基于背包LiDAR的半湿润常绿阔叶林及其常见树种的垂直结构特征

doi:10.17520/biods.2023216

生物多样性 ›› 2023, Vol. 31 ›› Issue (11): 23216. DOI: 10.17520/biods.2023216

• 半湿润常绿阔叶林专题 • 上一篇下一篇

基于背包LiDAR的半湿润常绿阔叶林及其常见树种的垂直结构特征

饶杰生¹, 杨涛¹, 田希¹, 刘文聪¹, 王晓凤¹, 钱恒君¹, 沈泽昊¹^,²^,^*()

1.云南大学生态与环境学院, 昆明 650091
2.北京大学城市与环境学院, 北京大学地表过程分析与模拟教育部重点实验室, 北京 100871

收稿日期:2023-06-25 接受日期:2023-08-24 出版日期:2023-11-20 发布日期:2023-09-18
通讯作者: * E-mail: shzh@urban.pku.edu.cn
基金资助:
云南省科技厅-云南大学双一流学科建设重大专项(2018FY001-002);云南省基础研究计划重大项目课题(202101BC07 0002)

Vertical structural characteristics of a semi-humid evergreen broad-leaved forest and common tree species based on a portable backpack LiDAR

Jiesheng Rao¹, Tao Yang¹, Xi Tian¹, Wencong Liu¹, Xiaofeng Wang¹, Hengjun Qian¹, Zehao Shen¹^,²^,^*()

1 School of Ecology and Environmental Science, Yunnan University, Kunming 650091
2 Key Laboratory of MOE for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871

Received:2023-06-25 Accepted:2023-08-24 Online:2023-11-20 Published:2023-09-18
Contact: * E-mail: shzh@urban.pku.edu.cn

摘要/Abstract

摘要：

森林的垂直结构是地上植被要素在垂直方向上的排列, 它影响动植物多样性和生态系统功能, 是许多植物生态学家关注的重点。背包激光雷达技术的发展为大面积、高精度扫描三维森林结构提供了基础。直观反映生物量的冠层高度(canopy height, CH)、代表植物光合能力的叶面积指数(leaf area index, LAI)和单木尺度上的特征是森林垂直结构最重要的参数。本研究旨在探索鸡足山半湿润常绿阔叶林样地尺度和单木尺度上的垂直结构特征。本研究基于背包激光雷达, 对滇中高原20.16 ha半湿润常绿阔叶林样地群落的CH和LAI进行了精细扫描和点云定量分析, 在进行地形校正和群落分类的基础上, 精细提取和分析了森林群落的叶面积指数的垂直变化和水平格局, 并定量提取了群落常见乔木种的单木形态和垂直结构参数。结果显示: (1)以20 m × 20 m标准样方为统计单位的CH和LAI的分布接近正态分布; (2)根据LAI的垂直分布, 森林动态监测样地群落冠层由上至下可划分为林冠上层、林冠中层、林冠下层与灌木层4个层次; (3)元江栲(Castanopsis orthacantha)和高山栲(C. delavayi)群落的LAI垂直变化呈单峰格局, 峰值高度分别为15 m和13 m, 云南松(Pinus yunnanensis)群落为双峰格局, 峰值高度为5 m和10 m; (4)不同树种的各单木参数表现出较大的差异性, 但冠幅面积/胸径比表现出相对的稳定性。本研究在国内首次基于激光雷达技术定量分析具有复杂结构的半湿润常绿阔叶林的叶面积指数的三维格局, 或可对以后该类型森林生物多样性的研究和不同森林类型之间的比较研究提供数据基础。

关键词: 半湿润常绿阔叶林, 垂直结构, 叶面积指数, 冠层高度, 背包激光雷达, 单木

Abstract

Background & AimsThe vertical structure of a forest is the vertical arrangement of aboveground vegetation elements. This feature of the forest affects plant and animal diversity and ecosystem function, and thus has been the focus of many plant ecologists. The development of portable backpack LiDAR technology allows for scanning of 3D forest structure over a large area with high precision. The purpose of this study is to explore the vertical structural characteristics of the semi-humid evergreen broad-leaved forest in Jizu Mountains on the scale of plot and individual tree.

Methods: The most important parameters of the vertical forest structure are: the canopy height (CH), the leaf area index (LAI), and the characteristics of individual tree. The CH directly reflects the biomass and the LAI represents photosynthetic capacity of plants. Based on a portable backpack LiDAR, the CH and LAI of a 20.16 ha semi-humid evergreen broad-leaved forest dynamics plot in the Central Yunnan Plateau were carefully scanned and quantitatively analyzed. On the basis of topographic correction and community classification, the vertical change and horizontal pattern of the LAI of the forest community were extracted and analyzed, and the parameters of single tree morphology and vertical structure of common tree species were surveyed quantitatively.

Results: The results showed that: (1) the distribution of CH and LAI in a 20 m × 20 m square was close to a normal distribution; (2) according to the vertical distribution of LAI, the canopy of the large plot can be divided into four layers: the upper canopy, the middle canopy, the lower canopy, and the shrub layer; (3) the vertical variation of LAI of the Castanopsis orthacantha community and the C. delavayi community showed a single-peak pattern with peak heights of 15 m and 13 m, respectively, and that of the Pinus yunnanensis community showed a double-peak pattern with peak heights of 5 m and 10 m; (4) the parameters of different tree species showed great variation, but the value of crown area/diameter was relatively uniform.

Conclusion This is the first study in China to quantitatively analyze a 3D pattern of LAI for a semi-humid evergreen broad-leaved forest with a complex structure based on LiDAR technology. This work may provide a useful database for future studies of forest biodiversity of this type and for comparative studies between different forest types.

Key words: semi-humid evergreen broad-leaved forest, vertical structure, leaf area index, canopy height, the portable backpack LiDAR, individual tree

饶杰生, 杨涛, 田希, 刘文聪, 王晓凤, 钱恒君, 沈泽昊 (2023) 基于背包LiDAR的半湿润常绿阔叶林及其常见树种的垂直结构特征. 生物多样性, 31, 23216. DOI: 10.17520/biods.2023216.

Jiesheng Rao, Tao Yang, Xi Tian, Wencong Liu, Xiaofeng Wang, Hengjun Qian, Zehao Shen (2023) Vertical structural characteristics of a semi-humid evergreen broad-leaved forest and common tree species based on a portable backpack LiDAR. Biodiversity Science, 31, 23216. DOI: 10.17520/biods.2023216.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2023216

https://www.biodiversity-science.net/CN/Y2023/V31/I11/23216

图/表 8

图1 鸡足山20.16 ha森林动态监测样地林冠无人机扫描图(部分)

Fig. 1 Unmanned aerial vehicle scaned image (part) of the canopy of the 20.16 ha forest dynamics plot in Jizu Mountains, Yunnan

图2 树木位置测量示意图(辅助杆是竖直的)

Fig. 2 Schematic diagram of tree positioning (The auxiliary rod is vertical)

图3 点云数据获取。(a)样方扫描路径示意图; (b)点云中的定位桩; (c)现实中的定位桩。

Fig. 3 Point cloud data acquisition. (a) A sketch of the sample scan path; (b) The positioning piles in point clouds; (c) The positioning pile in reality.

图4 激光雷达点云示意图。(a)地形归一化前样方点云剖面图; (b)地形归一化后样方点云剖面图; (c)样地森林群落三维点云图。

Fig. 4 Schematic diagram of LiDAR point cloud. (a) Sample point cloud profile before terrain normalization; (b) Sample point cloud profile after terrain normalization; (c) 3D point cloud map of forest community in the forest dynamics plot.

图5 鸡足山20.16 ha森林动态监测样地森林群落的冠层高度水平格局和频数分布。(a)分辨率1 m的冠层高度; (b)样方冠层高度分布直方图(平均值为15.84 m)。

Fig. 5 Spatial pattern and histogram of the canopy height (CH) in the 20.16 ha forest dynamics plot in Jizu Mountains, Yunnan. (a) The horizontal pattern of CH with a 1-m spatial resolution; (b) A histogram of frequency distribution of the CH (mean = 15.84 m) in a grid.

图6 鸡足山20.16 ha森林动态监测样地叶面积指数的水平格局和频率分布。(a)样方尺度的叶面积指数与森林动态监测样地地形叠加图, 绿色圆越大表示LAI越大; (b)叶面积指数频率分布直方图(平均值为8.63)。

Fig. 6 Horizontal pattern and frequency distribution of leaf area index (LAI) of 20.16 ha forest dynamics plot in Jizu Mountains, Yunnan. (a) Overlay map of LAI of each plot and DEM of the forest dynamics plot, and the bigger the green circle, the greater the LAI; (b) Histogram of LAI frequency distribution (mean = 8.63).

图7 鸡足山20.16 ha森林动态监测样地中3个群落类型的叶面积指数的垂直变化

Fig. 7 Vertical variation of leaf area index (LAI) of three community types (Pinus yunnanensis community, Castanopsis delavayi community, and C. orthacantha community) in a 20.16 ha forest dynamics plot in Jizu Mountains, Yunnan.

表1 鸡足山20.16 ha森林动态监测样地12种常见乔木植物形态结构参数

Table 1 Morphological and structural parameters of 12 of common trees species in a 20.16 ha forest dynamics plot in Jizu Mountains, Yunnan

物种 Species	生活型 Life form	胸径 Diameter at breast height (DBH) (cm)	树高 Tree height (TH) (m)	枝下高 Crown base height (CBH) (m)	树冠直径 Crown diameter (m)	冠幅面积 Crown area (CA) (m2)	枝下高/树高 CBH/TH (%)	冠幅/胸径 CA/DBH (m2/cm)
元江栲 Castanopsis orthacantha	EBT	89.3 (47%)	22.6 (16%)	5.7 (21%)	12.3 (38%)	133.4 (65%)	25.2 (11%)	1.39 (13%)
高山栲 Castanopsis delavayi	EBT	61.6 (33%)	21.1 (21%)	6.7 (44%)	10.7 (24%)	93.9 (48%)	30.6 (21%)	1.51 (27%)
黄毛青冈 Cyclobalanopsis delavayi	EBT	59.0 (42%)	23.6 (13%)	9.2 (27%)	13.7 (38%)	163.9 (65%)	38.5 (20%)	2.54 (40%)
滇青冈 Cyclobalanopsis glaucoides	EBT	46.1 (53%)	20.2 (26%)	6.6 (17%)	8.8 (49%)	72.3 (104%)	34.1 (29%)	1.34 (45%)
白穗石栎 Lithocarpus leucostachyus	EBT	56.1 (26%)	21.3 (3%)	8.6 (26%)	9.6 (20%)	74.1 (37%)	40.1 (26%)	1.31 (27%)
银木荷 Schima argentea	EBT	35.4 (12%)	25.6 (10%)	14.0 (36%)	7.7 (22%)	47.9 (49%)	54.2 (31%)	1.45 (68%)
云南松 Pinus yunnanensis	ECT	43.6 (37%)	20.4 (10%)	10.4 (11%)	8.9 (26%)	65.0 (52%)	51.1 (13%)	1.44 (21%)
华山松 Pinus armandii	ECT	58.0 (27%)	22.9 (17%)	4.4 (33%)	9.2 (23%)	69.7 (46%)	19.6 (35%)	1.20 (32%)
尼泊尔桤木 Alnus nepalensis	DBT	37.3 (26%)	21.0 (19%)	8.8 (29%)	7.5 (23%)	45.8 (50%)	42.7 (27%)	1.19 (27%)
胡桃 Juglans regia	DBT	55.2 (20%)	30.6 (9%)	13.3 (20%)	14.3 (20%)	165.3 (44%)	43.8 (24%)	2.93 (24%)
头状四照花 Dendrobenthamia capitata	EBT	32.5 (27%)	18.7 (7%)	7.8 (20%)	7.7 (28%)	49.1 (58%)	42.0 (21%)	1.56 (23%)
野桂花 Osmanthus yunnanensis	EBT	30.5 (17%)	15.4 (18%)	4.2 (15%)	7.3 (25%)	44.1 (53%)	27.7 (20%)	1.59 (77%)

参考文献 36

[1]	Beland M, Parker G, Sparrow B, Harding D, Chasmer L, Phinn S, Antonarakis A, Strahler A (2019) On promoting the use of lidar systems in forest ecosystem research. Forest Ecology and Management, 450, 117484. DOI URL
[2]	Bonan GB (1993) Importance of leaf area index and forest type when estimating photosynthesis in boreal forests. Remote Sensing of Environment, 43, 303-314.
[3]	Bongers F (2001) Methods to assess tropical rain forest canopy structure: An overview. Plant Ecology, 153, 263-277. DOI URL
[4]	Cao Y, Wang DY, Wang ZW, Tian LJ, Zheng CG, Tian Y, Liu Y (2021) Research on tree pith location in radial direction based on terrestrial laser scanning. Forests, 12, 671. DOI URL
[5]	Chen JM, Black TA (1992) Defining leaf area index for non-flat leaves. Plant, Cell & Environment, 15, 421-429.
[6]	Dash J, Ogutu BO (2016) Recent advances in space-borne optical remote sensing systems for monitoring global terrestrial ecosystems. Progress in Physical Geography: Earth and Environment, 40, 322-351. DOI URL
[7]	De Pauw K, Sanczuk P, Meeussen C, Depauw L, De Lombaerde E, Govaert S, Vanneste T, Brunet J, Cousins SAO, Gasperini C, Hedwall PO, Iacopetti G, Lenoir J, Plue J, Selvi F, Spicher F, Uria-Diez J, Verheyen K, Vangansbeke P, De Frenne P (2022) Forest understorey communities respond strongly to light in interaction with forest structure, but not to microclimate warming. New Phytologist, 233, 219-235. DOI URL
[8]	Dixon SD, Worrall F, Rowson JG, Evans MG (2015) Calluna vulgaris canopy height and blanket peat CO₂ flux: Implications for management. Ecological Engineering, 75, 497-505. DOI URL
[9]	Ehbrecht M, Seidel D, Annighöfer P, Kreft H, Köhler M, Zemp DC, Puettmann K, Nilus R, Babweteera F, Willim K, Stiers M, Soto D, Boehmer HJ, Fisichelli N, Burnett M, Juday G, Stephens SL, Ammer C (2021) Global patterns and climatic controls of forest structural complexity. Nature Communi- cations, 12, 519.
[10]	Gui XJ, Lian JY, Zhang RY, Li YP, Shen H, Ni YL, Ye WH (2019) Vertical structure and its biodiversity in a subtropical evergreen broad-leaved forest at Dinghushan in Guangdong Province, China. Biodiversity Science, 27, 619-629. (in Chinese with English abstract) DOI URL
	[桂旭君, 练琚愉, 张入匀, 李艳朋, 沈浩, 倪云龙, 叶万辉 (2019) 鼎湖山南亚热带常绿阔叶林群落垂直结构及其物种多样性特征. 生物多样性, 27, 619-629.] DOI
[11]	Guo QH, Liu J, Tao SL, Xue BL, Li L, Xu GC, Li WK, Wu FF, Li YM, Chen LH, Pang SX (2014) Perspectives and prospects of LiDAR in forest ecosystem monitoring and modeling. Chinese Science Bulletin, 59, 459-479. (in Chinese with English abstract) DOI URL
	[郭庆华, 刘瑾, 陶胜利, 薛宝林, 李乐, 徐光彩, 李文楷, 吴芳芳, 李玉美, 陈琳海, 庞树鑫 (2014) 激光雷达在森林生态系统监测模拟中的应用现状与展望. 科学通报, 59, 459-479.]
[12]	Hosoi F, Omasa K (2007) Factors contributing to accuracy in the estimation of the woody canopy leaf area density profile using 3D portable lidar imaging. Journal of Experimental Botany, 58, 3463-3473. PMID
[13]	Kamoske AG, Dahlin KM, Stark SC, Serbin SP (2019) Leaf area density from airborne LiDAR: Comparing sensors and resolutions in a temperate broadleaf forest ecosystem. Forest Ecology and Management, 433, 364-375. DOI
[14]	Kumkar Y, Astrup R, Stordal F, Bright RM (2020) Quantifying regional surface energy responses to forest structural change in Nordic Fennoscandia. Journal of Geophysical Research: Atmospheres, 125, e2019JD032092. DOI URL
[15]	Kunz M, Fichtner A, Härdtle W, Raumonen P, Bruelheide H, von Oheimb G (2019) Neighbour species richness and local structural variability modulate aboveground allocation patterns and crown morphology of individual trees. Ecology Letters, 22, 2130-2140. DOI PMID
[16]	Lalic B, Mihailovic DT (2004) An empirical relation describing leaf-area density inside the forest for environmental modeling. Journal of Applied Meteorology, 43, 641-645. DOI URL
[17]	Lang AC, Härdtle W, Bruelheide H, Geißler C, Nadrowski K, Schuldt A, Yu MJ, von Oheimb G (2010) Tree morphology responds to neighbourhood competition and slope in species-rich forests of subtropical China. Forest Ecology and Management, 260, 1708-1715. DOI URL
[18]	Li YM, Guo QH, Tao SL, Zheng GA, Zhao KG, Xue BL, Su YJ (2016) Derivation, validation, and sensitivity analysis of terrestrial laser scanning-based leaf area index. Canadian Journal of Remote Sensing, 42, 719-729. DOI URL
[19]	Liu LX, Pang Y, Li ZY (2016) Individual tree DBH and height estimation using terrestrial laser scanning (TLS) in a subtropical forest. Scientia Silvae Sinicae, 52(2), 26-37. (in Chinese with English abstract)
	[刘鲁霞, 庞勇, 李增元 (2016) 基于地基激光雷达的亚热带森林单木胸径与树高提取. 林业科学, 52(2), 26-37.]
[20]	Liu XQ, Su YJ, Hu TY, Yang QL, Liu BB, Deng YF, Tang H, Tang ZY, Fang JY, Guo QH (2022) Neural network guided interpolation for mapping canopy height of China’s forests by integrating GEDI and ICESat-2 data. Remote Sensing of Environment, 269, 112844. DOI URL
[21]	Lou YK, Fan Y, Dai QL, Wang ZY, Ku WP, Zhao MS, Yu SQ (2021) Relationship between vertical structure and overall species diversity in an evergreen deciduous broad-leaved forest community of Tianmu Mountain Natural Reserve. Acta Ecologica Sinica, 41, 8568-8577. (in Chinese with English abstract)
	[楼一恺, 范忆, 戴其林, 王铮屹, 库伟鹏, 赵明水, 余树全 (2021) 天目山常绿落叶阔叶林群落垂直结构与群落整体物种多样性的关系. 生态学报, 41, 8568-8577.]
[22]	MacArthur RH, MacArthur JW (1961) On bird species diversity. Ecology, 42, 594-598. DOI URL
[23]	Parker GG, Russ ME (2004) The canopy surface and stand development: Assessing forest canopy structure and complexity with near-surface altimetry. Forest Ecology and Management, 189, 307-315. DOI URL
[24]	Potapov P, Li XY, Hernandez-Serna A, Tyukavina A, Hansen MC, Kommareddy A, Pickens A, Turubanova S, Tang H, Silva CE, Armston J, Dubayah R, Blair JB, Hofton M (2021) Mapping global forest canopy height through integration of GEDI and Landsat data. Remote Sensing of Environment, 253, 112165. DOI URL
[25]	Rasul A, Ibrahim S, Onojeghuo AR, Balzter H (2020) A trend analysis of leaf area index and land surface temperature and their relationship from global to local scale. Land, 9, 388. DOI URL
[26]	Simonson WD, Allen HD, Coomes DA (2014) Applications of airborne lidar for the assessment of animal species diversity. Methods in Ecology and Evolution, 5, 719-729. DOI URL
[27]	Soma M, Pimont F, Durrieu S, Dupuy JL (2018) Enhanced measurements of leaf area density with T-LiDAR: Evaluating and calibrating the effects of vegetation heterogeneity and scanner properties. Remote Sensing, 10, 1580. DOI URL
[28]	Suzuki T, Shiozawa S, Yamaba A, Amano Y, Japan WUT (2021) Forest data collection by UAV lidar-based 3D mapping: Segmentation of individual tree information from 3D point clouds. International Journal of Automation Technology, 15, 313-323. DOI URL
[29]	Tang H (2015) Lidar Remote Sensing of Vertical Foliage Profile and Leaf Area Index. PhD dissertation, University of Maryland, College Park, Park, MD.
[30]	Thorpe HC, Astrup R, Trowbridge A, Coates KD (2010) Competition and tree crowns: A neighborhood analysis of three boreal tree species. Forest Ecology and Management, 259, 1586-1596. DOI URL
[31]	Wang XF, Rao JS, Yang T, Liu WC, Tian X, Chen X, Liu QM, Xu YX, Zhang QY, Zhang HQ, Zhang X, Ou XK, Shen ZH (2023) Spatial variation and determinants of woody plant species diversity in a semi-humid evergreen broad-leaved forest in the Jizu Mountains, Yunnan. Biodiversity Science, 31, 23217. (in Chinese with English abstract)
	[王晓凤, 饶杰生, 杨涛, 刘文聪, 田希, 陈稀, 刘其明, 徐衍潇, 张秋雨, 张洪强, 张旭, 欧晓昆, 沈泽昊 (2023) 云南鸡足山半湿润常绿阔叶林群落木本植物多样性格局与环境解释. 生物多样性, 31, 23217.] DOI
[32]	Xiao ZQ, Song JL, Yang HA, Sun R, Li JA (2022) A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. International Journal of Remote Sensing, 43, 1409-1429. DOI URL
[33]	Xie YY, Wang B, Yao Y, Yang L, Gao Y, Zhang ZM, Lin LX (2020) Quantification of vertical community structure of subtropical evergreen broad-leaved forest community using UAV-Lidar data. Acta Ecologica Sinica, 40, 940-951. (in Chinese with English abstract)
	[解宇阳, 王彬, 姚扬, 杨琅, 高媛, 张志明, 林露湘 (2020) 基于无人机激光雷达遥感的亚热带常绿阔叶林群落垂直结构分析. 生态学报, 40, 940-951.]
[34]	Xie YY, Yang T, Wang XF, Chen X, Pang SX, Hu JA, Wang AX, Chen L, Shen ZH (2022) Applying a portable backpack lidar to measure and locate trees in a nature forest plot: Accuracy and error analyses. Remote Sensing, 14, 1806. DOI URL
[35]	Zhang Y, Chen HYH (2015) Individual size inequality links forest diversity and above-ground biomass. Journal of Ecology, 103, 1245-1252. DOI URL
[36]	Zhao J, Li J, Liu QH (2013) Review of forest vertical structure parameter inversion based on remote sensing technology. Journal of Remote Sensing, 17, 697-716. (in Chinese with English abstract)
	[赵静, 李静, 柳钦火 (2013) 森林垂直结构参数遥感反演综述. 遥感学报, 17, 697-716.]

基于背包LiDAR的半湿润常绿阔叶林及其常见树种的垂直结构特征

Vertical structural characteristics of a semi-humid evergreen broad-leaved forest and common tree species based on a portable backpack LiDAR

RichHTML

PDF (PC)

补充材料

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 36

相关文章 8

编辑推荐

Metrics

本文评价

[1]	张楚然, 李生发, 李逢昌, 唐志忠, 刘辉燕, 王丽红, 顾荣, 邓云, 张志明, 林露湘. 云南鸡足山亚热带半湿润常绿阔叶林20 ha动态监测样地木本植物生境关联与群落数量分类[J]. 生物多样性, 2024, 32(1): 23393-.
[2]	刘文聪, 田希, 杨涛, 饶杰生, 王晓凤, 钱恒君, 涂梦灵, 单子铭, 欧晓昆, 沈泽昊. 云南鸡足山半湿润常绿阔叶林优势树种的种群结构与更新特征[J]. 生物多样性, 2023, 31(11): 23251-.
[3]	左艳洁, 彭明春, 王崇云, 沈泽昊, 李永萍, 周新茂, 周杰, 周光信, 任佳昕, 刘忠安. 滇中高原半湿润常绿阔叶林的岛屿化与物种多样性[J]. 生物多样性, 2023, 31(11): 23252-.
[4]	田希, 刘文聪, 饶杰生, 王晓凤, 杨涛, 陈稀, 张秋雨, 刘其明, 徐衍潇, 张旭, 沈泽昊. 云南鸡足山半湿润常绿阔叶林的林隙干扰格局与成因[J]. 生物多样性, 2023, 31(11): 23219-.
[5]	杨涛, 沈泽昊, 王晓凤, 饶杰生, 刘文聪, 田希, 陈稀, 张秋雨, 刘倩, 钱恒君, 解宇阳, 刘其明, 徐衍潇, 涂梦灵, 单子铭, 张玉坤, 侯波, 李建斌, 欧晓昆. 滇中高原亚热带半湿润常绿阔叶林植物群落多样性特征[J]. 生物多样性, 2023, 31(11): 23238-.
[6]	罗彩访, 杨涛, 张秋雨, 王馨培, 沈泽昊. 滇中半湿润常绿阔叶林木本植物的功能特征和功能多样性及其影响因子[J]. 生物多样性, 2023, 31(11): 23215-.
[7]	罗恬, 俞方圆, 练琚愉, 王俊杰, 申健, 吴志峰, 叶万辉. 冠层垂直高度对植物叶片功能性状的影响: 以鼎湖山南亚热带常绿阔叶林为例[J]. 生物多样性, 2022, 30(5): 21414-.
[8]	桂旭君, 练琚愉, 张入匀, 李艳朋, 沈浩, 倪云龙, 叶万辉. 鼎湖山南亚热带常绿阔叶林群落垂直结构及其物种多样性特征[J]. 生物多样性, 2019, 27(6): 619-629.