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Assembly of functional diversity in an oceanic island flora

Nature volume 619, pages 545–550 (2023)Cite this article

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Abstract

Oceanic island floras are well known for their morphological peculiarities and exhibit striking examples of trait evolution1,2,3. These morphological shifts are commonly attributed to insularity and are thought to be shaped by the biogeographical processes and evolutionary histories of oceanic islands2,4. However, the mechanisms through which biogeography and evolution have shaped the distribution and diversity of plant functional traits remain unclear5. Here we describe the functional trait space of the native flora of an oceanic island (Tenerife, Canary Islands, Spain) using extensive field and laboratory measurements, and relate it to global trade-offs in ecological strategies. We find that the island trait space exhibits a remarkable functional richness but that most plants are concentrated around a functional hotspot dominated by shrubs with a conservative life-history strategy. By dividing the island flora into species groups associated with distinct biogeographical distributions and diversification histories, our results also suggest that colonization via long-distance dispersal and the interplay between inter-island dispersal and archipelago-level speciation processes drive functional divergence and trait space expansion. Contrary to our expectations, speciation via cladogenesis has led to functional convergence, and therefore only contributes marginally to functional diversity by densely packing trait space around shrubs. By combining biogeography, ecology and evolution, our approach opens new avenues for trait-based insights into how dispersal, speciation and persistence shape the assembly of entire native island floras.

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Fig. 1: Trait space of the native flora of Tenerife fits within the global trait space and is subject to similar constraints to the global trait space but is biased towards medium-statured species with intermediate trait values (shrubby functional hotspot).
Fig. 2: Imprint of biogeography and evolution on the trait space of Tenerife native flora.
Fig. 3: Contribution of biogeographical and evolutionary processes to the functional diversity of the native flora of Tenerife.

Data availability

The trait data and floristic information of the species are available in a Figshare repository (https://doi.org/10.6084/m9.figshare.22355065.v1). Source data are provided with this paper.

Code availability

The analysis and data visualization performed in R software are available in a Figshare repository (https://doi.org/10.6084/m9.figshare.22355065.v1).

References

  1. Carlquist, S. The biota of long-distance dispersal. II. Loss of dispersibility in Pacific Compositae. Evolution (N. Y.) 20, 30–48 (1966).

    Google Scholar 

  2. Darwin, C. On the Origin of Species (Murray, 1859).

  3. Zizka, A. et al. The evolution of insular woodiness. Proc. Natl Acad. Sci. USA 119, e2208629119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Burns, K. C. Evolution in Isolation: the Search for an Island Syndrome in Plants (Cambridge Univ. Press, 2019).

  5. Schrader, J., Wright, I. J., Kreft, H. & Westoby, M. A roadmap to plant functional island biogeography. Biol. Rev. 96, 2851–2870 (2021).

    Article  PubMed  Google Scholar 

  6. Patiño, J. et al. A roadmap for island biology: 50 fundamental questions after 50 years of The Theory of Island Biogeography. J. Biogeogr. 44, 963–983 (2017).

    Article  Google Scholar 

  7. Whittaker, R. J., Fernández-Palacios, J. M., Matthews, T. J., Borregaard, M. K. & Triantis, K. A. Island biogeography: taking the long view of nature’s laboratories. Science 357, eaam8326 (2017).

    Article  PubMed  Google Scholar 

  8. Losos, J. B. & Ricklefs, R. E. Adaptation and diversification on islands. Nature 457, 830–836 (2009).

    Article  ADS  CAS  PubMed  Google Scholar 

  9. Craven, D., Knight, T. M., Barton, K. E., Bialic-Murphy, L. & Chase, J. M. Dissecting macroecological and macroevolutionary patterns of forest biodiversity across the Hawaiian archipelago. Proc. Natl Acad. Sci. USA 116, 16436–16441 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  10. MacArthur, R. H. & Wilson, E. O. The Theory of Island Biogeography (Princeton Univ. Press, 1969).

  11. Gillespie, R. G. & Baldwin, B. G. in The Theory of Island Biogeography Revisited (eds Losos, J. B. & Ricklefs, R. E.) 358–387 (Princeton Univ. Press, 2010).

  12. Weigelt, P. et al. Global patterns and drivers of phylogenetic structure in island floras. Sci. Rep. 5, 12213 (2015).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  13. Loiseau, N. et al. Global distribution and conservation status of ecologically rare mammal and bird species. Nat. Commun. 11, 5071 (2020).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  14. Veron, S. et al. High evolutionary and functional distinctiveness of endemic monocots in world islands. Biodivers. Conserv. 30, 3697–3715 (2021).

    Article  Google Scholar 

  15. Violle, C., Reich, P. B., Pacala, S. W., Enquist, B. J. & Kattge, J. The emergence and promise of functional biogeography. Proc. Natl Acad. Sci. USA 111, 13690–13696 (2014).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  16. Ottaviani, G. et al. Linking plant functional ecology to island biogeography. Trends Plant Sci. 25, 329–339 (2020).

    Article  CAS  PubMed  Google Scholar 

  17. Lavorel, S. & Garnier, E. Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. Funct. Ecol. 16, 545–556 (2002).

    Article  Google Scholar 

  18. Violle, C. et al. Let the concept of trait be functional! Oikos 116, 882–892 (2007).

    Article  Google Scholar 

  19. Reich, P. B. The world-wide ‘fast-slow’ plant economics spectrum: a traits manifesto. J. Ecol. 102, 275–301 (2014).

    Article  Google Scholar 

  20. Wright, I. J. et al. The worldwide leaf economics spectrum. Nature 428, 821–827 (2004).

    Article  ADS  CAS  PubMed  Google Scholar 

  21. Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).

    Article  ADS  PubMed  Google Scholar 

  22. Díaz, S. & Cabido, M. Vive la différence: plant functional diversity matters to ecosystem processes. Trends Ecol. Evol. 16, 646–655 (2001).

    Article  Google Scholar 

  23. Mouchet, M. A., Villéger, S., Mason, N. W. H. & Mouillot, D. Functional diversity measures: an overview of their redundancy and their ability to discriminate community assembly rules. Funct. Ecol. 24, 867–876 (2010).

    Article  Google Scholar 

  24. Wieczynski, D. J. et al. Climate shapes and shifts functional biodiversity in forests worldwide. Proc. Natl Acad. Sci. USA 116, 587–592 (2019).

    Article  ADS  CAS  PubMed  Google Scholar 

  25. Bruelheide, H. et al. Global trait–environment relationships of plant communities. Nat. Ecol. Evol. 2, 1906–1917 (2018).

    Article  PubMed  Google Scholar 

  26. Mammola, S. & Cardoso, P. Functional diversity metrics using kernel density n‐dimensional hypervolumes. Methods Ecol. Evol. 11, 986–995 (2020).

    Article  Google Scholar 

  27. König, C. et al. Biodiversity data integration—the significance of data resolution and domain. PLoS Biol. 17, e3000183 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Cornwell, W. K., Pearse, W. D., Dalrymple, R. L. & Zanne, A. E. What we (don’t) know about global plant diversity. Ecography 42, 1819–1831 (2019).

    Article  Google Scholar 

  29. Heleno, R. H. & Vargas, P. How do islands become green? Glob. Ecol. Biogeogr. 24, 518–526 (2015).

    Article  Google Scholar 

  30. Stuessy, T. F., Crawford, D. J. & Marticorena, C. Patterns of phylogeny in the endemic vascular flora of the Juan Fernandez Islands, Chile. Syst. Bot. 15, 338–346 (1990).

    Article  Google Scholar 

  31. Stuessy, T. F. et al. Anagenetic evolution in island plants. J. Biogeogr. 33, 1259–1265 (2006).

    Article  Google Scholar 

  32. Bohle, U. R., Hilger, H. H. & Martin, W. F. Island colonization and evolution of the insular woody habit in Echium L. (Boraginaceae). Proc. Natl Acad. Sci. USA 93, 11740–11745 (1996).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  33. Barajas-Barbosa, M. P., Weigelt, P., Borregaard, M. K., Keppel, G. & Kreft, H. Environmental heterogeneity dynamics drive plant diversity on oceanic islands. J. Biogeogr. 47, 2248–2260 (2020).

    Article  Google Scholar 

  34. Givnish, T. J. et al. Origin, adaptive radiation and diversification of the Hawaiian lobeliads (Asterales: Campanulaceae). Proc. R. Soc. B 276, 407–416 (2009).

    Article  PubMed  Google Scholar 

  35. Florencio, M. et al. Macaronesia as a fruitful arena for ecology, evolution, and conservation biology. Front. Ecol. Evol. 9, 718169 (2021).

    Article  Google Scholar 

  36. Fernández-Palacios, J. M. Climatic responses of plant species on Tenerife, the Canary Islands. J. Veg. Sci. 3, 595–603 (1992).

    Article  Google Scholar 

  37. Acebes Ginovés, J. R. et al. Pteridophyta, Spermatophyta in Lista de especies silvestres de Canarias. Hongos, plantas y animales terrestres (eds Arechavaleta, M. et al) 119-172 (Gobierno de Canarias, 2010).

  38. Price, J. P. et al. Colonization and diversification shape species–area relationships in three Macaronesian archipelagos. J. Biogeogr. 45, 2027–2039 (2018).

    Article  Google Scholar 

  39. Fernández-Palacios, J. M. et al. A reconstruction of Palaeo-Macaronesia, with particular reference to the long-term biogeography of the Atlantic island laurel forests. J. Biogeogr. 38, 226–246 (2011).

    Article  Google Scholar 

  40. Carlquist, S. Island Biology (Columbia Univ. Press, 1974).

  41. van Huysduynen, H. et al. Temporal and palaeoclimatic context of the evolution of insular woodiness in the Canary Islands. Ecol. Evol. 11, 12220–12231 (2021).

    Article  Google Scholar 

  42. Dória, L. C. et al. Insular woody daisies (Argyranthemum, Asteraceae) are more resistant to drought‐induced hydraulic failure than their herbaceous relatives. Funct. Ecol. 32, 1467–1478 (2018).

    Article  Google Scholar 

  43. Lens, F., Davin, N., Smets, E. & del Arco, M. Insular woodiness on the Canary Islands: a remarkable case of convergent evolution. Int. J. Plant Sci. 174, 992–1013 (2013).

    Article  Google Scholar 

  44. Shmida, A. & Werger, M. J. A. Growth form diversity on the Canary Islands. Vegetatio 102, 183–199 (1992).

    Article  Google Scholar 

  45. Biddick, M., Hendriks, A. & Burns, K. C. Plants obey (and disobey) the island rule. Proc. Natl Acad. Sci. USA 116, 17632–17634 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  46. Fernández-Palacios, J. M. et al. Evolutionary winners are ecological losers among oceanic island plants. J. Biogeogr. 48, 2186–2198 (2021).

    Article  Google Scholar 

  47. Silvertown, J. The ghost of competition past in the phylogeny of island endemic plants. J. Ecol. 92, 168–173 (2004).

    Article  Google Scholar 

  48. Hanz, D. M. et al. Climatic and biogeographical drivers of functional diversity in the flora of the Canary Islands. Glob. Ecol. Biogeogr. 31, 1313–1331 (2022).

    Article  Google Scholar 

  49. Molina-Venegas, R., Ramos-Gutiérrez, I. & Moreno-Saiz, J. C. Phylogenetic patterns of extinction risk in the endemic flora of a Mediterranean hotspot as a guiding tool for preemptive conservation actions. Front. Ecol. Evol. 8, 571587 (2020).

    Article  Google Scholar 

  50. Rundell, R. J. & Price, T. D. Adaptive radiation, nonadaptive radiation, ecological speciation and nonecological speciation. Trends Ecol. Evol. 24, 394–399 (2009).

    Article  PubMed  Google Scholar 

  51. Spasojevic, M. J. & Suding, K. N. Inferring community assembly mechanisms from functional diversity patterns: the importance of multiple assembly processes. J. Ecol. 100, 652–661 (2012).

    Article  Google Scholar 

  52. Carvajal-Endara, S., Hendry, A. P., Emery, N. C. & Davies, T. J. Habitat filtering not dispersal limitation shapes oceanic island floras: species assembly of the Galápagos archipelago. Ecol. Lett. 20, 495–504 (2017).

    Article  PubMed  Google Scholar 

  53. Irl, S. D. H., Obermeier, A., Beierkuhnlein, C. & Steinbauer, M. J. Climate controls plant life-form patterns on a high-elevation oceanic island. J. Biogeogr. 47, 2261–2273 (2020).

    Article  Google Scholar 

  54. Troll, V. R. & Carracedo, J. C. The Geology of the Canary Islands (Elsevier, 2016).

  55. Fernández-Palacios, J. M. & Nicolás, J. P. Altitudinal pattern of vegetation variation on Tenerife. J. Veg. Sci. 6, 183–190 (1995).

    Article  Google Scholar 

  56. Ricklefs, R. E. The Economy of Nature (WH Freeman, 2008).

  57. Stefan, V. & Levin, S. plotbiomes: Plot Whittaker biomes with ggplot2. R version 0.0.0.900 https://doi.org/10.5281/zenodo.7145245 (2022).

  58. Perez, T. M. et al. Botanic gardens are an untapped resource for studying the functional ecology of tropical plants. Phil. Trans. R. Soc. B 374, 20170390 (2019).

    Article  Google Scholar 

  59. Muer, T., Sauerbier, H. & Calixto, F. C. Die Farn-und Blütenpflanzen der Kanarischen Inseln (Margraf Publishers GmbH, 2016).

  60. Pérez-Harguindeguy, N. et al. Corrigendum to: New handbook for standardised measurement of plant functional traits worldwide. Aust. J. Bot. 64, 715 (2016).

    Article  Google Scholar 

  61. Penone, C. et al. Imputation of missing data in life-history trait datasets: which approach performs the best? Methods Ecol. Evol. 5, 961–970 (2014).

    Article  Google Scholar 

  62. Jin, Y. & Qian, H. V.PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography 42, 1353–1359 (2019).

    Article  Google Scholar 

  63. Stekhoven, D. J. & Bühlmann, P. missForest: nonparametric missing value imputation using Random Forest. R version 1.3 https://cran.r-project.org/web/packages/missForest/index.html (2012).

  64. Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).

    Article  Google Scholar 

  65. Orme, D. et al. The caper package: comparative analysis of phylogenetics and evolution in R. R version 5, 1-36 https://search.r-project.org/CRAN/refmans/caper/html/caper-package.html (2013).

  66. Kattge, J. et al. TRY plant trait database—enhanced coverage and open access. Glob. Chang. Biol. 26, 119–188 (2020).

    Article  ADS  PubMed  Google Scholar 

  67. Maitner, B. & Boyle, B. TNRS: taxonomic name resolution service. R version 0.3.0 https://CRAN.R-project.org/package=TNRS (2022).

  68. Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer Cham, 2016).

  69. Blonder, B. Hypervolume concepts in niche- and trait-based ecology. Ecography 41, 1441–1455 (2018).

    Article  Google Scholar 

  70. Villéger, S., Mason, N. W. H. & Mouillot, D. New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology 89, 2290–2301 (2008).

    Article  PubMed  Google Scholar 

  71. Blonder, B. R package (v 2.0.12): hypervolume: high dimensional geometry and set operations using kernel density estimation, support vector machines, and convex hulls. https://search.r-project.org/CRAN/refmans/hypervolume/html/hypervolume-package.html (2019).

  72. Weigelt, P., König, C. & Kreft, H. GIFT—a global inventory of floras and traits for macroecology and biogeography. J. Biogeogr. 47, 16–43 (2020).

    Article  Google Scholar 

  73. Joswig, J. S. et al. Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation. Nat. Ecol. Evol. 6, 36–50 (2022).

    Article  PubMed  Google Scholar 

  74. Segrestin, J. et al. PhenoSpace: a shiny application to visualize trait data in the phenotypic space of the global spectrum of plant form and function. Ecol. Evol. 11, 1526–1534 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Schleuter, D., Daufresne, M., Massol, F. & Argillier, C. A user’s guide to functional diversity indices. Ecol. Monogr. 80, 469–484 (2010).

    Article  Google Scholar 

  76. De Mendiburu, F. Agricolae: statistical procedures for agricultural research. R version 1.1-4 https://cran.r-project.org/web/packages/agricolae/index.html (2014).

  77. R Core Team. R: A Language and Environment for Statistical Computing. http://www.R-project.org/ (R Foundation for Statistical Computing, 2021).

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Acknowledgements

M.P.B.B. and H.K. acknowledge funding from the German Research Foundation (DFG) Research Training Group 1644 ‘Scaling Problems in Statistics’, grant no. 152112243. D.C. acknowledges funding from the Agencia Nacional de Investigación y Desarrollo (Chile; FONDECYT Regular no. 1201347). We thank the Jardín Botánico Canario ‘Viera y Clavijo’ in Gran Canaria for allowing measurements in the seed bank as well as for the samples taken of rare species that were not possible to find in the field; N. Straßburger, M. V. Rodríguez, A. A. Diez, B. Bhattarai, M. Mulligan and W. Osterman for invaluable assistance in the field and in the laboratory; B. Ø. Hansen for his helpful programming advice; R. Barone for assisting with plant identification and fieldwork; and G. Ottaviani, P. Gaüzère and L. Valente for providing valuable comments that improved our work immensely.

Author information

Authors and Affiliations

  1. Biodiversity, Macroecology & Biogeography, University of Göttingen, Göttingen, Germany

    Martha Paola Barajas Barbosa, Patrick Weigelt, Pierre Denelle & Holger Kreft

  2. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany

    Martha Paola Barajas Barbosa

  3. Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany

    Martha Paola Barajas Barbosa

  4. Centro de Modelación y Monitoreo de Ecosistemas, Universidad Mayor, Santiago, Chile

    Dylan Craven

  5. Data Observatory Foundation, Santiago, Chile

    Dylan Craven

  6. Campus-Institute Data Science, University of Göttingen, Göttingen, Germany

    Patrick Weigelt & Holger Kreft

  7. Centre of Biodiversity and Sustainable Land Use (CBL), University of Göttingen, Göttingen, Germany

    Patrick Weigelt & Holger Kreft

  8. Island Ecology and Biogeography Research Group, Department of Botany, Ecology and Plant Physiology, Universidad de La Laguna, Canary Islands, Spain

    Rüdiger Otto

  9. Instituto Multidisciplinario de Biología Vegetal (IMBIV), Consejo Nacional de Investigaciones Científicas y Técnicas and Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina

    Sandra Díaz

  10. Department of Geography and Environmental Science, University of Hawai‘i at Hilo, Hilo, HI, USA

    Jonathan Price

  11. Island Ecology and Biogeography Research Group, Instituto Universitario de Enfermedades Tropicales y Salud Pública de Canarias (IUETSPC), Universidad de La Laguna, Tenerife, Canary Islands, Spain

    José María Fernández-Palacios

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Contributions

H.K. conceived the initial idea. M.P.B.B., D.C., P.W. and H.K. further developed the concepts and designed the research. M.P.B.B. collected and measured plant traits and performed the statistical analysis. D.C. and P.D. contributed to the statistical analysis. R.O. and J.M.F.-P. supported the fieldwork logistics and execution, that is, plant trait data collection and species identification. J.P. curated lineage information. S.D. supported trait data curation and writing the discussion. All authors contributed to the interpretation of the results and the writing of the paper.

Corresponding author

Correspondence to Martha Paola Barajas Barbosa.

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Nature thanks Pierre Gaüzère, Gianluigi Ottaviani and Luis Valente for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Trait data overview and assessment.

a. Present empirical data and missing data distribution across 100% (n = 436) of Tenerife native seed plant species. b. Present empirical data and missing data distribution across 80% (n = 348, i.e., species with minimum of five trait values) of Tenerife native seed plant species, and c. across five species groups included in the main analysis. The missing trait data represented in black, were filled using phylogenetically informed imputation (see Methods). Percentages reported for each trait refer to the proportion of missing data. d. Density distribution of the empirical trait values only, and including imputed trait values for each trait. Percentages correspond to the proportion of species with imputed trait values.

Extended Data Fig. 2 Overview of the principal components explained variance of both island and global trait data, and hypervolume overlap.

a. Percentage of explained variance of the six dimensions of the principal component analysis (PCA) based on six plant functional traits of Tenerife’s native seed plants and seed plants from across the globe (348 Tenerife and 2,274 global species). b. Percentage of contributions of each trait to each dimension of the PCA. Trait values were z- and log-transformed prior to the PCA. c. Tenerife species projected onto the global spectrum of plant form and function21, contour lines indicating 0.5, 0.95 and 0.99 quantiles using kernel density estimation; PCA protection following74. Note that Tenerife native flora falls within the 99% isoline space of the global trait space. d. Estimated overlap, i.e., Sørensen index, between the island and global trait space estimated via null model (where n = 300 species randomly sampled, from island and global data separately, with replacement 999 times) based on hypervolume approach (see details in Methods). Null model 1 controls for a potential underrepresentation of shrubs in the global trait space by sampling the current proportions of growth form sensu72 (see Methods) and for the species richness difference between datasets. Null model 2 controls only for the species richness difference between both global and Tenerife datasets. In d. dots and error bars (not visible here as they are close to the mean) correspond to the mean values and 95% confidence intervals.

Extended Data Fig. 3 Overview of principal components analysis (PCA) for eight plant functional traits (n = 348 species) of Tenerife native seed plants.

a. Percentage of explained variance of the eight dimensions of the PCA. b. Percentage of contributions of each trait to each dimension of the PCA. Trait values were log- and scaled. c. Differences among the first and second principal component of the trait spaces of different biogeographical groups, Non-endemic native species (NEN), Macaronesian endemic species (MAC), Canary Islands endemic species (CE), Tenerife endemic species (TE) and cladogenetic species (CLA). Identical letters indicate no significant differences (Kruskal-Wallis text, P>0.05). Data are represented as boxplots where the middle line is the median, the lower and upper hinges correspond to the 25th and 75th percentiles, upper and lower whiskers extend from the hinge to the largest and lowest value, respectively, no further than 1.5 * IQR from the hinge.

Extended Data Fig. 4 Tenerife climatic representativity mapped on Whittaker biomes.

a. and b. field sites visited in 2017 and 2018 (n = 500), where plant material was collected to measure plant functional traits for this study.

Extended Data Fig. 5 Hot clades of endemic species of the Macaronesia (green), Tenerife (blue) and of native non-endemic species (black) are highlighted.

Hot nodes indicate clades with more species than expected at random. Node corresponds to standard effect size and node transparency is scaled by the number of sample trees in which a node was significantly overdispersed. Nodes include at least 10 species and occur in at least 50 sample trees. Note that the vast majority of hot nodes are among Tenerife endemic species.

Extended Data Fig. 6 Functional contribution and originality of the major radiated plant lineages present in Tenerife.

a. Functional contribution and b. functional originality for the 63 radiated lineages. Note that only Aeonium alliance and Polycarpaea lineages (marked with *) are significantly contributing to the expansion of Tenerife trait space, as their functional contribution or originality are significantly different from other species that do not belong to the lineage (results based on Kruskal-Wallis, P < 0.05). Each box plot in magenta colour correspond to a lineage; number of species on a lineage (i.e., n numbers) are the same in a-b. Each box plot in grey colour corresponds to all island species, except for species included in the corresponding compared lineage. In a–b data are represented as boxplots where the middle line is the median, the lower and upper hinges correspond to the 25th and 75th percentiles, upper and lower whiskers extend from the hinge to the largest and lowest value, respectively, no further than 1.5 * IQR from the hinge. c. Location of Aeonium alliance and Polycarpaea species in the island trait space; lineages extend it towards high values of leaf thickness. d. Number of radiated lineages present in Tenerife (31), Canary Islands (54) and Macaronesia (14). The 63 major lineages are composed of 195 species or 56% of all species included in the main analysis. The 63 lineages are nested within the Macaronesia, Canary Islands and Tenerife.

Extended Data Fig. 7 Sensitivity analyses using only cases (n = 237 species) with complete empirical data for all 8 traits.

a. Trait spaces for the native flora of Tenerife and dissected into five distinct species groups that illustrate the imprint of biogeography and evolution on the functional diversity of an oceanic island flora. b. Functional richness, functional dispersion and functional evenness were calculated using n-dimensional hypervolumes while controlling for the number of species richness for the five groups and for a null group in grey, where dots and error bars correspond to the mean values and 95% confidence intervals, based on null models (top). Functional contribution and originality of each group with respect to the rest of island species (bottom); data is represented as boxplots where the middle line is the median, the lower and upper hinges correspond to the 25th and 75th percentiles, upper and lower whiskers extend from the hinge to the largest and lowest value, respectively, no further than 1.5 * IQR from the hinge. See details in Methods.

Extended Data Table 1 Validation of trait values imputation
Full size table
Extended Data Table 2 Phylogenetic signal of empirical trait values and phylogenetic signal of missing trait values
Full size table

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Barajas Barbosa, M.P., Craven, D., Weigelt, P. et al. Assembly of functional diversity in an oceanic island flora. Nature 619, 545–550 (2023). https://doi.org/10.1038/s41586-023-06305-z

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  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-023-06305-z

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