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Journal of Vegetation Science 18: 307-312, 2007 © IAVS; Opulus Press Uppsala. FORUM - Is tree diversity different down-under? - 307

FORUM

Is tree diversity different in the Southern Hemisphere?

Burns, K.C.

School of Biological Sciences, Victoria University of Wellington, P.O. Box 600, Wellington, ; Fax +64 4 463 5331; E-mail [email protected]; Web http://www.vuw.ac.nz/staff/kevin_burns/index.htm

Abstract Introduction Questions: Is tree diversity higher in the southern hemisphere? Are latitudinal asymmetries in diversity sensitive to sampling Latitudinal variation in species diversity has intrigued effects? biologists for over two centuries (Hawkins 2001). How- Location: 198 forested locales worldwide. ever, it has only recently been appreciated that declines Methods: I re-analysed the Gentry database, which I augmented in diversity towards the poles may differ substantially with an additional survey from New Zealand. Data were used to test whether latitudinal declines in tree diversity differ between between hemispheres. In a recent review of latitudinal the northern and southern hemispheres. Data were also used to diversity asymmetries, Chown et al. (2004) argue that test whether hemispheric asymmetries in diversity are sensitive “…simple exercises – such as plotting richness values to sampling effects, or geographic variation in tree densities. for different latitudes or latitudinal bands against each Results: Area-based measurements of species diversity are other for the hemispheres and examining the resulting higher in the southern hemisphere. However, southern forests relationship… – rarely appear in the literature. Thus, it is house denser populations. After controlling for geographic not yet clear how common or strong hemisphere-related variation in tree densities, diversity patterns reverse, indicating asymmetry is.” (p. 460, Chown et al. 2004; cf. Hillebrand tree diversity is higher in the northern hemisphere. 2004). Conclusions: Latitudinal changes in tree diversity differ between hemispheres. However, the nature of hemispherical In a pioneering study, Gentry (1988) suggested that asymmetries in species diversity hinges on how diversity tree diversity might be higher ʻdown-underʼ in the south- is defined, illustrating how different definitions of diversity ern hemisphere. He graphically illustrated that species can yield strikingly different solutions to common ecological diversity of woody follows a bell-shaped distribu- problems. tion with latitude, rising from low diversity levels at the poles to a peak near the equator. But the peak in species diversity appeared to occur in the southern hemisphere. Keywords: Latitudinal diversity gradient; Sampling effect; Diversity also seemed to decline more rapidly with Species diversity. latitude in the northern hemisphere. However, Gentry (1988) based this observation on a limited number of forest inventories and he did not statistically test for Nomenclature: Allan (1961) and Moore & Edgar (1970). differences in diversity between hemispheres. Species diversity is deceptively difficult to character- ize. The most common measure of diversity is on an area- basis (i.e. species density, α-diversity, or the number of species present in a given area). However, area-based estimates of species diversity can be confounded by population density, if the number of individuals sampled varies among sampling points (Bunge & Fitzpatrick 1993; Gotelli 2001). Such ʻsampling effectsʼ can have impor- tant consequences to our understanding of how factors such as insularity and productivity influence taxonomic diversity (Hector et al. 2002; Forbes et al. 2001; Chiarucci et al. 2004; Lawes et al. 2005). However, “standardizing 308 Burns, K.C. FORUM data sets by area… may produce very different results continents (Africa = 18, Australasia = 38, Europe = 5, compared to standardizing by the number of individu- North America = 57, = 126), with over als collected, and it is not always clear which measure 80% of sampling points coming from North and South of diversity is appropriate” (p. 379, Gotelli & Colwell America. 2001). In an attempt to increase the representation of poorly Here, I test whether tree diversity is higher in the sampled regions and latitudes, I used Gentryʼs (1982) pro- southern hemisphere. Using the Gentry database, I tocol to sample an additional site in New Zealand. These evaluate whether hemispherical clines in area-based data were collected in Otari-Wiltonʼs Bush (41º14' S, measurements of tree diversity (i.e. species richness 174º45' E), which contains a large, undisturbed stand of per unit area) differ between hemispheres. I then as- conifer-broadleaf forest on the southern tip of the North sess latitudinal trends in tree population density and Island, New Zealand (see Burns & Dawson 2005 for a test whether latitudinal asymmetries in tree diversity detailed site description). Elevation ranges between 70 remain unchanged after controlling for variation in plant m and 280 m above sea-level, mean annual temperature density. is 12.8 ºC and total annual rainfall averages 1249 mm (Anon. 1996). I tested for hemispherical differences in area-based Methods measures of species diversity (i.e. number of species per 0.1 ha) using the general linear model procedure in Analyses were conducted using the Alwyn H. SPSS (Anon. 2002). The absolute value of latitude was Gentry Forest Transect Data Set (Phillips & Miller used as a covariate and hemisphere (north or south) was 2002). Gentry and his colleagues sampled a total of considered a fixed factor. The full model, comprised of 226 forested locales across the globe with a sampling the independent effects of the covariate and the fixed- design comprised of 10 separate transects, each meas- factor and their interaction was assessed. Following uring 2 m × 50 m (Gentry 1982). The first transect Engqvist (2005), the interaction term was used to test typically began from a randomly chosen starting point for differences in the slope of relationships for each in undisturbed forest and was oriented in a random hemisphere. Separate tests were conducted for trees, direction. Each subsequent transect was then oriented (lianas and hemi-epiphytes combined) and total in a random direction within a 180° arch from the end species diversity. of the previous transect. All plants > 2.5 cm diameter Next, I re-assessed hemispherical differences in at breast height (1.37 m) that were rooted within 1 m of species diversity after controlling for latitudinal varia- the transect line was identified to species. Plants were tion in plant density. Least-squares regression was used classified as belonging to morpho-species when their to evaluate the relationship between plant density and taxonomic identity was uncertain. Each plant was also latitude, and the relationship between plant density and categorized according to growth habit, either as a tree, species richness per unit area. Standardized residuals of or hemi-epiphyte. As a result, each subsequent 0.1 the relationship between plant density and area-based ha plot provides an estimate of plant population density measures of species diversity were then subject to the and species richness per unit area for each growth form. same general linear model procedure described above, The full dataset is freely available on line (http://www. using the same covariate (absolute value of latitude) and mobot.org/MOBOT/research/gentry/data.shtml) and is fixed-factor (hemisphere). Diversity and density estimates discussed in detail by Phillips & Miller (2002). were log10 transformed to conform to normality assump- Of the 226 plots included in the dataset, 29 differ tions. Separate tests were again conducted for trees, lianas from the protocol described above. Lianas and hemi- and total species diversity. epiphytes were not recorded in 6 sites, and 23 sites were Several additional analyses were conducted to control not sampled over a full 0.1 ha (i.e. < 10 transects were for geographic and latitudinal differences in sampling sampled). To promote unbiased comparisons, these plots intensity. In addition to the analysis of the full dataset (N were omitted from analyses, leading to a sample size of = 198), analyses were repeated after removing all sites 197 standardized inventories. Forest inventories were located above 42° latitude to account for latitudinal differ- also not distributed homogeneously across the globe. ences in sampling intensity (N = 188). Analyses were also First, temperate forests in the northern hemisphere were repeated on North and South American sites exclusively, sampled more intensely than south-temperate forests. to account for differences in sampling intensity between The highest latitude sampled in the southern hemisphere continents. In the separate analysis of American sites, was in south-central (40°43' S, 72°18' W), while ten samples located on Caribbean islands were also omitted sites in North America and Europe were located above to control for insularity effects (N = 148). In all three 42° latitude. Sampling intensity also differed between sets of analyses, the dependent variable and covariate FORUM - Is tree diversity different down-under? - 309

Table 1. F-statistics from general linear models of the effect of latitude and hemisphere on species diversity of lianas (including hemi-epiphytes), trees and both life forms combined. Results from area-based diversity estimates (species richness/0.1 ha) are shown alongside individual-based diversity estimates (residuals of relationships between plant density and species richness per unit area). Analyses were conducted on all fully-sampled Gentry plots (ʻfull global datasetʼ, N = 198), all plots located below 42° latitude to control for latitudinal differences in sampling intensity (ʻsites < 42° latitudeʼ, N = 188) and all non-insular plots located in North and South America below 42° latitude to control for continental differences in sampling intensity (N = 148). Subscripts refer to the more diverse hemisphere (S = southern hemisphere, N = northern hemisphere). Lianas Trees Trees & Lianas per-area per-individual per-area per-individual per-area per-individual

Full global dataset 4.6S* 24.2N*** 10.5S** 10.1N** 14.9S*** 14.8N***

Sites < 42° latitude 5.5S* 11.6N** 4.5S* 16.1N*** 7.0S** 10.4N**

North & South America (< 42°) 10.7S** 14.4N*** 4.3S* 29.1N*** 7.1S** 16.7N***

were variously transformed (i.e. squared, log10 or log10 Results + 1) to conform to assumptions when necessary. Lastly, I assessed climatic correlates of global variation in plant A total of 346 woody plants were encountered in density. New Zealand (see App. 1). These included 323 trees, 22 Temperature and precipitation data from were ob- lianas and one hemi-epiphyte. A total of 35 species were tained from the International Panel for Climate Change, encountered, including 28 tree species, 6 liana species and which were arranged as an array of half-degree longitude one hemi-epiphyte species. Results from New Zealand × latitude grid cells according to New et al. (1999). For were very similar to inventories of temperate forests in each site in the full dataset (N = 198), monthly averages Chile (Phillips & Miller 2002). The total dataset consisted were obtained for the period 1961-1990 to calculate four of 67 423 woody plants (trees = 55 913, lianas = 11 510) climatic variables: (1) mean monthly temperature, (2) and 20 974 species occurrences (trees = 16 206, lianas = mean monthly precipitation, (3) the standard deviation of 4768). mean monthly temperature, and (4) the standard devia- The total number of woody plant species occurring tion of mean monthly precipitation, following Hartley et in each plot declined with latitude at a different rate in al. (2006). Standard deviations of monthly temperature the northern and southern hemispheres (Table 1). The and precipitation data were obtained to estimate annual slope of the diversity-latitude relationship for all woody fluctuations in climate. Relationships between total plant plants was steeper for the northern hemisphere (Fig. density and the four climatic variables were then assessed 1). Similar results were obtained in separate analyses with multiple regression. Plant density, mean precipita- of trees and lianas. Similar results were also obtained tion and standard deviation in temperature were log10 with the full data set, sites located below 42° latitude transformed, and mean temperature was squared, to and non-insular, North and South American sites. conform to normality assumptions. Therefore, area-based diversity estimates indicate that

Fig. 1. A. Latitudinal variation in species richness per unit area (the total number of woody plant species per 0.1 ha); B. Latitudinal variation in species richness after controlling for plant density (standardized residuals of the relationship between species richness per unit area and plant density). Vertical dashed lines are drawn at the equator. Species richness per unit area declines more rapidly with latitude in the northern hemisphere, indicating tree diversity is higher in the southern hemisphere. However, the pattern reverses (i.e. diversity is higher in the northern hemisphere) after controlling for plant density. 310 Burns, K.C. FORUM

Fig. 2. Relationships (A) between plant density (log10 transformed) and latitude, and (B) between species richness per unit area and plant density (both log10 transformed). Southern hemisphere latitudes have negative values. tree diversity is higher in the southern hemisphere. Discussion Plant population densities differed between hemi- spheres (Fig. 2, see also Enquist & Niklas 2001; Currie Overall results showed that tree diversity is indeed et al. 2004). Total plant density declined linearly with different ʻdown-underʼ. However, the nature of hemi- latitude (r2 = 0.364, P < 0.001), and species richness per spherical asymmetries in diversity is strongly depend- unit area increased with plant density (r2 = 0.545, P < ent on how diversity is measured. When measured on 0.001). General linear model analyses of the residuals a per-area basis, diversity appears to be higher in the of the relationship between species richness per unit southern hemisphere, which supports Gentryʼs (1988) area and plant density yielded different results from the speculation. However, plant density also varies asym- previous analyses. After controlling for differences in metrically between hemispheres, increasing linearly from plant density, diversity estimates again declined with north to south. After controlling for latitudinal differences latitude, but in this case declines were more rapid in in plant density, the direction of hemispherical diversity the southern hemisphere (Fig. 1). Similar results were asymmetries reverses. On a per-individual basis, tree obtained in separate analyses of different growth forms diversity is higher in the northern hemisphere. and amalgamations of data (Table 1). Therefore, after This result can be analogized to an imaginary land- controlling for plant density, tree diversity is higher in scape that is randomly populated by plants belonging the northern hemisphere. to a variety of species, but plant density is higher at one Plant densities were correlated with several climatic end of the landscape than the other. If two equal sized variables. Total densities of woody plants were positively plots are placed on either side of the landscape, species related with mean annual temperature (T = 2.28, P = richness per unit area will be higher on the side of the 0.007) and negatively related to the standard deviation landscape containing more plants, because as more of average monthly temperatures (T = -5.12, P < 0.001). plants are sampled, more species will be encountered Plant densities were unrelated to mean annual precipita- by chance (see Gotelli & Colwell 2001). Hemispherical tion (T = 0.01, P = 0.991) and the standard deviation of asymmetries in tree species diversity appear to be influ- average monthly precipitation (T = -0.06, P = 0.953). enced by a similar type of sampling effect. Except that Multicollinearly assumptions were met in all four in- the side of the landscape with more plants (the southern dependent variables (variance inflation factor < 2.0 for hemisphere) actually contains fewer species. Or more all). precisely, results suggest that one would encounter new species less rapidly while randomly inspecting plants in the more densely populated, southern hemisphere. Sampling effects have been hypothesized to generate the latitudinal diversity gradient. Higher productivity at the equator might lead to denser populations, which could then randomly ʻsampleʼ more species (see Evans et al. 2005). Although I did not intend to test the sampling effect hypothesis as an overarching explanation for the FORUM - Is tree diversity different down-under? - 311 latitudinal gradient, my analyses argue against it. Even Acknowledgements. Alessandro Chiarucci, Gordon Jenkins, after removing the effect of plant density from area-based Michael Kessler, Michael Weiser and an anonymous reviewer estimates of species diversity, diversity still peaks at low provided helpful comments on earlier drafts of the manu- latitudes. Therefore, some factor associated with latitude script. (see Hawkins & Diniz-Filho 2005) is an important driver of geographic variation in individual-based estimates of References species diversity. In a previous analysis of the Gentry dataset, Currie Anon. 1996. Otari-Wiltonʼs bush management plan, Wellington et al. (2004) found that plant density is correlated with City Council, Wellington, NZ. evapotranspiration, albeit weakly (rs = 0.35). Analyses Anon. 2002. Release 11.5.1 for windows. SPSS Inc., Chicago, conducted here showed that plant density is more strongly IL, US. associated with temperature variability (rs = – 0.42), Allan, H.H. 1961. Flora of New Zealand. Vol. 1. Government indicating that areas with less variable monthly tempera- Printer, Wellington, NZ. tures (i.e. more stable temperature regimes) house denser Bunge, J. & Fitzpatrick, M. 1993. Estimating the number of plant populations. This result suggests that temperature species, a review. J. Am. Stat. Assoc. 88: 364-373. variability can partially explain latitudinal asymmetries Burns, K.C. & Dawson, J. 2005. Patterns in the diversity and in plant density. Annual fluctuations in temperature are distribution of epiphytes and vines in a New Zealand forest. Aust. Ecol. 30: 891-899. much reduced in the southern hemisphere (Chown et Chiaruccci, A., Alongi, C. & Wilson, J.B. 2004. Competitive al. 2004), due to smaller continental landmasses and exclusion and the no-interaction model operate simultane- the ameliorating effect of the ocean, which stores heat ously in microcosm plant communities. J. Veg. Sci. 15: as latent energy. This effect appears to explain higher 789-796. plant population densities in the southern hemisphere. Chown, S.L., Sinclair, B.J., Leinaas, H.P. & Gaston, K.J. 2004. However, the overall adjusted r2 value from this analy- Hemispheric asymmetries in – a serious matter sis is quite small, indicating that other factors, such as for ecology. PLoS Biol. 2: 1701-1707. historical effects or soil conditions, are also important. Currie, D.J., Mittelbach, G.G., Cornell, H.V., Field, R., Guégan, Therefore, while the negative relationship between J.-F., Hawkins, B.A., Kaufman, D.M., Kerr, J.T., Oberdorff, latitude and plant density appears to be associated with T., OʼBrien, E. & Turner J.R.G. 2004. Predictions and tests of climate-based hypotheses of broad-scale variation in temperature variability, a comprehensive explanation for taxonomic richness. Ecol. Lett. 7: 1121-1134. this pattern remains to be elucidated. Engqvist, L. 2005. The mistreatment of covariate interaction Niklas et al. (2003) linked the relationship between terms in linear model analyses of behavioural and evolu- plant density and species richness per unit area to plant tionary ecology studies. Anim. Behav. 70: 967-971. size. Regardless of hemisphere, most species in Gen- Enquist, B.J. & Niklas, K.J. 2001. Invariant scaling relations tryʼs plots occur only as saplings. Therefore, sampling across tree-dominated communities. Nature 410: 665- regimes that neglect to census smaller plants might seri- 660. ously bias estimates of species diversity. The reversal of Evans, K.L., Warren, P.H. & Gaston, K.J. 2005. Species-energy hemispherical asymmetries in diversity after controlling relationships at the macroecological scale: a review of the for sampling effects highlights a similar concern; dif- mechanisms. Biol. Rev. 80: 1-25. ferent ways of quantifying diversity can yield different Forbes, S., Schauwecker, T. & Weiher, E. 2001. Rarefaction does not eliminate the species richness-biomass relationship geographic patterns in biodiversity. in calcareous blackland prairies. J. Veg. Sci. 12: 525-532. Overall results uncovered strong hemispherical Gentry, A.H. 1982. Patterns in neotropical plant species diver- asymmetries in tree diversity. However, the direction sity. Evol. Biol. 15: 1-84. of hemispherical diversity asymmetries hinges on how Gentry, A.H. 1988. Changes in plant community diversity and species diversity is defined. On an area-basis, forests in floristic composition on environmental and geographic the southern hemisphere house more species. However, gradients. Ann. Miss. Bot. Gar. 75: 1-34. patterns in species diversity are strongly influenced by Gotelli, N.J. 2001. Research frontiers in null model analyses. geographic variation in plant density, and after correcting Global Ecol. Biogeogr. 10: 337-343. for sampling effects, diversity is higher in the northern Gotelli, N.J. & Colwell, R.K. 2001. Quantifying biodiversity: hemisphere. Tree diversity therefore appears to be differ- procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4: 379-391. ent down-under. However, identifying which hemisphere Hartley, S., Harris, R. & Lester, P.J. 2006. Quantifying uncer- is more diverse hinges on oneʼs definition of diversity. tainty in the potential distribution of an invasive species: climate and the Argentine ant. Ecol. Lett. 9: 1068-1079. Hawkins, B.A. 2001. Ecologyʼs oldest pattern? Trends Ecol. Evol. 16: 470. Hawkins, B.A. & Diniz-Filho, J.A.F. 2005. ʻLatitudeʼ and 312 Burns, K.C. FORUM

geographic patterns in species diversity. Ecography 27: Moore, L.B. & Edgar, E. 1970. Flora of New Zealand, Vol. 2. 268-272. Government Printer, Wellington, NZ. Hector, A., Bazeley-White, E., Loreau, M., Otway, S. & Schmid, New, M., Hulme, M. & Jones, P.D. 1999. Representing twenti- B. 2002. Overyielding in grassland communities: testing eth century space-time climate variability. Part 1: develop- the sampling effect hypothesis with replicated biodiversity ment of a 1961-90 mean monthly terrestrial climatology. experiments. Ecol. Lett. 5: 502-511. J. Climatol. 12: 829-856. Hillebrand, H. 2004. On the generality of the latitudinal diver- Niklas, K.J., Midgley, J.J. & Rand, R.H. 2003. Size-depend- sity gradient. Am. Nat. 163: 192-211. ent species richness: trends within plant communities and Lawes, M.J., Lamb, B.C.C. & Boudreau, S. 2005. Area- but across latitude. Ecol. Lett. 6: 631-636. no edge-effect on woody seedling abundance and species Phillips, O.L. & Miller, J.S. 2002. Global patterns of plant richness in old forest fragments. J. Veg. Sci. biodiversity: Alwyn H. Gentryʼs forest transect data set. 16: 363-372. Missouri Botanical Garden, St. Louis, MO, US.

Received 28 September 2006; Accepted 23 December 2006; Co-ordinating Editor: S. Díaz. 1

App. 1.

Family Genus Species Individuals Diameter at breast height (multi-stemmed individuals in parentheses)

Araliaceae Pseudopanax arboreus 1 2.8 Araliaceae Pseudopanax arboreus 2 10.3, 28.0 Araliaceae Pseudopanax crassifolius 1 12.0 Araliaceae Pseudopanax crassifolius 1 12.2 Asteraceae Brachyglottis repanda 1 4.0 Asteraceae Brachyglottis repanda 1 3.0 Asteraceae Olearia rani 2 19.0, 13.5 Asteraceae Olearia rani 1 14.2 novae-zelandiae 1 16.5 Apocynaceae Parsonsia heterophylla (L) 2 3.5, 5.7 Apocynaceae Parsonsia heterophylla (L) 1 3.1 Apocynaceae Parsonsia heterophylla (L) 1 3.0 Corynocarpaceae Corynocarpus laevigatus 1 14.0 Corynocarpaceae Corynocarpus laevigatus 1 3.8 Corynocarpaceae Corynocarpus laevigatus 1 29.5 Cyatheaceae Cyathea dealbata 5 15.5, 24.8, 21.5, 13.8, 24.0 Cyatheaceae Cyathea dealbata 5 21.1, 29.0, 24.5, 24.0, 21.5 Cyatheaceae Cyathea dealbata 2 20.8, 27.0 Cyatheaceae Cyathea dealbata 7 24.0, 28.5, 18.5, 16.5, 16.0, 21.0, 18.0 Cyatheaceae Cyathea dealbata 2 26, 22.0 Cyatheaceae Cyathea dealbata 2 24.0, 23.0 Cyatheaceae Cyathea dealbata 2 18.1, 18.2 Cyatheaceae Cyathea dealbata 2 19.2, 10.0 Dicksoniaceae Dicksonia squarrosa 1 14.4 Elaeocarpaceae Elaeocarpus dentatus 3 24.0, 44.5, 70.5 Elaeocarpaceae Elaeocarpus dentatus 3 22.0, 4.2, 25.0 Elaeocarpaceae Elaeocarpus dentatus 1 22.5 Elaeocarpaceae Elaeocarpus dentatus 1 37.5 Griseliniaceae Griselinia lucida (H) 1 (6.0, 4.4, 5.2) Beilschmiedia tawa 3 22, 47.0, 42.0 Lauraceae Beilschmiedia tawa 4 15.7, 17.9, 24.3, 14.6 Lauraceae Beilschmiedia tawa 4 55.0, 46.1, 42.4, 35.3 Lauraceae Beilschmiedia tawa 4 40.0, 6.5, 30.1, 20.0 Lauraceae Beilschmiedia tawa 1 39.5 Lauraceae Beilschmiedia tawa 7 19.8, 10.2, 15.0, 18.6, 30.4, 18.7, 18.0 Loganiaceae Geniostoma rupestre 2 2.5, (3.6, 4.4) Loganiaceae Geniostoma rupestre 1 2.6 Loganiaceae Geniostoma rupestre 1 (4.0, 4.0, 3.7) Loganiaceae Geniostoma rupestre 1 2.7 Loganiaceae Geniostoma rupestre 1 2.6 Loganiaceae Geniostoma rupestre 1 2.5 Loganiaceae Geniostoma rupestre 1 2.7 Hoheria sexstylosa 7 4.6, 3.3, 3.2, 3.0, 13.0, 3.5, 17.5 Malvaceae Hoheria sexstylosa 1 10.8 Malvaceae Hoheria sexstylosa 1 5.5 Meliaceae Dysoxylem spectabilie 1 24.2 18.4, (3.5, 11.0), 4.3, 3.1, 4.8, 4.1, 5.5, 3.5, 4.0, 3.8, 3.7, 3.7, 4.1, 3.5, 14.7, 2.7, 6.3, 4.3, 5.0, 6.9, 5.0, 4.6, 4.5, 3.4, 4.6, 4.5, 3.0, 15.8, 6.2, 3.0, 3.4, 12.5, Meliaceae Dysoxylem spectabilie 34 5.5, 6.0 5.7, 8.9, 4.6, 3.6, 6.1, 7.8, 4.5, 3.0, 7.1, (8.1, 6.2), 8.7, (5.5, 6.3), (5.7, 4.0), 4.4, Meliaceae Dysoxylem spectabilie 21 3.5, 3.0, 7.2, 14.0, 7.4, 8.2, 5.9 Meliaceae Dysoxylem spectabilie 11 13.9, 6.5, 23.0, 5.4, 12.0, 11.2, 3.0, (16.0, 21.1), 8.2, 13.8, 5.5 3.9, 9.4, 22.0, 17.6, 6.8, 8.8, 5.2, 5.8, 9.9, 19.3, 22.1, 4.2, 2.7, 18.7, 23.9, 3.2, Meliaceae Dysoxylem spectabilie 17 3.1 6.5, 2.9, 2.8, 2.8, 2.5, 2.5, 3.4, 10.0, 4.0, 41.1, 4.8, 3.0, 13.3, 9.4, 3.9, 2.8, 2.7, Meliaceae Dysoxylem spectabilie 18 2.5 36.4, 19.3, (14.2, 16.9), 8.9, 12.3, 15.7, 13.9, (15.5, 20.0), 33.2, (17.8, 18.2), 6.5, 2.9, 15.0, 6.5, 4.0, 3.5, 26.5, 2.5, 5.3, 22.0, (23.0, 7.1), 17.0, (26.0, 16.5), Meliaceae Dysoxylem spectabilie 33 17.0, 11.7, 9.0, 23.0, 36.6, 18.0, 23.0, 2.8, 3.2, 42.4 Monimiaceae arborea 1 (4.5, 6.0) Monimiaceae 1 (9.2, 13.9) Monimiaceae Hedycarya arborea 1 15.0 Monimiaceae Hedycarya arborea 3 13.4, 9.3, 11.3 Moraceae Streblus heterophyllus 1 3.7 Myrtaceae Metrosideros diffusa (L) 1 3.5 Myrtaceae Metrosideros diffusa (L) 1 4.2 Myrtaceae Metrosideros diffusa (L) 1 (2.7, 3.1)

App. 1. Internet supplement to: Burns, K.C. 2007. Is tree diversity different in the Southern Hemisphere?. J. Veg. Sci. 18: 307-312. 2

Myrtaceae Metrosideros fulgens (L) 1 2.5 Myrtaceae Metrosideros fulgens (L) 2 (4.3, 5.0, 2.6), 3.3 Myrtaceae Metrosideros fulgens (L) 3 2.6, 4.0, (4.5, 5.5) Myrtaceae Metrosideros perforata (L) 1 (3.8, 3.2, 2.8) Myrtaceae Metrosideros perforata (L) 1 2.9 Myrtaceae Metrosideros perforata (L) 3 8.2, 3.0, 3.1 Myrsinaceae Mysine australis 2 2.5, 4.2 Oleaceae Nestegis cunninghamii 2 12.3, 13.5 Passifloraceae Passiflora tetandra (L) 1 (3.0, 4.0) (7.0, 7.5, 8.2), (4.6, 5.8), (6.2, 2.8, 3.5), 6.4, (8.0, 7.5), (7.1, 6.3), (5.3, 3.8), 3.2, Piperaceae Macropiper excelsum 10 7.4, (3.0, 3.0) Piperaceae Macropiper excelsum 1 2.5 Piperaceae Macropiper excelsum 3 (5.0, 3.0, 3.0), 5.0, (6.0, 2.9, 3.2, 4.2) Piperaceae Macropiper excelsum 1 5.3 Piperaceae Macropiper excelsum 3 (4.3, 5.7), 3.3, 2.6 Piperaceae Macropiper excelsum 2 5.7, 2.8 Piperaceae Macropiper excelsum 5 3.3, 5.2, 2.7, 4.0, 3.0 Pittosporaceae Pittosporum eugenioides 1 19.0 Podocarpaceae Dacrydium cupressinum 1 91.5 Podocarpaceae Dacrydium cupressinum 1 60.6 Podocarpaceae Dacrydium cupressinum 1 72.5 Podocarpaceae Podocarpus totora 2 (25.5, 14.4), 48.5 Podocarpaceae Prumnopitys ferruginea 1 60.5 Podocarpaceae Prumnopitys taxifolia 1 31.0 Podocarpaceae Prumnopitys taxifolia 1 13.0 Proteaceae Knightia excelsa 1 46.9 Proteaceae Knightia excelsa 2 3.1, 5.3 Proteaceae Knightia excelsa 2 33.5, 11.0 Proteaceae Knightia excelsa 1 37.5 Proteaceae Knightia excelsa 1 16.0 Proteaceae Knightia excelsa 2 51.0, 58.5 Rosaceae Rubus cissoides (L) 1 2.6 Rosaceae Rubus cissoides (L) 1 4.0 Rosaceae Rubus cissoides (L) 1 7.5 Rubiaceae Coprosma grandifolia 2 6.5, 3.4 Rubiaceae Coprosma grandifolia 2 3.1, 8.8 Rubiaceae Coprosma grandifolia 1 2.5 Rutaceae Melicope simplex 1 (13.5,7.2) Rutaceae Melicope simplex 2 12.0, (6.5, 12.2, 8.2) Sapindaceae Alectryon excelsus 2 3.0, 8.2 Sapindaceae Alectryon excelsus 1 3.1 Violaceae Melicytus ramiflorus 11 (11.3, 9.5, 7.5), 10.5, (9.0, 6.5), 23.0, 5.6, 4.5, 8.0, (8.0, 3.7,4.0), 2.5, 13.0, 9.0 Violaceae Melicytus ramiflorus 4 9.2, 6.5, (10.0, 11.2), (9.3, 9.1, 7.1) Violaceae Melicytus ramiflorus 5 3.0, 2.8, 3.1, 3.5, 3.2 Violaceae Melicytus ramiflorus 1 3.1 Violaceae Melicytus ramiflorus 4 (5.7, 15.9), (9.8, 9.8), 26.9, 10.7 Violaceae Melicytus ramiflorus 3 11.0, 2.5, (2.8, 15.4) Violaceae Melicytus ramiflorus 2 17.5, 13.1 Violaceae Melicytus ramiflorus 1 46.5

App. 1. Internet supplement to: Burns, K.C. 2007. Is tree diversity different in the Southern Hemisphere?. J. Veg. Sci. 18: 307-312.