臺灣博碩士論文加值系統

被子植物之葉部形態形質往往隨環境因子而改變，顯示其適應不同棲地環境的生長機制。蕨類植物在植株型態與生活史上與被子植物有明顯的差異。但有關於蕨類之葉部形態形質以及其生長機制如何隨環境梯度而改變的研究卻十分少見，且臺灣亦少有沿環境梯度設立樣區調查蕨類群集的研究。本研究旨在了解1)蕨類與石松之物種組如何隨環境因子而改變、2)蕨類物種間葉部形態形質之差異與其葉片生長機制之間的關係，以及3)蕨類群集之葉部形態形質如何隨環境因子而改變。臺灣是一個具有明顯海拔差異的島嶼，許多環境因子也同時隨著海拔而改變，造就了多樣的棲地。為了解海拔與其他環境因子如何影響蕨類與石松植物，我在臺灣東北部海拔850公尺至2100公尺間之山區設立了18個20×20公尺及60個10×10公尺之樣區，紀錄各樣區之微氣候、地形、土壤、光照，及生物性環境因子。同時，調查了地生與附生蕨類之物種組成，並採集葉片樣本進行一系列之形質特徵測量，包含葉厚、葉面積、比葉面積(specific leaf area, SLA)、單位面積之葉綠素含量、葉乾物質含量(leaf dry matter content, LDMC)、葉肉質程度(succulence)、總碳與總氮含量、13C/12C 比例，以及15N/14N比例。在統計分析上，物種組成與環境因子間的關係由除趨勢對應分析(detrended correspondence analysis, DCA)和典範對應分析(canonical correspondence analysis, CCA)來檢測；形質特徵與形質特徵間的關係由皮爾森相關性檢定分析(Pearson’s correlation test)以及主成分分析(Principal component analysis)來檢測；族群之形態形質與環境梯度之關係由RLQ分析與第四角分析(fourth-corner analysis)來檢測。結果顯示，所有樣區總計有121種蕨類與石松植物，其中83種蕨類經過形質特徵之測量與分析，48種為地生，35種為附生。在物種組成方面，地生與附生之物種主要皆隨海拔與溫度而改變，地生物種還受土壤酸鹼度和坡度影響，而附生物種則亦受土壤碳氮比(間接地)及林冠與地形之開闊度影響。地生物種中，於較低溫或有較高酸度土壤之棲地主要可見瘤足蕨屬物種分布，於較溫暖之棲地則主要為雙蓋蕨屬植物；數個物種如紅苞蹄蓋蕨及雉尾烏毛蕨於陡坡之環境中常見。附生物種中，於溫暖之棲地主要可見兩種巢蕨及半附生之瓶蕨、波氏星蕨；在主要由巨大檜木組成之高土壤碳氮比棲地中，膜蕨科物種為優勢；兩種具有硬葉之水龍骨科蕨類及兩種膜蕨屬物種在樹冠與地形開闊向陽之環境中為優勢。經歸納，地生蕨類物種之葉片有三種主要的生長策略，分別為1)速生型(acquisitive)、2)精緻慢生型(delicate conservative)、3)抗逆境慢生型(resistance conservative)；附生蕨類的葉片主要可歸納為四種生長機制，分別為1)速生缺水落葉型(acquisitive drought-deciduous)、2)半耐旱型(intermediate)、3)耐旱保守型(xeromorphic conservative)、4)脫水復原型(poikilohydric)。地生物種之生長機制差異主要源於葉乾物質含量隨低溫逆境與低土壤養分可得性的環境而改變，而附生物種的生長機制差異主要是由於葉肉質程度與葉面積隨乾旱逆境與光照強度的改變所致。

Leaf morphological traits of angiosperm species are often related to environmental factors, revealing distinct strategies of plants adapting to different habitats. Ferns have distinct growth form and life history comparing with angiosperms, though few studies have focused on how ferns’ leaf morphological traits and growing strategies change along environmental gradients, and in Taiwan there are also few research have studied on how fern species composition change along environmental gradients based on plots survey. This study aims to understand 1) how do fern and lycophyte species composition change along environmental gradients; 2) how do the trait differences between fern species relate to their leaf growing strategies, and 3) how are the relationships of community-level fern’s leaf morphological traits and environmental factors. Taiwan has strong elevation gradient, driving the change of many environmental factors and creating diverse habitats. To find out how does elevation and other environmental factors affect ferns and lycophytes, I established 18 20×20-m plots and 60 10×10-m plots at elevation zones between 850 and 2100 m a.s.l. in northeastern Taiwan, and recorded microclimatic, topographical, soil, light, and biotic environmental factors. Terrestrial and epiphytic fern species composition were surveyed, and leaf sample were collected and measured for a set of traits including leaf thickness, leaf area, specific leaf area, area-based chlorophyll content, leaf dry matter content, succulence, leaf total carbon and nitrogen content, 13C/12C ratio, and 15N/14N ratio. In statistical analysis, species-environment relationships were analyzed by detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA), trait-trait relationships were analyzed by Pearson’s correlation test and display by principal component analysis, response of community-level traits along environmental variables were analyzed using the RLQ and fourth-corner methods. Overall, I found 121 fern and lycophyte species, 83 ferns have been measured and analyzed, 48 are terrestrial and 35 are epiphytic. Both terrestrial and epiphytic species composition mainly changed with elevation and temperature, while terrestrial species’ composition also changed with soil pH and slope, epiphytic species’ composition also changed with soil C:N ratio (indirectly) and site openness. In terrestrial species, Plagiogyria species had optima at mid to low temperature or more acid soil habitats; Dipluzium species had optima at warm habitat; several species such as Athyrium nakanoi, Blechnum melanopus had optima at steep habitat. For epiphytic species, two nest ferns and two hemiepiphytic fern had optima at high temperature habitat; Hymenophylaceae species had optima at high soil C:N ratio habitat which dominated by large Chamaecyparis tree; two hard leaf Polypodiaceae species and two Hymenophyllum species had optima at high site openness habitat. Three growing strategies are identified for terrestrial species, including 1) acquisitive, 2) delicate conservative, and 3) resistance conservative; four strategies are identified for epiphyte: 1) acquisitive drought-deciduous, 2) intermediate, 3) xeromorphic conservative, and 4) poikilohydric. Terrestrial species’ growing strategies were mainly related to the change of LDMC to the stress of cold and low nutrient availability, epiphytic species’ strategies were mainly related to the change of succulence and LA to the drought stress and light intensity.

誌謝 I
中文摘要 III
Abstract V
Content VII
List of figures X
List of tables XII
Abbreviation in this study XIII
1. INTRODUCTION 1
1.1 Integrated study of species composition, trait composition along environmental gradients, and the interspecies trait differences 1
1.2 Fern and lycophyte species composition change along environmental gradients 2
1.3 Adapting strategies of terrestrial and epiphytic ferns: interpretation of functional traits 2
1.3.1 Fern physiological traits – previous studies 4
1.3.2 Fern morphological traits – previous studies 5
1.4 Community-level fern traits change with environmental gradients 5
1.5 This study 6
2. MATERIALS AND METHODS 8
2.1 Study area 8
2.1.1 Geographical location 8
2.1.2 Geology and soil 9
2.1.3 Climate and vegetation 9
2.2 Sampling design 11
2.3 The measurements of environmental conditions 12
2.3.1 Spatial factors 12
2.3.2 Topographical factors 12
2.3.3 Soil factors 12
2.3.4 Light condition 15
2.3.5 Woody species composition factors 16
2.3.5 Microclimate 16
2.4 Ferns and lycophytes community’s composition 17
2.5 Fern trait sampling 18
2.6 Traits measurements 18
2.6.1 Leaf thickness 19
2.6.2 Area-based leaf chlorophyll content 19
2.6.3 Leaf area 19
2.6.4 Leaf fresh weight and leaf dry weight 20
2.6.5 Leaf dry matter content, specific leaf area and succulence 20
2.6.6 Leaf total carbon and nitrogen content, stable isotope 13C/12C, 15N/14N ratio 21
2.7 Statistical analysis 21
2.7.1 Pretreatment 21
2.7.2 Environmental condition 24
2.7.3 Species-environment relationship 25
2.7.4 Trait-species and Trait-trait relationships 26
2.7.5 Community-level trait-environment relationships 26
2.7.6 Variation partitioning of species and traits composition by environmental factors 27
3. RESULTS 28
3.1 Species-environment relationship 28
3.1.1 Pattern of environmental gradients related to the variation in species composition 28
3.1.2 Important environmental factors related to species composition 28
3.1.3 Species optima along important environmental factors 29
3.2 Trait-species and trait-trait relationship 33
3.2.1 Traits comparison between terrestrial and epiphytic ferns 33
3.2.2 Trait-trait correlations 33
3.3 Community-level trait-environment relationships 41
3.4 Variation of species composition and traits composition explained by environmental factors 45
4. DISCUSSION 46
5. CONCLUSION 50
6. REFERENCE 51
7. APPENDIX 58
Appendix 1: Environmental condition results 58
Appendix 1.1 Microclimate 58
Appendix 1.2 Soil properties 65
Appendix 1.3 Light 65
Appendix 1.4 Woody species composition and forest structure 65
Appendix 2: Supplemental results 67
Appendix 2.1: Species-environment relationship 67
Appendix 2.2: Trait-trait relationship 68
Appendix 3.3 Community-level trait-environment relationships 71
Appendix 3: Species list 73
Appendix 4: Species traits data 76
Appendix 5: R code 80
Appendix 5.1 Code for temperature, relative humidity and wind data sorting 80
Appendix 5.2 Code for the main analysis 124

1. Acebey, A. R., Krömer, T., & Kessler, M. 2017. Species richness and vertical distribution of ferns and lycophytes along an elevational gradient in Los Tuxtlas, Veracruz, Mexico. Flora 235 83–91.
2. Becker, R. A., Wilks, A. R., Brownrigg, R., Minka, T. P. & Deckmyn, A. 2018. maps: Draw Geographical Maps. R package version 3.3.0. https://CRAN.R-project.org/package=maps
3. Becker, R. A., Wilks, A. R. & Brownrigg, R. 2018. mapdata: Extra Map Databases. R package version 2.3.0. https://CRAN.R-project.org/package=mapdata
4. Benzing, D.H. 1990. ‘Vascular epiphytes. General biology and related biota.’ Cambridge University Press: Cambridge
5. Bivand, R. & Lewin-Koh, N. 2019. maptools: Tools for Handling Spatial Objects. R package version 0.9–5. https://CRAN.R-project.org/package=maptools
6. Chang, C. R., Lee, P. F., Bai, M. L., & Lin, T. T. 2004. Predicting the geographical distribution of plant communities in complex terrain–a case study in Fushian Experimental Forest, northeastern Taiwan. Ecography 27: 577–588.
7. Chang, Y. H. 1998. The study of the relationship between the distribution of pteridophytes and environmental factors at Fushan area in North Taiwan, and estimating the utility of ferns as the microenvironmental indicators [Master thesis]. Taipei: National Taiwan University Library.
8. Díaz, S., Kattge, J., Cornelissen, J.H.C., Wright, I.J., Lavorel, S., Dray, S., Reu, B., Kleyer, M., Wirth, C., Prentice, I.C., Garnier, E., Bönisch, G., Westoby, M., Poorter, H., Reich, P.B., Moles, A.T., Dickie, J., Gillison, A.N., Zanne, A.E., Chave, J., Wright, S.J., Sheremet’ev, S.N., Jactel, H., Baraloto, C., Cerabolini, B., Pierce, S., Shipley, B., Kirkup, D., Casanoves, F., Joswig, J.S., Günther, A., Falczuk, V., Rüger, N., Mahecha, M.D. & Gorné, L.D. 2016. The global spectrum of plant form and function. Nature 529: 167.
9. Dolédec, S., Chessel, D., Ter Braak, C. J. F., & Champely, S. 1996. Matching species traits to environmental variables: a new three-table ordination method. Environmental and Ecological Statistics 3: 143–166.
10. Dray, S. & Dufour, A.B. 2007. The ade4 package: implementing the duality diagram for ecologists. Journal of Statistical Software 22: 1–20.
11. Dray, S., & Legendre, P. 2008. Testing the species traits–environment relationships: the fourth‐corner problem revisited. Ecology 89: 3400–3412.
12. Eddelbuettel, D. & Sanderson, C., 2014. RcppArmadillo: Accelerating R with high-performance C++ linear algebra. Computational Statistics and Data Analysis 71: 1054–1063. http://dx.doi.org/10.1016/j.csda.2013.02.005
13. Ellenberg, H. H. 1988. Vegetation Ecology of Central Europe. Cambridge University Press.
14. Ellsworth, D. S., & Reich, P. B. 1992. Leaf mass per area, nitrogen content and photosynthetic carbon gain in Acer saccharum seedlings in contrasting forest light environments. Functional Ecology 423–435.
15. Frazer, G. W., Canham, C. D., & Lertzman, K. P. 1999. Gap Light Analyzer (GLA), Version 2.0: Imaging software to extract canopy structure and gap light transmission indices from true-colour fisheye photographs, users manual and program documentation. Simon Fraser University, Burnaby, British Columbia, and the Institute of Ecosystem Studies, Millbrook, New York, 36.
16. Garnier, E., Cordonnier, P., Guillerm, J.L. & Sonie, L. 1997. Specific leaf area and leaf nitrogen concentration in annual and perennial grass species growing in Mediterranean old-fields. Oecologia 111: 490–498.
17. Guijarro, J. A. 2018. climatol: Climate Tools (Series Homogenization and Derived Products). R package version 3.1.1. https://CRAN.R-project.org/package=climatol
18. He, F. & Legendre, P. 1996. On species-area relation. The American Naturalist 148: 719–737.
19. Hietz, P., & Briones, O. 1998. Correlation between water relations and within-canopy distribution of epiphytic ferns in a Mexican cloud forest. Oecologia 114: 305–316.
20. Hietz, P., & Briones, O. 2001. Photosynthesis, chlorophyll fluorescence and within-canopy distribution of epiphytic ferns in a Mexican cloud forest. Plant Biology 3: 279–287.
21. Hsu, R. C. C., Wolf, J. H., & Tamis, W. L. 2014. Regional and elevational patterns in vascular epiphyte richness on an East Asian island. Biotropica 46: 549–555.
22. Kahle, D. & Wickham H. 2013. ggmap: Spatial Visualization with ggplot2. The R Journal, 5: 144–161. http://journal.r-project.org/archive/2013-1/kahle-wickham.pdf
23. Karst, A. L., & Lechowicz, M. J. 2007. Are correlations among foliar traits in ferns consistent with those in the seed plants?. New Phytologist 173: 306–312.
24. Kessler, M., Siorak, Y., Wunderlich, M., & Wegner, C. 2007. Patterns of morphological leaf traits among pteridophytes along humidity and temperature gradients in the Bolivian Andes. Functional Plant Biology 34: 963–971.
25. Kessler, M., Kluge, J., Hemp, A., & Ohlemüller, R. 2011. A global comparative analysis of elevational species richness patterns of ferns. Global ecology and biogeography 20: 868-880.
26. Kessler, M., Karger, D. N., & Kluge, J. 2016. Elevational diversity patterns as an example for evolutionary and ecological dynamics in ferns and lycophytes. Journal of Systematics and Evolution 54: 617–625.
27. Kluge, J., & Kessler, M. 2007. Morphological characteristics of fern assemblages along an elevational gradient: patterns and causes. Ecotropica 13: 27–43.
28. Kluge, J., & Kessler, M. 2011. Phylogenetic diversity, trait diversity and niches: species assembly of ferns along a tropical elevational gradient. Journal of Biogeography 38: 394–405.
29. Knapp, R. 2011. Ferns and Fern Allies of Taiwan. KBCC Press & Yuan-Liou Publishing, Taipei, Taiwan.
30.Knapp, R. & Hsu, T-C. 2017. Ferns and Fern Allies of Taiwan – Second supplement. KBCC Press.
31. Kreft, H., Jetz, W., Mutke, J., & Barthlott, W. 2010. Contrasting environmental and regional effects on global pteridophyte and seed plant diversity. Ecography 33: 408–419.
32. Lai, Y. -J. 2002 A study on the habitats of Rheophytic ferns around Taipei area [Master thesis]. Taipei: National Taiwan University Library.
33. Legendre, P., Galzin, R., & Harmelin-Vivien, M. L. 1997. Relating behavior to habitat: solutions to the fourth‐corner problem. Ecology 78: 547–562.
34. Li, C.-F., Chytrý, M., Zelený, D., Chen, M.-Y., Chen, T.-Y., Chiou, C.-R., Hsia, Y.-J., Liu, H.-Y., Yang, S.-Z., Yeh, C.-L., Wang, J.-C., Yu, C.-F., Lai, Y.-J., Chao, W.-C. & Hsieh, C.-F. 2013. Classification of Taiwan forest vegetation. Applied Vegetation Science 16: 698–719.
35. Lin, K.-C., Chen, Z.-S. & Chang, J.-M. 1988. Morphology, physicochemical properties, and classification of Lalashan podzolic soils of Northern Taiwan. Journal of the Chinese Agricultural Chemical Society 26: 503–514.
36. Liu, J.-T. & Chen, Z.-S. Characteristics, genesis, and classification of podzolic soils in Tamanshan mountain, northern Taiwan. 1990. Journal of the Chinese Agricultural Chemical Society 28: 148–159.
37. Lösch, R. 2001. ‘Wasserhaushalt der Pflanze.’ Quelle and Meyer: Wiebelsheim, Germany.
38. McIlroy, D., Brownrigg, R., Minka, T. P. & Bivand, R. 2018. mapproj: Map Projections. R package version 1.2.6. https://CRAN.R-project.org/package=mapproj
39. McCune, B. & Keon, D. 2002. Equations for potential annual direct incident radiation and heat load. Journal of Vegetation Science 13: 603–606.
40. Mehlich, A. 1984. Mehlich 3 soil test extractant: A modification of Mehlich 2 extractant. Communications in soil science and plant analysis 15: 1409–1416.
41. Moreno, S. O. 2017. condformat: Conditional Formatting in Data Frames. R package version 0.7.0. https://CRAN.R-project.org/package=condformat
42. Muller, K. & Wickham, H. 2018. tibble: Simple Data Frames. R package version 1.4.2. https://CRAN.R-project.org/package=tibble
43. Niemann G.J., Pureveen J.B.M., Eijkel G.B., Poorter H. & Boon J.J. 1992. Differences in relative growth rate in 11 grasses correlate with differences in chemical composition as determined by pyrolysis mass spectrometry. Oecologia 89: 567–573.
44. Nervo, M. H., da Silva Coelho, F. V., Windisch, P. G., & Overbeck, G. E. 2016. Fern and lycophyte communities at contrasting altitudes in Brazil’s subtropical Atlantic Rain Forest. Folia Geobotanica 51: 305–317.
45. Neuwirth, E. 2014. RColorBrewer: ColorBrewer Palettes. R package version 1.1-2. https://CRAN.R-project.org/package=RColorBrewer
46. Oksanen, J., Blanchet, F. G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P. R., O''Hara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H., Szoecs, E. & Wagner, H. 2018. vegan: Community Ecology Package. R package version 2.5–2. https://CRAN.R-project.org/package=vegan
47. Page, C. N. 2002. Ecological strategies in fern evolution: a neopteridological overview. Review of Palaeobotany and Palynology 119: 1–33.
48. Pérez-Harguindeguy, N., Díaz, S., Garnier, E., Lavorel, S., Poorter, H., Jaureguiberry, P., Bret-Harte, M. S., Cornwell, W. K., Craine, J. M., Gurvich, D. E., Urcelay, C., Veneklaas, E. J., Reich, P. B., Poorter, L., Wright, I. J., Ray, P., Enrico, L., Pausas, J. G., de Vos, A. C., Buchmann, N., Funes, G., Quétier, F., Hodgson, J. G., Thompson, K., Morgan, H. D., ter Steege, H., van der Heijden, M. G. A., Sack, L., Blonder, B., Poschlod, P., Vaieretti, M. V., Conti, G., Staver, A. C., Aquino, S. & Cornelissen J. H. C. 2013. New handbook for standardized measurement of plant functional traits worldwide. Australian Journal of Botany 61:167–234.
49. Peres‐Neto P. R., Dray S. & ter Braak C. J. F. 2017. Linking trait variation to the environment: critical issues with community‐weighted mean correlation resolved by the fourth‐corner approach. Ecography 40: 806–816.
50. Pasek, J., Tahk, A., Culter, G., & Schwemmle, M. 2018. weights: Weighting and Weighted Statistics. R package version 1.0. https://CRAN.R-project.org/package=weights.
51. R Core Team. 2018. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
52. Radovski, M. 2010. Testing a trait-based model of fern community assembly [Master thesis]. McGill University Library.
53. Rueden, C. T.; Schindelin, J. & Hiner, M. C. 2017. "ImageJ2: ImageJ for the next generation of scientific image data". BMC Bioinformatics 18:529
54. Saldaña, A., Gianoli, E., & Lusk, C. H. 2005. Ecophysiological responses to light availability in three Blechnum species (Pteridophyta, Blechnaceae) of different ecological breadth. Oecologia 145: 251.
55. Saldaña, A., Lusk, C. H., Gonzáles, W. L., & Gianoli, E. 2007. Natural selection on ecophysiological traits of a fern species in a temperate rainforest. Evolutionary Ecology 21: 651.
56. Shen, Y.-C. 2019. Relationship between functional traits of woody species and elevation gradient: a case study from forest vegetation in Northern Taiwan [Master thesis]. Taipei: National Taiwan University Library.
57. ter Braak, C. J., Peres‐Neto, P. R., & Dray, S. 2018. Simple parametric tests for trait–environment association. Journal of Vegetation Science 29: 801–811.
58. Violle, C., Navas, M. L., Vile, D., Kazakou, E., Fortunel, C., Hummel, I., & Garnier, E. 2007. Let the concept of trait be functional! Oikos 116: 882–892.
59. Watkins, J. E., Rundel, P. W., & Cardelús, C. L. 2007. The influence of life form on carbon and nitrogen relationships in tropical rainforest ferns. Oecologia 153: 225.
60. Wegner, C., Wunderlich, M., Kessler, M., & Schawe, M. 2003. Foliar C:N ratio of Ferns along an Andean Elevational Gradient. Biotropica 35: 486–490.
61. Westhoff, V., & Van Der Maarel, E. 1978. The braun-blanquet approach. In Classification of plant communities 287–399. Springer, Dordrecht.
62. Westoby, M. 1998. A leaf-height-seed (LHS) plant ecology strategy scheme. Plant and Soil 199: 213–227.
63. Westoby, M., Cunningham, S., Fonesca, C.R., Overton, J.M. & Wright, I.J. 1998. Phylogeny and variation in light capture area deployed per unit investment in leaves: designs for selecting study species with a view to generalising. In: Lambers H, Poorter H, Van Vuuren MMI, eds. Inherent variation in plant growth, physiological mechanisms and ecological consequences. Leiden, The Netherlands: Backhuys, 539–566.
64. Wickham, H., Francois, R., Henry, L. & Muller, K. 2018. dplyr: A grammar of data manipulation. R package version 0.7.5. https://CRAN.R-project.org/package=dplyr.
65. Wickham, H. 2016. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York.
66. Wilson, P. J., Thompson, K. E. N., & Hodgson, J. G. 1999. Specific leaf area and leaf dry matter content as alternative predictors of plant strategies. The New Phytologist. 143: 155–162.
67. Witkowski E.T.F., & Lamont B.B. 1991. Leaf specific mass confounds leaf density and thickness.
Oecologia 88: 486–493.
68. Zhang, Q., Chen, J. W., Li, B. G., & Cao, K. F. 2009. The effect of drought on photosynthesis in two epiphytic and two terrestrial tropical fern species. Photosynthetica 47: 128–132.
69. Zelený D. 2018. weimea: Weighted Mean Analysis. R package version 0.1.10.