采用Strauss-Hardcore模型研究不同导管构型被子植物的导管空间分布特征

doi:10.17521/cjpe.2021.0083

摘要/Abstract

摘要：

被子植物木质部导管的分布格局非常多样, 并且与木质部的输水功能有密切的联系, 然而在木材解剖学中对导管分布格局往往采用定性描述, 不利于分析该特征与物种的水力功能、生态地理分布的关系。该文采用点格局分析方法, 依据木材孔型、导管空间排列和导管群集度三类木材宏观结构特征组合, 选取不同导管分布类型的17种代表性阔叶树种, 利用Strauss-Hardcore模型对其木质部横切面解剖影像进行定量分析。Strauss-Hardcore模型能够很好地拟合木质部中导管二维空间位点的分布特征, 该模型的3个参数: 硬核距离、局部聚集距离、点对交互作用强度(局部聚集指数)都有着明确的生物学意义。传统解剖学对导管构型的定性分类同模型相比不能准确表现被子植物的木质部导管空间分布特征, Strauss-Hardcore模型的局部聚集度指数主要受导管群集度影响, 尤其是复导管和导管团的存在都会增大导管小尺度聚集程度。对散孔材、半环孔材的生长轮及环孔材的晚材部分解剖图像分析表明, 导管以单导管为主且没有明显分布方向的散孔材树种, 其木质部导管点对交互作用强度为负值, 局部聚集指数一般小于0.4, 导管空间分布依次在3个局部尺度表现出排斥-排斥-随机格局; 而导管具有径向、弦向、锯齿形等明显目视识别特征的物种, 无论孔型和是否以单复导管为主, 其导管点对交互作用强度为正值, 局部聚集指数均大于0.4, 导管依次在3个局部尺度上表现出排斥-聚集-随机的分布格局。采用点过程模型有利于准确描述导管二维空间分布规律, 增强对导管空间格局形成机理的理解, 可有力地支撑木质部三维导管系统的理论研究和木质部结构-功能的实验研究。

关键词: 木质部导管, 空间点格局, Ripley's K函数, Strauss-Hardcore模型

Abstract:

Aims Spatial patterns of vessel in xylem are diverse and closely related with water transportation functions in angiosperms. However, the pattern was generally described qualitatively in anatomy, which were unable to reveal their links to xylem functions and to species distribution. We used point pattern analysis to study vessel spatial pattern in xylem cross-sectional images to quantify their features.

Methods Images of 17 types of vessel configurations were selected in terms of wood porosity, vessel arrangement, and vessel grouping. Optimum Strauss-Hardcore models for coordinates in the images were fitted. Correlations among vessel variables and model coefficients were tested.

Important findings We found that (1) Strauss-Hardcore model fitted all the data well and its three parameters, i.e., hardcore distance, local aggregation distance, and point-pair interaction or point aggregation index, and had apparent biological significance. (2) Classifications of wood xylem by traditional anatomical indices could not precisely present the spatial pattern of vessels compared to spatial point analysis, and local aggregation index from Strauss-Hardcore model was mainly influenced by vessel grouping, especially frequency of radial multiples and vessel clusters. (3) Among the 17 vessel patterns analyzed, diffusive or semi-ring species with xylem consisting of solidary vessels showed negative point-pair interaction and aggregation index was less than 0.4, whereas species with obvious vessel arrangement and multiple or clusters of vessel grouping in xylem owned positive point-pair interaction and bigger aggregation index. (4) The former group of species demonstrated inhibition- inhibition-random pattern at three local scales while the latter species showed inhibition-aggregation-random pattern according to the fitted Strauss-Hardcore models. The findings showed that point process modeling could precisely describe vessel distribution features in 2-D xylem sections and provide insights on vessel development. Therefore, this method may support 3-D vessel system simulation and experimental studies on structure-function of angiosperm xylem.

Key words: xylem vessel, spatial point pattern, Ripley's K function, Strauss-Hardcore model

郑景明, 刘洪妤. 采用Strauss-Hardcore模型研究不同导管构型被子植物的导管空间分布特征. 植物生态学报, 2021, 45(9): 1024-1032. DOI: 10.17521/cjpe.2021.0083

ZHENG Jing-Ming, LIU Hong-Yu. Using Strauss-Hardcore model to detect vessel spatial distribution in angiosperms with various vessel configurations. Chinese Journal of Plant Ecology, 2021, 45(9): 1024-1032. DOI: 10.17521/cjpe.2021.0083

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2021.0083

https://www.plant-ecology.com/CN/Y2021/V45/I9/1024

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参考文献 30

[1]	Adams HD, Zeppel MJB, Anderegg WRL, Hartmann H, Landhäusser SM, Tissue DT, Huxman TE, Hudson PJ, Franz TE, Allen CD, Anderegg LDL, Barron-Gafford GA, Beerling DJ, Breshears DD, Brodribb TJ, et al. (2017). A multi-species synthesis of physiological mechanisms in drought-induced tree mortality. Nature Ecology & Evolution, 1, 1285-1291.
[2]	Baddeley A, Turner R (2005). Spatstat: an R package for analyzing spatial point patterns. Journal of Statistical Software, 12, 1-42.
[3]	Baddeley A, Rubak E, Turner R (2015). Spatial Point Patterns: Methodology and Applications with R. CRC Press, New York.
[4]	Beeckman H (2016). Wood anatomy and trait-based ecology. IAWA Journal, 37, 127-151. DOI URL
[5]	Carlquist S (2001). Comparative Wood Anatomy. Springer, Berlin.
[6]	Carlquist S (2009). Non-random vessel distribution in woods: patterns, modes, diversity, correlations. Aliso, 27, 39-58.
[7]	Carlquist S (2012). How wood evolves: a new synthesis. Botany, 90, 901-940. DOI URL
[8]	Choat B, Brodribb TJ, Brodersen CR, Duursma RA, López R, Medlyn BE (2018). Triggers of tree mortality under drought. Nature, 558, 531-539. DOI URL
[9]	Choat B, Jansen S, Brodribb TJ, Cochard H, Delzon S, Bhaskar R, Bucci SJ, Feild TS, Gleason SM, Hacke UG, Jacobsen AL, Lens F, Maherali H, Martínez-Vilalta J, Mayr S, et al. (2012). Global convergence in the vulnerability of forests to drought. Nature, 491, 752-755. DOI URL
[10]	García-Cervigón AI, Olano JM, von Arx G, Fajardo A (2018). Xylem adjusts to maintain efficiency across a steep precipitation gradient in two coexisting generalist species. Annals of Botany, 122, 461-472. DOI PMID
[11]	Hacke UG, Spicer R, Schreiber SG, Plavcová L (2017). An ecophysiological and developmental perspective on variation in vessel diameter. Plant, Cell & Environment, 40, 831-845.
[12]	IAWA Committee (1989). IAWA list of microscopic features for hardwood identification. IAWA Bulletin, 10, 219-332. DOI URL
[13]	Jacobsen AL, Pratt RB, Tobin MF, Hacke UG, Ewers FW (2012). A global analysis of xylem vessel length in woody plants. American Journal of Botany, 99, 1583-1591. DOI PMID
[14]	Jacobsen AL, Valdovinos-Ayala J, Pratt RB (2018). Functional lifespans of xylem vessels: development, hydraulic function, and post-function of vessels in several species of woody plants. American Journal of Botany, 105, 142-150. DOI PMID
[15]	Johnson D, Eckart P, Alsamadisi N, Noble H, Martin C, Spicer R (2018). Polar auxin transport is implicated in vessel differentiation and spatial patterning during secondary growth in Populus. American Journal of Botany, 105, 186-196.
[16]	Loepfe L, Martinez-Vilalta J, Piñol J, Mencuccini M (2007). The relevance of xylem network structure for plant hydraulic efficiency and safety. Journal of Theoretical Biology, 247, 788-803. PMID
[17]	Martínez-Vilalta J, Mencuccini M, Álvarez X, Camacho J, Loepfe L, Piñol J (2012). Spatial distribution and packing of xylem conduits. American Journal of Botany, 99, 1189- 1196. DOI PMID
[18]	Mencuccini M, Martinez-Vilalta J, Piñol J, Loepfe L, Burnat M, Alvarez X, Camacho J, Gil D (2010). A quantitative and statistically robust method for the determination of xylem conduit spatial distribution. American Journal of Botany, 97, 1247-1259. DOI PMID
[19]	Mrad A, Domec JC, Huang CW, Lens F, Katul G (2018). A network model links wood anatomy to xylem tissue hydraulic behaviour and vulnerability to cavitation. Plant, Cell & Environment, 41, 2718-2730.
[20]	Panshin AJ, Zeeuw CD (1980). Textbook of Wood Technology: Structure, Identification, Uses Properties of Commercial Woods in the United States and Canada. McGraw-Hill Publishing Company, New York.
[21]	Perry GLW, Miller BP, Enright NJ (2006). A comparison of methods for the statistical analysis of spatial point patterns in plant ecology. Plant Ecology, 187, 59-82. DOI URL
[22]	Pfautsch S (2016). Hydraulic anatomy and function of trees- Basics and critical developments. Current Forestry Reports, 2, 236-248. DOI URL
[23]	R Core Team (2015). R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
[24]	Rueden CT, Schindelin J, Hiner MC, DeZonia BE, Walter AE, Arena ET, Eliceiri KW (2017). ImageJ2: ImageJ for the next generation of scientific image data. BMC Bioinformatics, 18, 529. DOI URL
[25]	Schenk HJ (2018). Wood: biology of a living tissue. American Journal of Botany, 105, 139-141. DOI URL
[26]	Scholz A, Klepsch M, Karimi Z, Jansen S (2013). How to quantify conduits in wood? Frontiers in Plant Science, 4, 56. DOI: 10.3389/fpls.2013.00056. DOI
[27]	Schweingruber FH, Börner A, Schulze ED (2008). Atlas of Woody Plant Stems: Evolution, Structure, and Environmental Modifications. Springer, Berlin.
[28]	Sievänen R, Godin C, DeJong TM, Nikinmaa E (2014). Functional-structural plant models: a growing paradigm for plant studies. Annals of Botany, 114, 599-603. PMID
[29]	von Arx G, Kueffer C, Fonti P (2013). Quantifying plasticity in vessel grouping-added value from the image analysis tool ROXAS. IAWA Journal, 34, 433-445. DOI URL
[30]	Wheeler EA, Baas P (1998). Wood identification-A review. IAWA Journal, 19, 241-264. DOI URL

模型 Model	点-过程特点 Point-process characteristic	适用范围 Scenario for model application
空间泊松模型 Poisson model	空间点位置完全随机 Complete spatial randomness of points	单一尺度, 单一导管属性, 随机分布特征 Single scale, single vessel identity, random distribution
硬核模型 Hardcore model	相邻点间距低于硬核距离则不能存在 Neighbor point is forbidden at distance smaller than hardcore distance	单一尺度, 单一导管属性, 均匀分布特征 Single scale, single vessel identity, uniform distribution
施特劳斯模型 Strauss model	相邻点间距越小则出现概率越低 Neighbor points have lower probability with smaller distance between them	单一尺度, 单一导管属性, 聚集分布特征 Single scale, single vessel identity, aggregation distribution
盖耶饱和模型 Geyer saturation model	任一点全部分布概率不超过特定值 Probability of each point is restrained at specific threshold value	单一尺度, 单一导管属性, 聚集分布特征, 受导管密度影响 Single scale, single vessel identity, aggregation distribution, influenced by total vessel density
多类型硬核模型 MultiHardcore model	点属性2类以上的硬核模型 Hardcore model with more than two point identities	单一尺度, 两类以上导管属性(如早、晚材导管, 单、复导管等), 同类导管均匀分布特征 Single scale, more than two vessel identities (e.g., vessel for early- and latewood, single vessel and multiple vessel), uniform distribution for each identity
多类型施特劳斯模型 MultiStrauss model	点属性2类以上的施特劳斯模型 Strauss model with more than two point identities	单一尺度, 两类以上导管属性, 同类导管聚集分布特征 Single scale, more than two vessel identities, aggregation distribution for each identity
斯特劳斯-硬核模型 Strauss-Hardcore model	一个硬核模型和一个施特劳斯模型的组合 A combination of a Strauss model and a Hardcore model	两个尺度, 单一属性的导管, 均匀-聚集分布特征 Two scales, single two vessel identity, uniform-aggregation distribution
多类型施特劳斯-硬核模型 MultiStrauss-Hardcore model	点属性2类以上的斯特劳斯-硬核模型 Strauss-Hardcore model with more than two point identities	两个尺度, 两类以上导管属性, 同类导管不同尺度上呈均匀和聚集分布特征 Two scales, more than two vessel identities, uniform-aggregation distribution
组合式盖耶模型 Piecewise Geyer model	组合模型, 可包括多个盖耶饱和子模型、硬核子模型和施特劳斯子模型 A hybrid model including multiple sub-models such as Strauss model, Hardcore model, and Geyer saturation model	多个尺度, 单一属性的导管, 均匀和聚集分布特征, 受导管总密度影响 More than two scales, single vessel identity, uniform-aggregation distribution, influenced by total vessel density

模型 Model	点-过程特点 Point-process characteristic	适用范围 Scenario for model application
空间泊松模型 Poisson model	空间点位置完全随机 Complete spatial randomness of points	单一尺度, 单一导管属性, 随机分布特征 Single scale, single vessel identity, random distribution
硬核模型 Hardcore model	相邻点间距低于硬核距离则不能存在 Neighbor point is forbidden at distance smaller than hardcore distance	单一尺度, 单一导管属性, 均匀分布特征 Single scale, single vessel identity, uniform distribution
施特劳斯模型 Strauss model	相邻点间距越小则出现概率越低 Neighbor points have lower probability with smaller distance between them	单一尺度, 单一导管属性, 聚集分布特征 Single scale, single vessel identity, aggregation distribution
盖耶饱和模型 Geyer saturation model	任一点全部分布概率不超过特定值 Probability of each point is restrained at specific threshold value	单一尺度, 单一导管属性, 聚集分布特征, 受导管密度影响 Single scale, single vessel identity, aggregation distribution, influenced by total vessel density
多类型硬核模型 MultiHardcore model	点属性2类以上的硬核模型 Hardcore model with more than two point identities	单一尺度, 两类以上导管属性(如早、晚材导管, 单、复导管等), 同类导管均匀分布特征 Single scale, more than two vessel identities (e.g., vessel for early- and latewood, single vessel and multiple vessel), uniform distribution for each identity
多类型施特劳斯模型 MultiStrauss model	点属性2类以上的施特劳斯模型 Strauss model with more than two point identities	单一尺度, 两类以上导管属性, 同类导管聚集分布特征 Single scale, more than two vessel identities, aggregation distribution for each identity
斯特劳斯-硬核模型 Strauss-Hardcore model	一个硬核模型和一个施特劳斯模型的组合 A combination of a Strauss model and a Hardcore model	两个尺度, 单一属性的导管, 均匀-聚集分布特征 Two scales, single two vessel identity, uniform-aggregation distribution
多类型施特劳斯-硬核模型 MultiStrauss-Hardcore model	点属性2类以上的斯特劳斯-硬核模型 Strauss-Hardcore model with more than two point identities	两个尺度, 两类以上导管属性, 同类导管不同尺度上呈均匀和聚集分布特征 Two scales, more than two vessel identities, uniform-aggregation distribution
组合式盖耶模型 Piecewise Geyer model	组合模型, 可包括多个盖耶饱和子模型、硬核子模型和施特劳斯子模型 A hybrid model including multiple sub-models such as Strauss model, Hardcore model, and Geyer saturation model	多个尺度, 单一属性的导管, 均匀和聚集分布特征, 受导管总密度影响 More than two scales, single vessel identity, uniform-aggregation distribution, influenced by total vessel density