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Quantifying Phytogeographical Regions of Australia Using Geospatial Turnover in Species Composition

Quantifying Phytogeographical Regions of Australia Using Geospatial Turnover in Species Composition The largest digitized dataset of land plant distributions in Australia assembled to date (750,741 georeferenced herbarium records; 6,043 species) was used to partition the Australian continent into phytogeographical regions. We used a set of six widely distributed vascular plant groups and three non-vascular plant groups which together occur in a variety of landscapes/habitats across Australia. Phytogeographical regions were identified using quantitative analyses of species turnover, the rate of change in species composition between sites, calculated as Simpson’s beta. We propose six major phytogeographical regions for Australia: Northern, Northern Desert, Eremaean, Eastern Queensland, Euronotian and South- Western. Our new phytogeographical regions show a spatial agreement of 65% with respect to previously defined phytogeographical regions of Australia. We also confirm that these new regions are in general agreement with the biomes of Australia and other contemporary biogeographical classifications. To assess the meaningfulness of the proposed phytogeographical regions, we evaluated how they relate to broad scale environmental gradients. Physiographic factors such as geology do not have a strong correspondence with our proposed regions. Instead, we identified climate as the main environmental driver. The use of an unprecedentedly large dataset of multiple plant groups, coupled with an explicit quantitative analysis, makes this study novel and allows an improved historical bioregionalization scheme for Australian plants. Our analyses show that: (1) there is considerable overlap between our results and older biogeographic classifications; (2) phytogeographical regions based on species turnover can be a powerful tool to further partition the landscape into meaningful units; (3) further studies using phylogenetic turnover metrics are needed to test the taxonomic areas. Citation: Gonza´lez-Orozco CE, Ebach MC, Laffan S, Thornhill AH, Knerr NJ, et al. (2014) Quantifying Phytogeographical Regions of Australia Using Geospatial Turnover in Species Composition. PLoS ONE 9(3): e92558. doi:10.1371/journal.pone.0092558 Editor: Ulrich Joger, State Natural History Museum, Germany Received August 14, 2013; Accepted February 25, 2014; Published March 21, 2014 Copyright:  2014 Gonzalez-Orozco et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: MCE’s contribution was supported under Australian Research Council’s ‘Future Fellow’ funding scheme (project number FT0992002). MCE and SWL also wish to thank the University of New South Wales, Australia for two Goldstar Grants (RG114989 & RG124461). The authors would like to thank Bernd Gruber for supporting the spatial overlap analyses. BDM thanks CSIRO (Australia) for a Distinguished Visiting Scientist Award. The authors acknowledge the support received from the Cancer Research UK and EPSRC Cancer Imaging Centre in association with the MRC and Department of Health (England) grant C1060/A10334, also NHS funding to the NIHR Biomedical Research Centre, MRC-funded studentship, also Chang Gung Medical Foundation (Taiwan) grants CMRPG370443 and CMRPG3B1922. MOL is an NIHR Senior Investigator. The authors thank Alice Warley at the Kings College London Centre for Ultrastructural Imaging (CUI) for assistance with electron microscopy. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript Competing Interests: The authors have declared that no competing interests exist. * E-mail: carlos.gonzalez-orozco@canberra.edu.au ¤ Current address: Institute for Applied Ecology and Collaborative Research Network for Murray-Darling Basin Futures, University of Canberra, Canberra, Australian Capital Territory, Australia ical regions) are defined on the distributions of specific taxonomic Introduction groups, and therefore are simpler to understand and to use The definition of biogeographical regions (also referred to as comparatively. bioregions) is fundamental for understanding the distribution of The history of Australian bioregionalization spans 190 years [6] biodiversity [1]. Bioregionalizations are important because they and may be divided into the colonial, post-federation, ecogeo- allow us to classify organisms into fundamental geographic units, graphical and systematic periods. The first attempt at a at different scales, to be used to establish global conservation bioregionalization classification of Australia was by Ferdinand agreements and to make diversity assessments [2,3,4,5]. The von Mueller in 1858, using vegetation types rather than taxic characteristics and terms used to define areas in biogeography are distributions [7]. In contrast, the naturalist Ralph Tate in 1889 not always used consistently (Table 1). For example, biomes are produced the first bioregionalization using a combination of taxic defined by both the climate and the types of organisms that have distributions and climate, coining the terms Eremaean and adapted to it and floristic zones are defined only by the types of Euronotian, both of which are still in use [8] and are also vegetation they contain. However, they are sometimes used used here. In 1933, during the Post-federation period, the interchangeably. Bioregions (phytogeographical and zoogeograph- PLOS ONE | www.plosone.org 1 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia Table 1. Glossary of terms. Term name Description Area The region of distribution of any taxonomic unit (species, genus, family) of the plant (or animal) world (Wulff 1950: 25) [51]. An endemic area is the geographical area to which a taxon or biota is understood to be native. (Parenti and Ebach 2009: 253) [50]. Biome Bioclimatic Zone. The geographical area defined by climate and the types of organisms that have adapted to it (e.g., mesic, arid). Biota A group of taxa (organisms), the combined distribution of which occupies a common set of geographical limits. (Parenti and Ebach 2009: 252) [50]. Biotic Area The geographical area inhabited by a biota. Limits of taxon distribution specify limits of the area (Parenti and Ebach 2009: 251) [50]. Biogeographical Region Bioregion or phytogeographical and zoological regions. The geographical area based on the distributions of specific taxonomic groups (e.g., plant or animal taxa). Vegetative (Floristic) Zone The geographical area defined by a particular type of vegetation (e.g., savannah, tundra, Mulga Scrub). The terms, regions, areas, and vegetation are often used inter-changeably, however, they do have specific meanings that we use herein with the following definitions. doi:10.1371/journal.pone.0092558.t001 zoogeographer G.E. Nicholls presented the first combined taxa has been used to identify phytogeographical regions of regionalization of Australian terrestrial flora and fauna [9]. plants across an entire continent such as Australia. Moreover, there has been no quantitative attempt to test existing Rather than adopt a combined bioregionalization, however, many Australian plant and animal geographers chose instead to phytogeographical regions that have been in use since the late th 19 century [8]. keep animal and plant distributions separate. Most important The method we apply to quantifying phytogeographical was Nancy Burbidge, who by the Ecogeographical Period regions is similar to recent zoogeographical studies [1,24]. developed her own regionalization consisting of areas that were Limited access to large nationally digitized spatial datasets is a largely based on Tate’s work [8] aswellasher expert knowledge likely reason why large studies do not exist on this topic. of flora distributions. Burbidge’s classification of Australia flora Australia is an exception because of the existence of Australia’s used the concept of interzones, that is, areas of overlap Virtual Herbarium AVH [31], which has digitized most (including the MacPherson-Macleay overlap zone), along with specimens housed in herbaria around Australia (http://www. three floristic zones (Temperate, Tropical and Eremaean) [10]. avh.ala.org.au/). This amalgamated database of herbarium Possibly the last continental bioregionalization of Australia’s records for an entire continent makes it possible to investigate flora was made by Dutch botanist Henk Doing in 1970, large scale patterns of plant distributions. In this paper we who created the first hierarchical classification of Australian used quantitative methods to prepare a phytogeographical flora according to vegetation type, communities and climate classification for the entire Australian continent using [11]. species turnover of nine major plant groups (Table 1) and to Other studies attempted to regionalize Australia through test the validity of an existing classification of Australia’s three using numerical, evidence-based data, such as Barlow’s 33 regions and 18 sub-regions. Our dataset contains representa- botanical regions derived from herbarium specimens [12]. By tives from diverse land plant groups (bryophytes, ferns, and the 1980s regionalization was done at the regional rather than angiosperms). continental level and many classifications ignored biotic areas in By first developing a species turnover-based phytogeographical favour of vegetative or climatic zones (i.e., biomes) [13]. classification, using taxonomic groups instead of climate, we are However, by thetimeofthe Systematic Period, particularly in then able to test how the environmental patterns, such as of theearly 1990s, therewas a resurgenceofbioticarea climate and soil types [19,20], fit the observed phytogeographical classification [14,15,16,17]. Of these new classifications, very regions. few were in agreement, leaving phytogeography with more areas The aims of this study were to: and area names than ever before [18]. In summary, there has to date been an accumulation of, often conflicting, area classifica- 1. Quantify and map the plant regions of Australia through tions, none of which were quantitatively produced or assessed. spatial analyses of modern databases of georeferenced Modern advances in the development of large databases of specimen data and compare these with the current phytogeo- georeferenced specimen observations, allied with concurrent graphical regionalization. improvements in spatial analysis tools, means that it is now 2. Identify what the major environmental drivers of species possible to quantitatively define and assess biotic regions turnover are for each of these phytogeographical regions. [19,20]. 3. Test the validity of previously proposed regions and sub- A key concept to define biogeographical regions (herein regions from the last 190 years, and propose an improved phytogeographical regions) is species turnover, which is the classification of the phytogeographical regions of Australia. rate of change in species composition between sites [21]. Species turnover has been used to generate classifications of bioregions [19,20,22,23,24,17] and there have been some Methods studies, for example, in sub-Saharan regions of Africa, wheremultipletaxa wereusedto successfullypartition the Spatial dataset continent into phytogeographical regions [25]. In other Table 2 summarizes the taxa and number of occurrence records cases, species turnover and multivariate statistical methods examined in this study. A total of 802,273 records were effectively diagnosed bioregions on different biological groups downloaded from Australia’s Virtual Herbarium (AVH) [31]. This [26,27,28,29,30]. However, no large dataset of geo-referenced dataset does not contain absence records, of course. Collections PLOS ONE | www.plosone.org 2 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia were mostly curated to the accepted taxonomy of the Australian Plant Census [32]. We did not consider any infra-specific taxa in a ðEq1:Þ b ~ 1{ sim the analysis. For each species, spatial errors were removed using az min (a,c) ArcGIS 9.2 [33]. The spelling and consistency of scientific names across taxa were corrected using Google Refine. Spatial outliers Where a refers to the number of species common to cells i and and all records without a geographic location were deleted. j, b is the number found in cell i but not cell j, and c is the Records that fell in the ocean or outside continental Australia number found in cell j but not cell i. A low b value indicates were excluded. After the correction process, 750,741 records sim that many taxa are shared between two grid cells (low remained for use in our final analyses. The geographic dissimilarity) and a high b means a small number of shared coordinates of each record were projected into an Albers equal sim taxa (high dissimilarity). area conic conformal coordinate system to avoid the latitudinal An agglomerative cluster analysis of the bsim turnover matrix biases of geographic coordinate systems. The records were was used to generate a WPGMA hierarchical cluster diagram in imported and aggregated to 100 km6100 km grid cells (870 in BIODIVERSE. Current literature suggests that dissimilarity clus- total) using BIODIVERSE 0.18 [34] (http://purl.org/biodiverse). tering algorithms are exposed to topology biases [55]. In order We calculated the ratio of species records to number of samples to reduce biases in our analyses, the cluster analysis included a per grid cell to measure redundancy, as an indicator of sample tie-breaker condition [18,19] such that, when more than one coverage [35]. We found that 70% of the analyzed grid cells had pair of sub-clusters had the same turnover score, the pair which a good level (60%) of species record redundancy within each grid had the highest Corrected Weighted Endemism (CWE) score cell (see Appendix S1). was selected for merging. This approach guarantees the same cluster result would be generated each time the model is run, as Taxonomic dataset well as increasing the endemicity of the resultant clusters. We The dataset included Australian representatives from a diverse identified the phytogeographical regions from the clusters based set of major terrestrial plant groups (bryophytes, ferns and several on two criteria: (1) a phytogeographical region is preferably large angiosperm genera and families) that represent a wide represented by a group of contiguous, or near-contiguous, grid geographic distribution across Australia [53,54]. For example, cells; (2) each cluster that represents a phytogeographical region Acacia and eucalypts are the most abundant canopy and sub- needs to be clearly separated from its children (immediate canopy woody plants in Australia [36,37,53]. One of the problems descendent nodes) or parent (immediate ancestral node) in the when gathering a large dataset is the reliability of the taxonomic dendrogram. identification. The more taxa included, the more challenging it becomes to achieve high taxonomic and spatial reliability of Spatial overlap analysis herbarium data. The strategy we applied was to utilize as many Our phytogeographical regions were visually compared with taxa as possible that combine a strong taxonomic tradition and several previous bioregionalizations of Australia. We also con- wide geographical ranges. Despite having experts on each group ducted a formalized comparison of the degree of overlap between involved in the cleaning process checking for taxonomic and our phytogeographical regions and the terrestrial phytogeograph- spatial errors in the sampled groups, we expect there to remain ical sub-regions proposed in the Australian Bioregionalization some low degree of taxonomic uncertainty. Atlas (ABA). This comparison used only the ABA because it is the existing classification that best reflects a historical viewpoint of Spatial analysis: bioregionalization geographical regionalizations of flora for Australia. Both classifi- All spatial analyses were conducted using BIODIVERSE [34]. A cations were converted to raster format with a resolution of matrix of species turnover was generated for all pair-wise 1006100 km. Because we aimed to identify phytogeographical combinations of grid cells (757,770 pairs). Simpson’s beta (b ) sim regions at the continental scale, a coarse grid cell size was applied. was used as the turnover measure because it corrects for species The effect of changes in grid cell size on the bioregions was richness differences between sites (Equation 1). explored in prior studies with eucalypts across Australia [19]. In that study we found no significant implications on the identifica- Table 2. The plant groups used in this study, number of occurrence points, and the number of species per group, with the totals. Taxon name Number of records Number of species Acacia 165,518 1,020 Asteraceae 105,692 823 Eucalypts (Angophora, Corymbia and Eucalyptus) 202,736 791 Ferns 58,774 356 Hornworts 370 13 Liverworts 16,502 735 Melaleuca 41,092 282 Mosses 79,210 835 Orchids 80,847 1,188 TOTAL 750,741 6,043 doi:10.1371/journal.pone.0092558.t002 PLOS ONE | www.plosone.org 3 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia tion of the major regions but some changes in the delimitation of environmental differences among the phytogeographic regions the regions boundaries occurred. The ABA sub-regions were then that were inferred from species turnover? overlaid on our phytogeographical regions using ArcMap 9.2 [33]. The gridded approach consists of three steps. First, summary The overall spatial agreement between both classification schemes statistics were calculated for 100 km6100 km grid cells of the (which differ in the number of classes and their extent) was eleven environmental variables in BIODIVERSE. Then, each of the calculated by the count of ABA sub-region cells that overlapped grid cells of the environmental variables were spatially linked to with only one of our regions and then divided by the total number each of the grid cells corresponding to the phytogeographic of cells in all ABA sub-regions. This value was summed up and regions. Finally, the association between the phytogeographical expressed as a percentage of overlap. regions and the environmental variables were calculated using Getis-Ord Gi* hotspot statistic spatial statistics in BIODIVERSE.We used the Getis-Ord Gi* hotspot statistic to assess if the Environmental correlates environmental values within the clusters (phytogeographic regions) Eleven environmental variables were used in this study (Table 3). were significantly different from those for the country as a whole A correlation matrix available on the spatial portal of the Atlas of [42,43]. The Gi* statistic is expressed as a z-score indicating the Living Australia was used to select variables which represented degree to which the values of a subset of grid cells, in this case the different environmental traits and demonstrated minimal correla- cells comprising a cluster, are greater or less than the mean of the tion. The spatial resolution of the layers was 1 km (approximately dataset. Those clusters with Gi* values greater than 2 or less than 0.01 degrees). The environmental layers were re-projected into the 22 represent sets of cells that have environmental values same Alber’s conic conformal coordinate system as the species significantly different from expected (a,0.05). data using the R software [38] and aggregated to 100 km6100 km grid cells using BIODIVERSE. The environmental variables were developed using ANUCLIM [39,40]. We also included four layers Results related to soils and topography, sourced from the National Land & Phytogeographical regions Water Resources Audit [41]. The mean value for each environ- We found and propose six phytogeographical regions: Northern mental variable within each 100 km6100 km grid cell was Region (Euronotian, Monsoonal Tropics and Monsoon sensu calculated using BIODIVERSE. [57,18,19]), Northern Desert Region (Eremaean North sensu Relative environmental turnover (RET) aims to identify [18,19], Eremaean (Eremaean South sensu [18,19]), Eastern phytogeographical regions based on species turnover and inves- Queensland (South-eastern Temperate and southeast sensu tigate their environmental correlates. It has been shown to be a [14,18,19] and South-Western (Southwest sensu [8]) (see Fig 1). useful method to partition the continent into meaningful The names of the proposed regions are aligned to correspond to phytogeographic regions in Acacia and eucalypts [18,19]. RET the Australian Bioregionalisation Atlas [17]. was derived from a framework to delineate biogeographic regions Overall, the spatial arrangement of the phytogeographical initially proposed by Kreft & Jetz [23]. Previous studies used the regions follows a distinctive north to south pattern, with an east to term environmental turnover to explore rates of change of west pattern at the sub-regional level. The phytogeographical dissimilarity in vertebrates and their relationship to environment regions are nested in geographically related pairs. The first split is depending on the geographic distance [24]. RET is different from of the Northern and Northern Desert regions (branch length (bl) of previous approaches because it is not geographic distance based, 0.09; dendrogram in Fig 1) from the other four regions. The but instead combines grid cell analyses with ordinations. RET Northern is on a long branch (bl = 0.12) and readily subdivided consist of two parts, one is an ordination and the second is a east (bl = 0.09) to west (bl = 0.03; Fig 2). The region with the gridded analysis. Here, we only used the gridded component of highest species similarity to the Northern is the Northern Desert RET. The key question addressed is what are the main Table 3. Environmental variables used in our analyses. Environmental variable Description Annual precipitation Monthly precipitation estimates (mm) Annual mean temperature The mean of the week’s maximum and minimum temperature (uC) Annual mean radiation The mean of all the weekly radiation estimates (Mj/m /day) Precipitation of coldest quarter Total precipitation over the coldest period of the year Radiation seasonality Standard deviation of the weekly radiation estimates expressed as a percentage of the annual mean (Mj/ m /day) Precipitation seasonality Standard deviation of the weekly precipitation estimates expressed as a percentage of the annual mean (mm) Temperature seasonality Standard deviation of the weekly mean temperatures estimates expressed as a percentage of the annual mean (uC) Ridge top flatness Metric of the topographic flatness derived from a surface of 9 second grid cells (dimensionless) Rock grain size Lithological property of the bedrocks related to the mean grain size (0–10 units) Sand Content of sand on the top 30 cm of soil layer estimated from soil maps at a resolution of 1 km (%) Clay Content of clay on the top 30 cm of soil layer estimated from soil maps at a resolution of 1 km (%) doi:10.1371/journal.pone.0092558.t003 PLOS ONE | www.plosone.org 4 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia Figure 1. Phytogeographical regions of Australian terrestrial flora (a) as defined by the corresponding dendrogram (b). The colors of the regions in the map correspond to those used to plot the dendrogram. The dendrogram is a representation of the spatial relationship of dissimilarities in species composition among regions. doi:10.1371/journal.pone.0092558.g001 Region (bl = 0.08; Fig 1). This phytogeographical region also has a clear east (bl = 0.05) to west subdivision (bl = 0.08; Fig 2). The other major cluster has a short branch (bl = 0.03). The largest clustering of grid cells is the Eremaean phytogeographical region which shares a very short branch (bl = 0.01) with the South- Western phytogeographical region (Fig 1). The Eremaean is on a long branch (0.08) and subdivides east (bl = 0.07) to west (bl = 0.04; Fig 2). The South-Western phytogeographical region is also on a long branch (bl = 0.11) and is subdivided into three coastal (bl = 0.02) subregions and an inland (bl = 0.04) subregion (Fig 2). The Euronotian and Eastern-Queensland phytogeographical regions cluster together (bl = 0.03). The Eastern Queensland phytogeographical region (bl = 0.24) runs along the eastern coast of Queensland from the Wet Tropics to the New South Wales border and inland into south central Queensland (Fig. 1). This region subdivides into northern and southern coastal subregions (bl = 0.03) and an inland (bl = 0.07; Fig 2) subregion. The Euronotian phytogeographical region (bl = 0.06) has a strong east subregion (bl = 0.16) to central-west subregion (bl = 0.12) structure (Fig. 2). Environmental correlates of the phytogeographical regions The environmental correlates of the six phytogeographical regions are shown in Table 4. The most extreme Gi* score was a precipitation trait for four of the six phytogeographical regions, while a temperature trait was the most extreme for the other two (see underlined values in Table 4). Species distribution and bioregions of Acacia and eucalypts in Australia are strongly influenced by annual precipitation and seasonal temperatures as well [18,19]. Precipitation and temperature seasonality are the environmen- tal variables that better correlate with turnover of the Northern phytogeographical region (which could be termed the ‘‘monsoonal Figure 2. Phytogeographical regions and new subregions region’’ environmentally). The Eremaean phytogeographical proposed for Australia (a), and their corresponding dendro- regions are differentiated by seasonality traits in the Northern gram (b). Note that the colors of the dendrogram clusters correspond Desert Region and annual precipitation in the Eremaean, to the colors of the subregions. Shaded colors indicate relationships: reflecting a possible Tropic of Capricorn division [10]. For the light blue and dark blue cluster together before clustering with brown Euronotian phytogeographical region, the amount of solar colours. doi:10.1371/journal.pone.0092558.g002 radiation and precipitation during the coldest quarter of the year PLOS ONE | www.plosone.org 5 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia Table 4. Gi* spatial statistics for the six phytogeographical regions of Australian flora. Bolded means statistically significant (a = 0.05). Northern Northern Eremaean Eastern Euronotian South-Western Environmental variable (N = 141) Desert (N = 185) (N = 317) Queensland (N = 43) (N = 114) (N = 70) Annual mean radiation 3.37 9.04 4.91 22.03 214.90 26.75 Annual mean temperature 12.69 11.66 22.55 20.82 217.02 28.45 Annual mean precipitation 17.69 24.89 215.45 5.01 6.86 21.78 Clay 22.28 1.16 2.05 3.85 0.37 25.81 Precipitation coldest quarter 27.31 27.76 25.51 1.83 16.26 9.71 Precipitation seasonality 17.38 13.23 212.83 21.61 212.59 23.84 Radiation seasonality 214.83 211.44 7.22 22.44 15.81 6.86 Ridge Top flatness 21.90 3.29 3.60 23.16 25.74 0.89 Rock grain size 1.52 24.71 20.20 20.89 21.31 7.70 Sand 3.31 0.78 22.26 22.79 21.84 2.85 Temperature seasonality 218.07 0.87 18.42 -0.86 24.80 22.77 N = number of grid cells per region. Underlined values are the most extreme scores for each region. doi:10.1371/journal.pone.0092558.t004 (winter) are the main environmental drivers. In the South-Western Spatial comparison of the new phytogeographical phytogeographical region precipitation in the coldest quarter, regions to biomes temperature, and landscape properties are the main drivers. Our results strongly reflect the northern tropical summer and southern temperate winter rainfall gradients. Precipitation is a Spatial comparison of the new phytogeographical more significant environmental correlate in the northern half of regions to the ABA terrestrial sub-regions the continent whereas high levels of solar radiation and cool Our phytogeographical regions resemble the nomenclature temperatures are more important below the Tropic of Capricorn. proposed by the terrestrial phytogeographical sub-regions of the However, annual precipitation is a predominant correlate of the ABA (Fig. 3c) [17] (Table 5). In numerical terms, the spatial coastal Queensland region where a tropical/sub-tropical transition agreement, between our phytogeographical regions (Fig 3a) and zone, the Eastern Queensland phytogeographical regions, is the ABA classification scheme is 65% (Fig 3c). This result created. represents a high level of agreement but there are still major gaps The north - south split between the Eremaean and Northern among many of the ABA subregions that we were able to fill using Desert Region roughly coincides with the Tropic of Capricorn and the species turnover approach. the summer-winter rainfall line (see Appendix S1 panel a). However, this split is not evident in the previously published biomes or bioregions of Australia (see Appendix S1 panels a-b-d) Discussion [10,4,44,49]. These biome descriptions, which are defined by both Our data suggest that the Northern region overlaps with the climate and biota, identify a large arid Eremaean region that is not ABA Kimberly Plateau, Arnhem Land, Cape York and Atherton split north to south into two regions as was found in our analysis. Plateau [in part] sub-regions and has a species composition more The Eremaean ‘‘zone is crossed obliquely by the junction between similar to the Northern Desert than to the more mesic the summer and winter rainfall systems but floristically the phytogeographic area along the eastern coast of Australia. The junction is not so strongly marked due to the presence of small Northern Desert phytogeographic region overlaps with some parts ranges of low mountains, which appear to have acted as refugia’’ of the Northern, Eastern and Western Desert ABA sub-regions. [10]. Our evidence suggests that the division line between The arid zone in our classification split into the Eremaean Eremaean and Northern Desert regions might be related to the (including the southern parts of the Eastern Desert and western effect of the Tropic of Capricorn, which may have resulted from Desert ABA sub-regions) as well as South-Western region, which is the palaeoclimatic shifts (warmer-cooler-warmer) during the last considered one of the world diversity hotspots. 65 Ma [58]. It was mentioned in a compilation of Australian These results are similar to the proposed ABA phytogeograph- phytogeography that ‘‘floristic composition from north to south is ical regions and sub-regions that have been in use for over 120 probably as closely related to temperature gradient and possibly years see [6,7,8,9,10,11,12,13]. However, because they are based also day length as to available rainfall’’ [10]. We also observed a on a rigorous quantitative analysis of a large data set, our results west-east climatic division within the Eremaean and Northern should be used to revise the ABA area taxonomy and area Desert regions. Our analysis identifies the Eastern Queensland as a boundaries as well as to extend sub-regions within the Eremaean separate phytogeographical region. This region can be described and Euronotian regions, so that all areas abut. The current climatically as an inter-zone defined by the summer-winter rainfall provisional area taxonomy within the ABA has few abutting sub- variation as previously noted in Burbidge’s biomes in Australia regions (see Figure 3b); our results can re-define these existing [10]. areas to create a more accurate area taxonomy for Australia’s phytogeographical regions and sub-regions. PLOS ONE | www.plosone.org 6 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia PLOS ONE | www.plosone.org 7 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia Figure 3. Spatial agreement between our six phytogeographical regions of Australian flora (a) and the terrestrial phytogeographical sub-regions of Australia (ABA) (b) [17]. Shown is the degree of spatial agreement of the ABA and our classification (c) and the percentage of overlap among each of our phytogeographical regions and the ABA sub-regions (d). Equivalent sub-regions from the ABA are noted below and as shown in Fig 2. The Northern Desert Region (red and blue: Northern Desert); Eremaean (red: Western Desert, blue: Eastern Desert); South-Western (blue & orange: Southwest Interzone); Euronotian (red: Eyre Peninsula and Adelaide [in part], blue: Victoria, Southeastern NSW, McPherson - Macleay Overlap [in part]); Eastern Queensland (blue: Atherton Tableland [in part], light blue: Eastern Queensland); Northern Region (red: Kimberley Plateau, orange: Arnhem Land, blue: Cape York Peninsula and Atherton Tableland in part). doi:10.1371/journal.pone.0092558.g003 species turnover can be used to successfully partition a Spatial comparison of the new phytogeographical continent into geographically meaningful regions using a regions to other classifications broad sample of plant groups. This analysis also demonstrates The comparison of our regions and sub-regions against that biogeographical regionalisation does not have to be geology [45], soils [46], and vegetation types [47] uncovered few convoluted and complex. With fewer factors involved, patterns congruent patterns (Appendix S1). The results align with the are easier to explain. For example, the strong evidence of the current distribution of major vegetation groups of Australia as relationship of sub-regions of species turnover with climatic cited by the National Vegetation Information Systems (NVIS) variables suggests that species assemblages across Australia [47]. Geology and soils are treated as artificial units (e.g., have responded to changes in weather systems across the Formations, Ferrosols etc.), rather than types of rock and soil continent. (e.g., sandstones, sandy loams) and therefore are unlikely to The phytogeographical regions presented here are defined overlap. However, general climatic maps correlate with our using species turnover and thus relate to taxonomic diversity in results. The six proposed floristic regions (see Appendix S1 the groups studied. Here, the taxonomic groups contain a panelc)closely agreewithKo ¨ ppen’s macro-climatic map of combination of recent (Acacia) and older clades (the bryophyte Australia (Appendix S1 panel e; http://www.bom.gov.au/ groups). It is probable that the recently diverged clades are climate/environ/other/kpn_group.shtml) [27]. Regarding Ko ¨p- driving the patterns identified because they comprise a large pen’s classification, the tropical zone (see Appendix S1, dark proportion of the species sampled. However, the older green in panel 3e) maps precisely with the Northern region, the bryophytic and pteridophytic clades do not have the same subtropical zone (see Appendix S1, light green in panel e) broad continental distributions of the younger clades studied matches well with our Eastern-Queensland region and the here, which may reflect recent distributional patterns that might temperateclimate group(seeAppendix S1,bluein panel e) fit not be shared with these older clades. If dominated by the well with our Euronotian region. The main inconsistency is with distributions of recently derived species, our results likely will the desert and grassland groups (see Appendix S1 orange and matchmodernclimaticzones,while older species might reflect yellow in panel e) where a split into grassland that covers semi- geological features, tectonic patterns or older palaeo-climatic arid areas is conspicuous, although these grassland areas zones. roughly agree with the eastern subregions of the Northern Given this, we highlight the importance of generating region- Desert and Eremaean regions. alizations based on large, multi-taxon datasets. Furthermore, basing floristic regions only on species turnover misses out on the Utilization of phytogeographical classifications full depth of phylogenetic information available. Future studies Our results support some previous biotic [57] and climatic should compare these results with patterns of spatial similarity classifications of Australia [10] but also disagree in some cases generated using measures of phylogenetic turnover [52], to obtain [59], and thus add new information to the biogeographical a better picture of the historical relationships among areas within literature. For example, our results suggest for the first time Australia. Understanding the adaptive changes in morphology and that the flora of arid Australia (Eremaean Region of the ABA) physiology that accompanied biome shifts will enable a broad can be divided into distinct phytogeographic regions, first understanding of the adaptive history of organisms and its along a north to south gradient and then along an east to west potential for adaptation in the face of human induced climate gradient, in contrast to some proposed biogeographic faunal change [56]. patterns [48]. We show that a unified method for quantifying Table 5. Area taxonomy overlaps between new areas and existing regions and sub-regions from the recently published Australian Bioregionalization Atlas (ABA) [17]. New Areas (this study) ABA Area Taxonomy Regions ABA Area Taxonomy Sub-regions Northern Desert Region Eremaean Northern Desert Eremaean Eremaean Western and Eastern Deserts South-Western Southwest Australia Southwest Interzone Euronotian McPherson - Macleay Overlap (in part), Southeastern NSW, Victoria, Adelaide (in part), Eyre Peninsula (in part). Northern Region Euronotian Kimberly Plateau, Arnhem Land, Cape York Peninsula, Atherton Tableland (in part) Eastern Queensland Euronotian Atherton Tableland (in part), Eastern Queensland Note that the new areas abut, while the ABA sub-regions are occasionally separated by undescribed areas (see gaps between regions in Figure 3b). doi:10.1371/journal.pone.0092558.t005 PLOS ONE | www.plosone.org 8 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia Supporting Information Acknowledgments We would like to thank the two Commonwealth Scientific and Industrial Appendix S1 Comparison of our six phytogeographical regions Research Organisation (CSIRO) internal reviewers for their valuable of Australian flora (c) against major biogeographical classifications comments. We would like to thank Bernd Gruber for supporting the spatial of Australia. Burbidges biomes [10] (a), Crisp et al biomes [49] (b), overlap analyses. BDM thanks CSIRO (Australia) for a Distinguished IBRA regions [4] (d) and Ko ¨ ppen’s macro-climatic map of Visiting Scientist Award. Australia (e). There is permission to re-print maps on panels A and B, and labels in panels D and E indicate the original publisher Author Contributions (official permission not required because is public material). Conceived and designed the experiments: CEGO MCE SL JTM. (TIF) Analyzed the data: CEGO SL JTM NJK. Contributed reagents/ materials/analysis tools: CEGO MCE SL AHT NJK ANSL CCC MC NSN BDM JTM. Wrote the paper: CEGO JTM SL MCE. References 1. Holt BG, Lessard JP, Borregaard MK, Fritz SA, Arau ´ jo MB, et al. (2013) An 25. Linder HP, Klerk HM, Born J, Burgess ND, Fjeldsa J, et al. (2012) The partitioning of Africa: statistically defined biogeographical regions in sub- update of Wallace’s Zoogeographic regions of the world. Science 339: 74–77. Saharan Africa. Journal of Biogeography 39: 1189–1205. 2. 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Quantifying Phytogeographical Regions of Australia Using Geospatial Turnover in Species Composition

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© 2014 Gonzalez-Orozco et al
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1932-6203
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1932-6203
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10.1371/journal.pone.0092558
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Abstract

The largest digitized dataset of land plant distributions in Australia assembled to date (750,741 georeferenced herbarium records; 6,043 species) was used to partition the Australian continent into phytogeographical regions. We used a set of six widely distributed vascular plant groups and three non-vascular plant groups which together occur in a variety of landscapes/habitats across Australia. Phytogeographical regions were identified using quantitative analyses of species turnover, the rate of change in species composition between sites, calculated as Simpson’s beta. We propose six major phytogeographical regions for Australia: Northern, Northern Desert, Eremaean, Eastern Queensland, Euronotian and South- Western. Our new phytogeographical regions show a spatial agreement of 65% with respect to previously defined phytogeographical regions of Australia. We also confirm that these new regions are in general agreement with the biomes of Australia and other contemporary biogeographical classifications. To assess the meaningfulness of the proposed phytogeographical regions, we evaluated how they relate to broad scale environmental gradients. Physiographic factors such as geology do not have a strong correspondence with our proposed regions. Instead, we identified climate as the main environmental driver. The use of an unprecedentedly large dataset of multiple plant groups, coupled with an explicit quantitative analysis, makes this study novel and allows an improved historical bioregionalization scheme for Australian plants. Our analyses show that: (1) there is considerable overlap between our results and older biogeographic classifications; (2) phytogeographical regions based on species turnover can be a powerful tool to further partition the landscape into meaningful units; (3) further studies using phylogenetic turnover metrics are needed to test the taxonomic areas. Citation: Gonza´lez-Orozco CE, Ebach MC, Laffan S, Thornhill AH, Knerr NJ, et al. (2014) Quantifying Phytogeographical Regions of Australia Using Geospatial Turnover in Species Composition. PLoS ONE 9(3): e92558. doi:10.1371/journal.pone.0092558 Editor: Ulrich Joger, State Natural History Museum, Germany Received August 14, 2013; Accepted February 25, 2014; Published March 21, 2014 Copyright:  2014 Gonzalez-Orozco et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: MCE’s contribution was supported under Australian Research Council’s ‘Future Fellow’ funding scheme (project number FT0992002). MCE and SWL also wish to thank the University of New South Wales, Australia for two Goldstar Grants (RG114989 & RG124461). The authors would like to thank Bernd Gruber for supporting the spatial overlap analyses. BDM thanks CSIRO (Australia) for a Distinguished Visiting Scientist Award. The authors acknowledge the support received from the Cancer Research UK and EPSRC Cancer Imaging Centre in association with the MRC and Department of Health (England) grant C1060/A10334, also NHS funding to the NIHR Biomedical Research Centre, MRC-funded studentship, also Chang Gung Medical Foundation (Taiwan) grants CMRPG370443 and CMRPG3B1922. MOL is an NIHR Senior Investigator. The authors thank Alice Warley at the Kings College London Centre for Ultrastructural Imaging (CUI) for assistance with electron microscopy. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript Competing Interests: The authors have declared that no competing interests exist. * E-mail: carlos.gonzalez-orozco@canberra.edu.au ¤ Current address: Institute for Applied Ecology and Collaborative Research Network for Murray-Darling Basin Futures, University of Canberra, Canberra, Australian Capital Territory, Australia ical regions) are defined on the distributions of specific taxonomic Introduction groups, and therefore are simpler to understand and to use The definition of biogeographical regions (also referred to as comparatively. bioregions) is fundamental for understanding the distribution of The history of Australian bioregionalization spans 190 years [6] biodiversity [1]. Bioregionalizations are important because they and may be divided into the colonial, post-federation, ecogeo- allow us to classify organisms into fundamental geographic units, graphical and systematic periods. The first attempt at a at different scales, to be used to establish global conservation bioregionalization classification of Australia was by Ferdinand agreements and to make diversity assessments [2,3,4,5]. The von Mueller in 1858, using vegetation types rather than taxic characteristics and terms used to define areas in biogeography are distributions [7]. In contrast, the naturalist Ralph Tate in 1889 not always used consistently (Table 1). For example, biomes are produced the first bioregionalization using a combination of taxic defined by both the climate and the types of organisms that have distributions and climate, coining the terms Eremaean and adapted to it and floristic zones are defined only by the types of Euronotian, both of which are still in use [8] and are also vegetation they contain. However, they are sometimes used used here. In 1933, during the Post-federation period, the interchangeably. Bioregions (phytogeographical and zoogeograph- PLOS ONE | www.plosone.org 1 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia Table 1. Glossary of terms. Term name Description Area The region of distribution of any taxonomic unit (species, genus, family) of the plant (or animal) world (Wulff 1950: 25) [51]. An endemic area is the geographical area to which a taxon or biota is understood to be native. (Parenti and Ebach 2009: 253) [50]. Biome Bioclimatic Zone. The geographical area defined by climate and the types of organisms that have adapted to it (e.g., mesic, arid). Biota A group of taxa (organisms), the combined distribution of which occupies a common set of geographical limits. (Parenti and Ebach 2009: 252) [50]. Biotic Area The geographical area inhabited by a biota. Limits of taxon distribution specify limits of the area (Parenti and Ebach 2009: 251) [50]. Biogeographical Region Bioregion or phytogeographical and zoological regions. The geographical area based on the distributions of specific taxonomic groups (e.g., plant or animal taxa). Vegetative (Floristic) Zone The geographical area defined by a particular type of vegetation (e.g., savannah, tundra, Mulga Scrub). The terms, regions, areas, and vegetation are often used inter-changeably, however, they do have specific meanings that we use herein with the following definitions. doi:10.1371/journal.pone.0092558.t001 zoogeographer G.E. Nicholls presented the first combined taxa has been used to identify phytogeographical regions of regionalization of Australian terrestrial flora and fauna [9]. plants across an entire continent such as Australia. Moreover, there has been no quantitative attempt to test existing Rather than adopt a combined bioregionalization, however, many Australian plant and animal geographers chose instead to phytogeographical regions that have been in use since the late th 19 century [8]. keep animal and plant distributions separate. Most important The method we apply to quantifying phytogeographical was Nancy Burbidge, who by the Ecogeographical Period regions is similar to recent zoogeographical studies [1,24]. developed her own regionalization consisting of areas that were Limited access to large nationally digitized spatial datasets is a largely based on Tate’s work [8] aswellasher expert knowledge likely reason why large studies do not exist on this topic. of flora distributions. Burbidge’s classification of Australia flora Australia is an exception because of the existence of Australia’s used the concept of interzones, that is, areas of overlap Virtual Herbarium AVH [31], which has digitized most (including the MacPherson-Macleay overlap zone), along with specimens housed in herbaria around Australia (http://www. three floristic zones (Temperate, Tropical and Eremaean) [10]. avh.ala.org.au/). This amalgamated database of herbarium Possibly the last continental bioregionalization of Australia’s records for an entire continent makes it possible to investigate flora was made by Dutch botanist Henk Doing in 1970, large scale patterns of plant distributions. In this paper we who created the first hierarchical classification of Australian used quantitative methods to prepare a phytogeographical flora according to vegetation type, communities and climate classification for the entire Australian continent using [11]. species turnover of nine major plant groups (Table 1) and to Other studies attempted to regionalize Australia through test the validity of an existing classification of Australia’s three using numerical, evidence-based data, such as Barlow’s 33 regions and 18 sub-regions. Our dataset contains representa- botanical regions derived from herbarium specimens [12]. By tives from diverse land plant groups (bryophytes, ferns, and the 1980s regionalization was done at the regional rather than angiosperms). continental level and many classifications ignored biotic areas in By first developing a species turnover-based phytogeographical favour of vegetative or climatic zones (i.e., biomes) [13]. classification, using taxonomic groups instead of climate, we are However, by thetimeofthe Systematic Period, particularly in then able to test how the environmental patterns, such as of theearly 1990s, therewas a resurgenceofbioticarea climate and soil types [19,20], fit the observed phytogeographical classification [14,15,16,17]. Of these new classifications, very regions. few were in agreement, leaving phytogeography with more areas The aims of this study were to: and area names than ever before [18]. In summary, there has to date been an accumulation of, often conflicting, area classifica- 1. Quantify and map the plant regions of Australia through tions, none of which were quantitatively produced or assessed. spatial analyses of modern databases of georeferenced Modern advances in the development of large databases of specimen data and compare these with the current phytogeo- georeferenced specimen observations, allied with concurrent graphical regionalization. improvements in spatial analysis tools, means that it is now 2. Identify what the major environmental drivers of species possible to quantitatively define and assess biotic regions turnover are for each of these phytogeographical regions. [19,20]. 3. Test the validity of previously proposed regions and sub- A key concept to define biogeographical regions (herein regions from the last 190 years, and propose an improved phytogeographical regions) is species turnover, which is the classification of the phytogeographical regions of Australia. rate of change in species composition between sites [21]. Species turnover has been used to generate classifications of bioregions [19,20,22,23,24,17] and there have been some Methods studies, for example, in sub-Saharan regions of Africa, wheremultipletaxa wereusedto successfullypartition the Spatial dataset continent into phytogeographical regions [25]. In other Table 2 summarizes the taxa and number of occurrence records cases, species turnover and multivariate statistical methods examined in this study. A total of 802,273 records were effectively diagnosed bioregions on different biological groups downloaded from Australia’s Virtual Herbarium (AVH) [31]. This [26,27,28,29,30]. However, no large dataset of geo-referenced dataset does not contain absence records, of course. Collections PLOS ONE | www.plosone.org 2 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia were mostly curated to the accepted taxonomy of the Australian Plant Census [32]. We did not consider any infra-specific taxa in a ðEq1:Þ b ~ 1{ sim the analysis. For each species, spatial errors were removed using az min (a,c) ArcGIS 9.2 [33]. The spelling and consistency of scientific names across taxa were corrected using Google Refine. Spatial outliers Where a refers to the number of species common to cells i and and all records without a geographic location were deleted. j, b is the number found in cell i but not cell j, and c is the Records that fell in the ocean or outside continental Australia number found in cell j but not cell i. A low b value indicates were excluded. After the correction process, 750,741 records sim that many taxa are shared between two grid cells (low remained for use in our final analyses. The geographic dissimilarity) and a high b means a small number of shared coordinates of each record were projected into an Albers equal sim taxa (high dissimilarity). area conic conformal coordinate system to avoid the latitudinal An agglomerative cluster analysis of the bsim turnover matrix biases of geographic coordinate systems. The records were was used to generate a WPGMA hierarchical cluster diagram in imported and aggregated to 100 km6100 km grid cells (870 in BIODIVERSE. Current literature suggests that dissimilarity clus- total) using BIODIVERSE 0.18 [34] (http://purl.org/biodiverse). tering algorithms are exposed to topology biases [55]. In order We calculated the ratio of species records to number of samples to reduce biases in our analyses, the cluster analysis included a per grid cell to measure redundancy, as an indicator of sample tie-breaker condition [18,19] such that, when more than one coverage [35]. We found that 70% of the analyzed grid cells had pair of sub-clusters had the same turnover score, the pair which a good level (60%) of species record redundancy within each grid had the highest Corrected Weighted Endemism (CWE) score cell (see Appendix S1). was selected for merging. This approach guarantees the same cluster result would be generated each time the model is run, as Taxonomic dataset well as increasing the endemicity of the resultant clusters. We The dataset included Australian representatives from a diverse identified the phytogeographical regions from the clusters based set of major terrestrial plant groups (bryophytes, ferns and several on two criteria: (1) a phytogeographical region is preferably large angiosperm genera and families) that represent a wide represented by a group of contiguous, or near-contiguous, grid geographic distribution across Australia [53,54]. For example, cells; (2) each cluster that represents a phytogeographical region Acacia and eucalypts are the most abundant canopy and sub- needs to be clearly separated from its children (immediate canopy woody plants in Australia [36,37,53]. One of the problems descendent nodes) or parent (immediate ancestral node) in the when gathering a large dataset is the reliability of the taxonomic dendrogram. identification. The more taxa included, the more challenging it becomes to achieve high taxonomic and spatial reliability of Spatial overlap analysis herbarium data. The strategy we applied was to utilize as many Our phytogeographical regions were visually compared with taxa as possible that combine a strong taxonomic tradition and several previous bioregionalizations of Australia. We also con- wide geographical ranges. Despite having experts on each group ducted a formalized comparison of the degree of overlap between involved in the cleaning process checking for taxonomic and our phytogeographical regions and the terrestrial phytogeograph- spatial errors in the sampled groups, we expect there to remain ical sub-regions proposed in the Australian Bioregionalization some low degree of taxonomic uncertainty. Atlas (ABA). This comparison used only the ABA because it is the existing classification that best reflects a historical viewpoint of Spatial analysis: bioregionalization geographical regionalizations of flora for Australia. Both classifi- All spatial analyses were conducted using BIODIVERSE [34]. A cations were converted to raster format with a resolution of matrix of species turnover was generated for all pair-wise 1006100 km. Because we aimed to identify phytogeographical combinations of grid cells (757,770 pairs). Simpson’s beta (b ) sim regions at the continental scale, a coarse grid cell size was applied. was used as the turnover measure because it corrects for species The effect of changes in grid cell size on the bioregions was richness differences between sites (Equation 1). explored in prior studies with eucalypts across Australia [19]. In that study we found no significant implications on the identifica- Table 2. The plant groups used in this study, number of occurrence points, and the number of species per group, with the totals. Taxon name Number of records Number of species Acacia 165,518 1,020 Asteraceae 105,692 823 Eucalypts (Angophora, Corymbia and Eucalyptus) 202,736 791 Ferns 58,774 356 Hornworts 370 13 Liverworts 16,502 735 Melaleuca 41,092 282 Mosses 79,210 835 Orchids 80,847 1,188 TOTAL 750,741 6,043 doi:10.1371/journal.pone.0092558.t002 PLOS ONE | www.plosone.org 3 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia tion of the major regions but some changes in the delimitation of environmental differences among the phytogeographic regions the regions boundaries occurred. The ABA sub-regions were then that were inferred from species turnover? overlaid on our phytogeographical regions using ArcMap 9.2 [33]. The gridded approach consists of three steps. First, summary The overall spatial agreement between both classification schemes statistics were calculated for 100 km6100 km grid cells of the (which differ in the number of classes and their extent) was eleven environmental variables in BIODIVERSE. Then, each of the calculated by the count of ABA sub-region cells that overlapped grid cells of the environmental variables were spatially linked to with only one of our regions and then divided by the total number each of the grid cells corresponding to the phytogeographic of cells in all ABA sub-regions. This value was summed up and regions. Finally, the association between the phytogeographical expressed as a percentage of overlap. regions and the environmental variables were calculated using Getis-Ord Gi* hotspot statistic spatial statistics in BIODIVERSE.We used the Getis-Ord Gi* hotspot statistic to assess if the Environmental correlates environmental values within the clusters (phytogeographic regions) Eleven environmental variables were used in this study (Table 3). were significantly different from those for the country as a whole A correlation matrix available on the spatial portal of the Atlas of [42,43]. The Gi* statistic is expressed as a z-score indicating the Living Australia was used to select variables which represented degree to which the values of a subset of grid cells, in this case the different environmental traits and demonstrated minimal correla- cells comprising a cluster, are greater or less than the mean of the tion. The spatial resolution of the layers was 1 km (approximately dataset. Those clusters with Gi* values greater than 2 or less than 0.01 degrees). The environmental layers were re-projected into the 22 represent sets of cells that have environmental values same Alber’s conic conformal coordinate system as the species significantly different from expected (a,0.05). data using the R software [38] and aggregated to 100 km6100 km grid cells using BIODIVERSE. The environmental variables were developed using ANUCLIM [39,40]. We also included four layers Results related to soils and topography, sourced from the National Land & Phytogeographical regions Water Resources Audit [41]. The mean value for each environ- We found and propose six phytogeographical regions: Northern mental variable within each 100 km6100 km grid cell was Region (Euronotian, Monsoonal Tropics and Monsoon sensu calculated using BIODIVERSE. [57,18,19]), Northern Desert Region (Eremaean North sensu Relative environmental turnover (RET) aims to identify [18,19], Eremaean (Eremaean South sensu [18,19]), Eastern phytogeographical regions based on species turnover and inves- Queensland (South-eastern Temperate and southeast sensu tigate their environmental correlates. It has been shown to be a [14,18,19] and South-Western (Southwest sensu [8]) (see Fig 1). useful method to partition the continent into meaningful The names of the proposed regions are aligned to correspond to phytogeographic regions in Acacia and eucalypts [18,19]. RET the Australian Bioregionalisation Atlas [17]. was derived from a framework to delineate biogeographic regions Overall, the spatial arrangement of the phytogeographical initially proposed by Kreft & Jetz [23]. Previous studies used the regions follows a distinctive north to south pattern, with an east to term environmental turnover to explore rates of change of west pattern at the sub-regional level. The phytogeographical dissimilarity in vertebrates and their relationship to environment regions are nested in geographically related pairs. The first split is depending on the geographic distance [24]. RET is different from of the Northern and Northern Desert regions (branch length (bl) of previous approaches because it is not geographic distance based, 0.09; dendrogram in Fig 1) from the other four regions. The but instead combines grid cell analyses with ordinations. RET Northern is on a long branch (bl = 0.12) and readily subdivided consist of two parts, one is an ordination and the second is a east (bl = 0.09) to west (bl = 0.03; Fig 2). The region with the gridded analysis. Here, we only used the gridded component of highest species similarity to the Northern is the Northern Desert RET. The key question addressed is what are the main Table 3. Environmental variables used in our analyses. Environmental variable Description Annual precipitation Monthly precipitation estimates (mm) Annual mean temperature The mean of the week’s maximum and minimum temperature (uC) Annual mean radiation The mean of all the weekly radiation estimates (Mj/m /day) Precipitation of coldest quarter Total precipitation over the coldest period of the year Radiation seasonality Standard deviation of the weekly radiation estimates expressed as a percentage of the annual mean (Mj/ m /day) Precipitation seasonality Standard deviation of the weekly precipitation estimates expressed as a percentage of the annual mean (mm) Temperature seasonality Standard deviation of the weekly mean temperatures estimates expressed as a percentage of the annual mean (uC) Ridge top flatness Metric of the topographic flatness derived from a surface of 9 second grid cells (dimensionless) Rock grain size Lithological property of the bedrocks related to the mean grain size (0–10 units) Sand Content of sand on the top 30 cm of soil layer estimated from soil maps at a resolution of 1 km (%) Clay Content of clay on the top 30 cm of soil layer estimated from soil maps at a resolution of 1 km (%) doi:10.1371/journal.pone.0092558.t003 PLOS ONE | www.plosone.org 4 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia Figure 1. Phytogeographical regions of Australian terrestrial flora (a) as defined by the corresponding dendrogram (b). The colors of the regions in the map correspond to those used to plot the dendrogram. The dendrogram is a representation of the spatial relationship of dissimilarities in species composition among regions. doi:10.1371/journal.pone.0092558.g001 Region (bl = 0.08; Fig 1). This phytogeographical region also has a clear east (bl = 0.05) to west subdivision (bl = 0.08; Fig 2). The other major cluster has a short branch (bl = 0.03). The largest clustering of grid cells is the Eremaean phytogeographical region which shares a very short branch (bl = 0.01) with the South- Western phytogeographical region (Fig 1). The Eremaean is on a long branch (0.08) and subdivides east (bl = 0.07) to west (bl = 0.04; Fig 2). The South-Western phytogeographical region is also on a long branch (bl = 0.11) and is subdivided into three coastal (bl = 0.02) subregions and an inland (bl = 0.04) subregion (Fig 2). The Euronotian and Eastern-Queensland phytogeographical regions cluster together (bl = 0.03). The Eastern Queensland phytogeographical region (bl = 0.24) runs along the eastern coast of Queensland from the Wet Tropics to the New South Wales border and inland into south central Queensland (Fig. 1). This region subdivides into northern and southern coastal subregions (bl = 0.03) and an inland (bl = 0.07; Fig 2) subregion. The Euronotian phytogeographical region (bl = 0.06) has a strong east subregion (bl = 0.16) to central-west subregion (bl = 0.12) structure (Fig. 2). Environmental correlates of the phytogeographical regions The environmental correlates of the six phytogeographical regions are shown in Table 4. The most extreme Gi* score was a precipitation trait for four of the six phytogeographical regions, while a temperature trait was the most extreme for the other two (see underlined values in Table 4). Species distribution and bioregions of Acacia and eucalypts in Australia are strongly influenced by annual precipitation and seasonal temperatures as well [18,19]. Precipitation and temperature seasonality are the environmen- tal variables that better correlate with turnover of the Northern phytogeographical region (which could be termed the ‘‘monsoonal Figure 2. Phytogeographical regions and new subregions region’’ environmentally). The Eremaean phytogeographical proposed for Australia (a), and their corresponding dendro- regions are differentiated by seasonality traits in the Northern gram (b). Note that the colors of the dendrogram clusters correspond Desert Region and annual precipitation in the Eremaean, to the colors of the subregions. Shaded colors indicate relationships: reflecting a possible Tropic of Capricorn division [10]. For the light blue and dark blue cluster together before clustering with brown Euronotian phytogeographical region, the amount of solar colours. doi:10.1371/journal.pone.0092558.g002 radiation and precipitation during the coldest quarter of the year PLOS ONE | www.plosone.org 5 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia Table 4. Gi* spatial statistics for the six phytogeographical regions of Australian flora. Bolded means statistically significant (a = 0.05). Northern Northern Eremaean Eastern Euronotian South-Western Environmental variable (N = 141) Desert (N = 185) (N = 317) Queensland (N = 43) (N = 114) (N = 70) Annual mean radiation 3.37 9.04 4.91 22.03 214.90 26.75 Annual mean temperature 12.69 11.66 22.55 20.82 217.02 28.45 Annual mean precipitation 17.69 24.89 215.45 5.01 6.86 21.78 Clay 22.28 1.16 2.05 3.85 0.37 25.81 Precipitation coldest quarter 27.31 27.76 25.51 1.83 16.26 9.71 Precipitation seasonality 17.38 13.23 212.83 21.61 212.59 23.84 Radiation seasonality 214.83 211.44 7.22 22.44 15.81 6.86 Ridge Top flatness 21.90 3.29 3.60 23.16 25.74 0.89 Rock grain size 1.52 24.71 20.20 20.89 21.31 7.70 Sand 3.31 0.78 22.26 22.79 21.84 2.85 Temperature seasonality 218.07 0.87 18.42 -0.86 24.80 22.77 N = number of grid cells per region. Underlined values are the most extreme scores for each region. doi:10.1371/journal.pone.0092558.t004 (winter) are the main environmental drivers. In the South-Western Spatial comparison of the new phytogeographical phytogeographical region precipitation in the coldest quarter, regions to biomes temperature, and landscape properties are the main drivers. Our results strongly reflect the northern tropical summer and southern temperate winter rainfall gradients. Precipitation is a Spatial comparison of the new phytogeographical more significant environmental correlate in the northern half of regions to the ABA terrestrial sub-regions the continent whereas high levels of solar radiation and cool Our phytogeographical regions resemble the nomenclature temperatures are more important below the Tropic of Capricorn. proposed by the terrestrial phytogeographical sub-regions of the However, annual precipitation is a predominant correlate of the ABA (Fig. 3c) [17] (Table 5). In numerical terms, the spatial coastal Queensland region where a tropical/sub-tropical transition agreement, between our phytogeographical regions (Fig 3a) and zone, the Eastern Queensland phytogeographical regions, is the ABA classification scheme is 65% (Fig 3c). This result created. represents a high level of agreement but there are still major gaps The north - south split between the Eremaean and Northern among many of the ABA subregions that we were able to fill using Desert Region roughly coincides with the Tropic of Capricorn and the species turnover approach. the summer-winter rainfall line (see Appendix S1 panel a). However, this split is not evident in the previously published biomes or bioregions of Australia (see Appendix S1 panels a-b-d) Discussion [10,4,44,49]. These biome descriptions, which are defined by both Our data suggest that the Northern region overlaps with the climate and biota, identify a large arid Eremaean region that is not ABA Kimberly Plateau, Arnhem Land, Cape York and Atherton split north to south into two regions as was found in our analysis. Plateau [in part] sub-regions and has a species composition more The Eremaean ‘‘zone is crossed obliquely by the junction between similar to the Northern Desert than to the more mesic the summer and winter rainfall systems but floristically the phytogeographic area along the eastern coast of Australia. The junction is not so strongly marked due to the presence of small Northern Desert phytogeographic region overlaps with some parts ranges of low mountains, which appear to have acted as refugia’’ of the Northern, Eastern and Western Desert ABA sub-regions. [10]. Our evidence suggests that the division line between The arid zone in our classification split into the Eremaean Eremaean and Northern Desert regions might be related to the (including the southern parts of the Eastern Desert and western effect of the Tropic of Capricorn, which may have resulted from Desert ABA sub-regions) as well as South-Western region, which is the palaeoclimatic shifts (warmer-cooler-warmer) during the last considered one of the world diversity hotspots. 65 Ma [58]. It was mentioned in a compilation of Australian These results are similar to the proposed ABA phytogeograph- phytogeography that ‘‘floristic composition from north to south is ical regions and sub-regions that have been in use for over 120 probably as closely related to temperature gradient and possibly years see [6,7,8,9,10,11,12,13]. However, because they are based also day length as to available rainfall’’ [10]. We also observed a on a rigorous quantitative analysis of a large data set, our results west-east climatic division within the Eremaean and Northern should be used to revise the ABA area taxonomy and area Desert regions. Our analysis identifies the Eastern Queensland as a boundaries as well as to extend sub-regions within the Eremaean separate phytogeographical region. This region can be described and Euronotian regions, so that all areas abut. The current climatically as an inter-zone defined by the summer-winter rainfall provisional area taxonomy within the ABA has few abutting sub- variation as previously noted in Burbidge’s biomes in Australia regions (see Figure 3b); our results can re-define these existing [10]. areas to create a more accurate area taxonomy for Australia’s phytogeographical regions and sub-regions. PLOS ONE | www.plosone.org 6 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia PLOS ONE | www.plosone.org 7 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia Figure 3. Spatial agreement between our six phytogeographical regions of Australian flora (a) and the terrestrial phytogeographical sub-regions of Australia (ABA) (b) [17]. Shown is the degree of spatial agreement of the ABA and our classification (c) and the percentage of overlap among each of our phytogeographical regions and the ABA sub-regions (d). Equivalent sub-regions from the ABA are noted below and as shown in Fig 2. The Northern Desert Region (red and blue: Northern Desert); Eremaean (red: Western Desert, blue: Eastern Desert); South-Western (blue & orange: Southwest Interzone); Euronotian (red: Eyre Peninsula and Adelaide [in part], blue: Victoria, Southeastern NSW, McPherson - Macleay Overlap [in part]); Eastern Queensland (blue: Atherton Tableland [in part], light blue: Eastern Queensland); Northern Region (red: Kimberley Plateau, orange: Arnhem Land, blue: Cape York Peninsula and Atherton Tableland in part). doi:10.1371/journal.pone.0092558.g003 species turnover can be used to successfully partition a Spatial comparison of the new phytogeographical continent into geographically meaningful regions using a regions to other classifications broad sample of plant groups. This analysis also demonstrates The comparison of our regions and sub-regions against that biogeographical regionalisation does not have to be geology [45], soils [46], and vegetation types [47] uncovered few convoluted and complex. With fewer factors involved, patterns congruent patterns (Appendix S1). The results align with the are easier to explain. For example, the strong evidence of the current distribution of major vegetation groups of Australia as relationship of sub-regions of species turnover with climatic cited by the National Vegetation Information Systems (NVIS) variables suggests that species assemblages across Australia [47]. Geology and soils are treated as artificial units (e.g., have responded to changes in weather systems across the Formations, Ferrosols etc.), rather than types of rock and soil continent. (e.g., sandstones, sandy loams) and therefore are unlikely to The phytogeographical regions presented here are defined overlap. However, general climatic maps correlate with our using species turnover and thus relate to taxonomic diversity in results. The six proposed floristic regions (see Appendix S1 the groups studied. Here, the taxonomic groups contain a panelc)closely agreewithKo ¨ ppen’s macro-climatic map of combination of recent (Acacia) and older clades (the bryophyte Australia (Appendix S1 panel e; http://www.bom.gov.au/ groups). It is probable that the recently diverged clades are climate/environ/other/kpn_group.shtml) [27]. Regarding Ko ¨p- driving the patterns identified because they comprise a large pen’s classification, the tropical zone (see Appendix S1, dark proportion of the species sampled. However, the older green in panel 3e) maps precisely with the Northern region, the bryophytic and pteridophytic clades do not have the same subtropical zone (see Appendix S1, light green in panel e) broad continental distributions of the younger clades studied matches well with our Eastern-Queensland region and the here, which may reflect recent distributional patterns that might temperateclimate group(seeAppendix S1,bluein panel e) fit not be shared with these older clades. If dominated by the well with our Euronotian region. The main inconsistency is with distributions of recently derived species, our results likely will the desert and grassland groups (see Appendix S1 orange and matchmodernclimaticzones,while older species might reflect yellow in panel e) where a split into grassland that covers semi- geological features, tectonic patterns or older palaeo-climatic arid areas is conspicuous, although these grassland areas zones. roughly agree with the eastern subregions of the Northern Given this, we highlight the importance of generating region- Desert and Eremaean regions. alizations based on large, multi-taxon datasets. Furthermore, basing floristic regions only on species turnover misses out on the Utilization of phytogeographical classifications full depth of phylogenetic information available. Future studies Our results support some previous biotic [57] and climatic should compare these results with patterns of spatial similarity classifications of Australia [10] but also disagree in some cases generated using measures of phylogenetic turnover [52], to obtain [59], and thus add new information to the biogeographical a better picture of the historical relationships among areas within literature. For example, our results suggest for the first time Australia. Understanding the adaptive changes in morphology and that the flora of arid Australia (Eremaean Region of the ABA) physiology that accompanied biome shifts will enable a broad can be divided into distinct phytogeographic regions, first understanding of the adaptive history of organisms and its along a north to south gradient and then along an east to west potential for adaptation in the face of human induced climate gradient, in contrast to some proposed biogeographic faunal change [56]. patterns [48]. We show that a unified method for quantifying Table 5. Area taxonomy overlaps between new areas and existing regions and sub-regions from the recently published Australian Bioregionalization Atlas (ABA) [17]. New Areas (this study) ABA Area Taxonomy Regions ABA Area Taxonomy Sub-regions Northern Desert Region Eremaean Northern Desert Eremaean Eremaean Western and Eastern Deserts South-Western Southwest Australia Southwest Interzone Euronotian McPherson - Macleay Overlap (in part), Southeastern NSW, Victoria, Adelaide (in part), Eyre Peninsula (in part). Northern Region Euronotian Kimberly Plateau, Arnhem Land, Cape York Peninsula, Atherton Tableland (in part) Eastern Queensland Euronotian Atherton Tableland (in part), Eastern Queensland Note that the new areas abut, while the ABA sub-regions are occasionally separated by undescribed areas (see gaps between regions in Figure 3b). doi:10.1371/journal.pone.0092558.t005 PLOS ONE | www.plosone.org 8 March 2014 | Volume 9 | Issue 3 | e92558 Phytogeographical Regions of Australia Supporting Information Acknowledgments We would like to thank the two Commonwealth Scientific and Industrial Appendix S1 Comparison of our six phytogeographical regions Research Organisation (CSIRO) internal reviewers for their valuable of Australian flora (c) against major biogeographical classifications comments. We would like to thank Bernd Gruber for supporting the spatial of Australia. Burbidges biomes [10] (a), Crisp et al biomes [49] (b), overlap analyses. 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