolution. However, there are few studies of what may be called the whole‐PES that integrates bark, wood and leaf functional traits for different leaf types and growth habits (evergreen vs. deciduous species). To address this gap in our knowledge, 6 bark traits, 7 wood traits (including mechanical support and nutrient transport characteristics) and 12 leaf traits (including chemical, structural and physiological characteristics) of 59 representative subtropical woody species were examined using principal component analysis (PCA) to determine PES strategies. The economics spectra of bark (BES), wood (WES) and leaves (LES), and the entire PES indicated that major traits represent resource acquisition strategies and conservation strategies clustering on the opposite ends of the PCA axis. A significant correlation was observed among the 25 functional traits. The data indicated that N and P nutrient levels were at the hub of BES, WES, LES and PES interrelationships. Evergreen and deciduous species had different WES and LES, and thus PES resource acquisition strategies. With the exception of the BES, evergreen species clustered on the conservative side, whereas deciduous species clustered on the acquisitive side. Synthesis . The PES presented here informs our understanding of whole‐plant responses to environmental differences, particularly regarding the role of N and P traits at the whole‐plant level. It also reveals and further supports the notion that evergreen and deciduous species, respectively, manifest conservative and acquisitive strategies, further informing our understanding of species biodiversity maintenance.

ObjectThis study attempted to explore the effects of vaccination on disease severity and the factors for viral clearance and hospitalization in omicron-infected patients.MethodsThe clinical manifestations of 3,265 Omicron-infected patients (BA.2 lineage variant; the Omicron group) were compared with those of 226 Delta-infected patients (the Delta group). A Multi-class logistic regression model was employed to analyze the impacts of vaccination doses and intervals on disease severity; a logistic regression model to evaluate the risk factors for hospitalization; R 4.1.2 data analysis to investigate the factors for time for nucleic acid negativization (NAN).ResultsCompared with the Delta group, the Omicron group reported a fast transmission, mild symptoms, and lower severity incidence, and a significant inverse correlation of vaccination dose with clinical severity (OR: 0.803, 95%CI: 0.742-0.868, p<0.001). Of the 7 or 5 categories of vaccination status, the risk of severity significantly decreased only at ≥21 days after three doses (OR: 0.618, 95% CI: 0.475-0.803, p<0.001; OR: 0.627, 95% CI: 0.482-0.815, p<0.001, respectively). The Omicron group also reported underlying illness as an independent factor for hospitalization, sore throat as a protective factor, and much shorter time for NAN [15 (12,19) vs. 16 (12,22), p<0.05]. NAN was associated positively with age, female gender, fever, cough, and disease severity, but negatively with vaccination doses.ConclusionBooster vaccination should be advocated for COVID-19 pandemic-related control and prevention policies and adequate precautions should be taken for patients with underlying conditions.

The plant economics spectrum describes the trade-off between plant resource acquisition and storage, and sheds light on plant responses to environmental changes. However, the data used to construct the plant economics spectrum comes mainly from seed plants, thereby neglecting vascular non-seed plant lineages such as the ferns. To address this omission, we evaluated whether a fern economics spectrum exists using leaf and root traits of 23 fern species living under three subtropical forest conditions differing in light intensity and nutrient gradients. The fern leaf and root traits were found to be highly correlated and formed a plant economics spectrum. Specific leaf mass and root tissue density were found to be on one side of the spectrum (conservative strategy), whereas photosynthesis rate, specific root area, and specific root length were on the other side of the spectrum (acquisitive strategy). Ferns had higher photosynthesis and respiration rates, and photosynthetic nitrogen-use efficiency under high light conditions and higher specific root area and lower root tissue density in high nutrient environments. However, environmental changes did not significantly affect their resource acquisition strategies. Thus, the plant economics spectrum can be broadened to include ferns, which expands its phylogenetic and ecological implications and utility.

Introduction : To determine whether the patterns of extracranial metastasis (ECMs) provide supplementary prognositc information to DS-GPA in elderly NSCLC patients with synchronous BM. Methods : This study included 4974 NSCLC patients with initial BM diagnosed from 2010 to 2015 using the Surveillance Epidemiology and End Results (SEER) program. Patients were divided randomly into training and hold-out test sets. Patterns of ECMs were established based on the difference of survival via competing risk analysis in the training set. A nomogram prediction of 6-month, 12-month, and 18-month disease-specific survival (DSS) was built using independent prognostic factors. Results : Three patterns of ECM were recognized: MA (neither liver, bone, nor lung involvement), MB (without liver involvement), and MC (with liver involvement). Comparing MA, MB and MC showed significant correlation to survival (SHR, 1.126, 95% CI, 1.053-1.205, P<0.001; SHR, 1.46, 95% CI, 1.339-1.592, P<0.001, respectively). In the hold-out test set, the AUC of the ROC curve for the 6-month DSS prediction reached 0.778, whereas reaching 0.757 in the training set. The calibration curves did not deviate from the reference line. Decision curve analyses revealed the net benefit of the nomogram for clinical utility. Conclusions : These results help clinicians make decisions for brain-metastatic NSCLC in the era of precision therapy. The risk stratification of extracranial involvements indicates differential treatment for elderly NSCLC patients with synchronous brain-metastasis.

Background and purpose We aimed to explore the necessity of the external iliac lymph nodes (EIN) along with inguinal nodes (IN) region in clinical target volume (CTV) for rectal carcinomas covering the anal canal region. Materials and methods This research premise enrolled 399 patients who had primary low rectal cancer detected below the peritoneal reflection via magnetic resonance imaging (MRI) and were treated with neoadjuvant radiotherapy (NRT), without elective EIN along with IN irradiation. We stratified the patients into two groups based on whether the lower edge of the rectal tumor extended to the anal canal (P group, n = 109) or not (Rb group, n = 290). Comparison of overall survival (OS), locoregional recurrence-free survival (LRFS), disease-free survival (DFS), as well as distant metastasis-free survival (DMFS) were performed via inverse probability of treatment weighting (IPTW) along with multivariable analyses. We compared the EIN and IN failure rates between the two groups via the Fisher and Gray’s test. Results P group showed a similar adjusted proportion along with five-year cumulative rate of EIN failure compared with the Rb group. The adjusted proportion and five-year cumulative rate of IN failure in the P group was higher in comparison to the Rb group. There were no remarkable differences in the adjusted five-year OS, DFS, DMFS or LRFS between the two groups. Anal canal involvement (ACI) exhibited no effect on OS, LRFS, DFS, or DMFS. Conclusions During NRT for rectal cancer with ACI, it may be possible to exclude the EIN and IN from the CTV.

以中国大陆30个省区为研究对象,基于2013～2019年各省区人均CO2排放及相关影响因素数据,运用多尺度地理加权回归方法,分析中国省域人均CO2排放影响因素的空间异质性.结果表明:(1)人均CO2排放影响因素的空间作用尺度不同.能源强度的空间作用尺度是所有因素中最小的,其空间作用尺度为45.而第三产业增加值与第二产业增加值比值的空间作用尺度是最大的,其空间作用尺度为94.其它因素的空间作用尺度由小到大分别为新型城镇化指数、人均社会消费品总额、人均固定资产投资额、数字经济指数.(2)所有影响因素中能源强度是影响人均CO2排放的最主要因素,其次是新型城镇化指数.(3)新型城镇化指数、能源强度均正向影响人均CO2排放,而其它因素对人均CO2排放的影响是双向的,且各因素正向作用和负向作用占总样本的比例不相同.

Comprehensive studies on the response of whole plant functional traits to nitrogen deposition can provide insight into the resource acquisition strategies of plants. However, current studies on nitrogen deposition have mainly focused on leaves or roots. We conducted nitrogen deposition simulation experiments with Machilus pauhoi (Lauraceae) from five provenances in a common garden experiment in the southeast of China. We measured 29 traits (biomass, phenology traits, and nutrient concentrations) of leaves, stems, and roots in response to nitrogen addition and selected 26 distinct important functional traits related to resource acquisition strategies of the whole M. pauhoi seedlings. We found that N (Nitrogen) addition significantly increased the biomass of M. pauhoi seedlings and altered biomass allocation among organs. The response of the leaf, stem and root traits to nitrogen addition was not always consistent among the different provenances of M. pauhoi seedlings. A uniform variation pattern of the three organs was found in the C (Carbon) and P (Phosphorus) concentrations, as well as N:P ratio. In contrast, N concentration, the C:N ratio and the phenotypic trait specific leaf area (SLA) and specific root area (SRL) did not respond in the same direction at the organ level. We concluded that nitrogen addition alters the biomass allocation pattern of M. pauhoi and the resource acquisition capacity of above- and below-ground organs. N concentrations and C:N ratio may play a key role in this regulatory process. Overall, N addition increased leaf mass fraction (LMF) and SRL, and instead decreased SLA and root mass fraction (RMF) of M. pauhoi. There are also differences in biomass allocation and resource acquisition patterns between the different provenances. AF and SC seedlings can be preferred provenances for M. pauhoi due to their balanced resource acquisition strategy and high phenotypic plasticity, respectively. Our study may contribute to a more comprehensive understanding of how N deposition affects the plant as a whole and provide a theoretical basis for precise nutrient management of M. pauhoi seedlings and their plantations in the context of nitrogen deposition.

Climate change could negatively alter plant ecosystems if rising temperatures exceed optimal conditions for obtaining carbon. The acclimation of plants to higher temperatures could mitigate this effect, but the potential of subtropical forests to acclimate still requires elucidation. We used space-for-time substitution to determine the photosynthetic and respiratory-temperature response curves, optimal temperature of photosynthesis (Topt), photosynthetic rate at Topt, temperature sensitivity (Q10), and the rate of respiration at a standard temperature of 25°C (R25) for Pinus taiwanensis at five elevations (1200, 1400, 1600, 1800, and 2000 m) in two seasons (summer and winter) in the Wuyi Mountains in China. The response of photosynthesis in P. taiwanensis leaves to temperature at the five elevations followed parabolic curves, and the response of respiration to temperature increased with temperature. Topt was higher in summer than winter at each elevation and decreased significantly with increasing elevation. Q10 decreased significantly with increasing elevation in summer but not winter. These results showed a strong thermal acclimation of foliar photosynthesis and respiration to current temperatures across elevations and seasons, and that R25 increased significantly with elevation and were higher in winter than summer at each elevation indicating that the global warming can decrease R25. These results strongly suggest that this thermal acclimation will likely occur in the coming decades under climate change, so the increase in respiration rates of P. taiwanensis in response to climatic warming may be smaller than predicted and thus may not increase atmospheric CO2 concentrations.

Background It is critical to accurately identify patients with severe acute pancreatitis (SAP) and moderately SAP (MSAP) in a timely manner. The study was done to establish two early multi-indicator prediction models of MSAP and SAP. Methods Clinical data of 469 patients with acute pancreatitis (AP) between 2015 and 2020, at the First Affiliated Hospital of Fujian Medical University, and between 2012 and 2020, at the Affiliated Union Hospital of Fujian Medical University, were retrospectively analyzed. The unweighted predictive score (unwScore) and weighted predictive score (wScore) for MSAP and SAP were derived using logistic regression analysis and were compared with four existing systems using receiver operating characteristic curves. Results Seven prognostic indicators were selected for incorporation into models, including white blood cell count, lactate dehydrogenase, C-reactive protein, triglyceride, D-dimer, serum potassium, and serum calcium. The cut-offs of the unwScore and wScore for predicting severity were set as 3 points and 0.513 points, respectively. The unwScore (AUC = 0.854) and wScore (AUC = 0.837) were superior to the acute physiology and chronic health evaluation II score (AUC = 0.526), the bedside index for severity in AP score (AUC = 0.766), and the Ranson score (AUC = 0.693) in predicting MSAP and SAP, which were equivalent to the modified computed tomography severity index score (AUC = 0.823). Conclusions The unwScore and wScore have good predictive value for MSAP and SAP, which could provide a valuable clinical reference for management and treatment.

ObjectiveThe objective of this study is to investigate the predictive value of a parametric model constructed by using procalcitonin, C-reactive protein (CRP) and D dimer within 48 h after admission in moderately severe and severe acute pancreatitis.MethodsA total of 238 patients were enrolled, of which 170 patients were moderately severe and severe acute pancreatitis (MSAP+SAP). The concentrations of procalcitonin, CRP and D dimer within 48 h after admission were obtained. The predictive value of the parametric model, modified computed tomography severity index (MCTSI), bedside index for severity in acute pancreatitis (BISAP), Ranson score, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, modified Marshall score and systemic inflammatory response syndrome (SIRS) score of all patients was calculated and compared.ResultsThe area under receiver operator characteristic curve, sensitivity, specificity, Youden index and critical value of the parametric model for predicting MSAP+SAP were 0.853 (95% CI, 0.804-0.903), 84.71%, 70.59%, 55.30% and 0.2833, respectively. The sensitivity of the parametric model was higher than that of MCTSI (84.00%), Ranson score (73.53%), BISAP (56.47%), APACHE II score (27.65%), modified Marshall score (17.06%) and SIRS score (78.24%); the specificity of it were higher than that of MCTSI (52.94%) and Ranson score (67.65%), but lower than BISAP (73.53%), APACHE II score (76.47%), modified Marshall score (100%)and SIRS score (100.00%).ConclusionThe parametric model constructed by using procalcitonin 48 h, CRP 48 h and D dimer 48 h can be regarded as an evaluation model for predicting moderately severe and severe acute pancreatitis.

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[目的]研究阔叶树不同冠层高度对当年生小枝上单叶生物量与出叶强度之间关系的影响,以期探明森林内光照环境变化对树木小枝性状的影响,为揭示阔叶树林冠生长对光环境变化的响应机制提供理论依据.[方法]采用标准化主轴回归估计(standardized major axis estimation,SMA)方法对江西省阳际峰自然保护区内69种阔叶树不同冠层高度的单叶生物量(ILM)与出叶强度(单位茎生物量的叶片数量与单位茎体积的叶片数量,Lim与Liv)的异速生长关系(树木本身某一部分的相对增长)进行研究,分析不同冠层高度(上冠层与下冠层)对亚热带常绿阔叶林内常绿和落叶树种的单叶生物量与出叶强度之间关系的影响.[结果]1)常绿和落叶树种的Liv、比叶面积和单叶面积均存在显著差异(P<0.05),但两者的叶片数量、ILM、Lim和茎密度均无显著差异(P>0.05).常绿树种在不同冠层高度处的叶片数量、Liv、比叶面积、Lim和茎密度均存在显著差异(P<0.05),但落叶树种在不同冠层高度处仅与比叶面积存在显著差异(P<0.05).2)常绿和落叶树种不同冠层高度当年生小枝的单叶生物量与出叶强度之间均为负等速关系;冠层高度对常绿树种小枝ILM-Lim的异速生长指数(方程斜率)无显著影响(P=0.95),但上冠层小枝ILM-Lim的异速生长常数(方程截距)显著高于下冠层(分别为1.24、1.05);冠层高度对落叶树种当年生小枝ILM-Lim的异速生长指数(P=0.65)与异速生长常数(P=0.83)均无显著影响.3)冠层高度对常绿树种当年生小枝ILM-Liv的异速生长指数(P=0.43)与异速生长常数(P=0.16)均无显著影响,对落叶树种当年生小枝ILM-Liv的异速生长指数(P=0.69)与异速生长常数(P=0.28)也无显著影响.[结论]冠层高度对常绿和落叶树种当年生小枝的单叶生物量与出叶强度之间的负等速关系未产生影响,但冠层高度对常绿树种的异速生长常数则产生显著影响,表明在一定的出叶强度下,上冠层具有更高的单叶生物量,这可能是受当年生小枝在不同冠层高度处的枝、叶资源获取策略不同所引起.