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Conditions conducive to fires are becoming increasingly common and widespread under climate change. Recent fire events across the globe have occurred over unprecedented scales, affecting a diverse array of species and habitats. Understanding biodiversity responses to such fires is critical for conservation. Quantifying post‐fire recovery is problematic across taxa, from insects to plants to vertebrates, especially at large geographic scales. Novel datasets can address this challenge. We use presence‐only citizen science data from iNaturalist, collected before and after the 2019–2020 megafires in burnt and unburnt regions of eastern Australia, to quantify the effect of post‐fire diversity responses, up to 18 months post‐fire. The geographic, temporal, and taxonomic sampling of this dataset was large, but sampling effort and species discoverability were unevenly spread. We used rarefaction and prediction (iNEXT) with which we controlled sampling completeness among treatments, to estimate diversity indices (Hill numbers: q = 0–2) among nine broad taxon groupings and seven habitats, including 3885 species. We estimated an increase in species diversity up to 18 months after the 2019–2020 Australian megafires in regions which were burnt, compared to before the fires in burnt and unburnt regions. Diversity estimates in dry sclerophyll forest matched and likely drove this overall increase post‐fire, while no taxon groupings showed clear increases inconsistent with both control treatments post‐fire. Compared to unburnt regions, overall diversity across all taxon groupings and habitats greatly decreased in areas exposed to extreme fire severity. Post‐fire life histories are complex and species detectability is an important consideration in all post‐fire sampling. We demonstrate how fire characteristics, distinct taxa, and habitat influence biodiversity, as seen in local‐scale datasets. Further integration of large‐scale datasets with small‐scale studies will lead to a more robust understanding of fire recovery. [ABSTRACT FROM AUTHOR]

Banksia L.f., an iconic genus of the Proteaceae, is endemic to Australia, with its highest species richness and phylogenetic diversity (PD) in southwestern Western Australia. Analysis of the phylogenetic component of richness and endemism uncovered important patterns of Banksia evolutionary history that are not seen at the species level. We found that Banksia is significantly phylogenetically clustered in this region, likely due to recent evolutionary radiations. We also found significant concentrations of phylogenetic endemism in this region, both neoendemism (short, range‐restricted evolutionary branches) and paleoendemism (long, range‐restricted evolutionary branches). There is a striking northwest to southeast divide in phyloturnover in southwestern Western Australia. The majority of the variation in turnover patterns can be explained by environmental factors, with climate representing the largest covariate. This study adds to the growing body of evidence that indicates the importance of integrating phylogenetic and biodiversity data to inform conservation planning. [ABSTRACT FROM AUTHOR]

Aim: Leaf pubescence has several important roles, including regulating heat balance, reducing damage from UV radiation, minimizing water loss and reducing herbivory. Each of these functions could affect a plant's ability to tolerate the biotic and abiotic stresses encountered in different parts of the world. However, we know remarkably little about large scale biogeographic patterns in leaf pubescence. Our aims were: (a) to determine whether a higher proportion of species have pubescence at sites where it is hot, dry and solar radiation is high, and (b) to quantify the latitudinal gradient in pubescence. Location: Australia. Taxon: Vascular land plants. Methods: We compiled data on the presence/absence of pubescence on mature photosynthetic organs for 4,183 species, spanning 107 families. We combined these data with over 1.9 million species occurrence records from the Atlas of Living Australia to calculate the proportion of species with pubescence in 3,261 grid cells spanning the Australian continent. Results: The proportion of pubescent species was most closely related to solar radiation (R2 = 0.33), followed by maximum temperature in the warmest month (R2 = 0.30). Mean annual precipitation was very weakly related to pubescence (R2 = 0.01). We found a significant negative relationship between latitude and pubescence (R2 = 0.19), with the average percentage of species with pubescence dropping from 46% at 10° S to 35% at 44° S. This cross‐species relationship remained significant after accounting for phylogenetic relationships between species. We found that a quadratic model explained more variation in pubescence across latitudes than did a linear model. The quadratic model shows a peak in the proportion of pubescent species at 19° S (within the tropics). Main conclusions: Our findings are consistent with the idea that leaf pubescence may have a protective function in areas with high solar radiation and high temperatures. Our data are also consistent with the idea that species towards the tropics should be better defended than are species at higher latitudes. [ABSTRACT FROM AUTHOR]

We present the largest comparative biogeographical analysis that has complete coverage of Australia's geography (20 phytogeographical subregions), using the most complete published molecular phylogenies to date of large Australian plant clades (Acacia, Banksia and the eucalypts). Two distinct sets of areas within the Australian flora were recovered, using distributional data from the Australasian Virtual Herbarium (AVH) and the Atlas of Living Australia (ALA): younger Temperate, Eremaean and Monsoonal biomes, and older southwest + west, southeast and northern historical biogeographical regions. The analyses showed that by partitioning the data into two sets, using either a Majority or a Frequency method to select taxon distributions, two equally valid results were found. The dataset that used a Frequency method discovered general area cladograms that resolved patterns of the Australian biomes, whereas if widespread taxa (Majority method, with >50% of occurrences outside a single subregion) were removed the analysis then recovered historical biogeographical regions. The study highlights the need for caution when processing taxon distributions prior to analysis as, in the case of the history of Australian phytogeography, the validity of both biomes and historical areas have been called into question. [ABSTRACT FROM AUTHOR]

The Australian freshwater fish fauna is very unique, but poorly understood. In the Australian Monsoonal Tropics (AMT) biome of northern Australia, the number of described and candidate species has nearly doubled since the last attempt to analyse freshwater fish species composition patterns and determine a bioregionalisation scheme. Here, we utilise the most complete database of catchment‐scale freshwater fish distributions from the AMT to date to: (a) reanalyze spatial patterns of species richness, endemism and turnover of freshwater fishes; (b) propose a biogeographic regionalisation based on species turnover; (c) assess the relationship between species turnover and patterns of environmental change and historic drainage connectivity; and (d) identify sampling gaps. Biogeographic provinces were identified using an agglomerative cluster analysis of a Simpson's beta (βsim) dissimilarity matrix. A generalised dissimilarity model incorporating eighteen environmental variables was used to investigate the environmental correlates of species turnover. Observed and estimated species richness and endemism were calculated and inventory completeness was estimated based on the ratio of observed to estimated species richness. Three major freshwater fish biogeographic provinces and 14 subprovinces are proposed. These differ substantially from the current bioregionalisation scheme. Species turnover was most strongly influenced by environmental variables that are interpreted to reflect changes in terrain (catchment relief and confinement), geology and climate (runoff perenniality, stream density), and biotic responses to climate (net primary productivity). Past connectivity between rivers during low sea‐level events is also influential highlighting the importance of historical processes in explaining contemporary patterns of biodiversity in the AMT. The inclusion of 49 newly discovered species and candidate species only reinforced known focal points of species richness and endemism in the AMT. However, a number of key sampling gaps remain that need to be filled to fully characterise the proposed bioregionalisation. [ABSTRACT FROM AUTHOR]

Aim Ecosystem functions such as productivity may be influenced not only by the biological diversity at each location (α-diversity) but also by the biological turnover between locations (β-diversity). We perform a continental-scale test of the strength and direction of relationships between gross primary productivity (GPP) and both α- and β-diversity. Location Continental Australia. Methods Species occurrence records were used to quantify the taxonomic α-diversity of vascular plants in approximately 11,000 1 km × 1 km grid cells across Australia, and to calculate the average β-diversity within a 10-km radius around each cell. The magnitude and variability of monthly, MODIS-derived remotely sensed GPP (2001-12) were summarized for continental Australia, as were rainfall and temperature over the same period. Generalized additive models were then used to test whether the magnitude or variability of GPP were distinctly influenced by either biodiversity measure, over and above the influence of environmental conditions. Results Precipitation and temperature explained large proportions of deviance in the magnitude (75.6%) and variability (38.3%) of GPP across the Australian continent. GPP was marginally more strongly related to species richness than it was to species turnover. However, neither diversity measure provided substantial increases in the explanatory power of GPP models over and above that of environment-only models (always < 1%). Main conclusions The relationship between primary productivity and taxonomic α- and β-diversity was weak for the Australian flora. Our findings question the generality of key assumptions, predictions and results in the literature regarding the strength of empirical relationships between productivity and biodiversity across multiple biological levels (α-, β- and γ-diversity) at macroecological scales. [ABSTRACT FROM AUTHOR]

Aim Biodiversity studies typically use species, or more recently phylogenetic diversity ( PD), as their analysis unit and produce a single map of observed diversity. However, observed biodiversity is not necessarily an indicator of significant biodiversity and therefore should not be used alone. By applying a small number of additional metrics to PD, with associated statistical tests, we can determine whether more or less of the phylogeny occurs in an area, whether branch lengths in an area are longer or shorter, and whether more long or short-branched endemism occurs in an area, than expected under a null model. Location Australian continent. Methods We used a phylogeny sampling 90% of Australia's angiosperm genera, and 3.4 million georeferenced plant specimens downloaded from Australia's Virtual Herbarium ( AVH), to calculate PD, relative phylogenetic diversity ( RPD) and relative phylogenetic endemism ( RPE). Categorical analysis of neo- and palaeo-endemism ( CANAPE) and randomization tests were performed to determine statistical significance. Results We identify several combinations of significant PD and endemism across the continent that are not seen using observed diversity patterns alone. Joint interpretation of these combinations complements the previous interpretations of Australia's plant evolutionary history. Of conservation concern, only 42% of the significant endemism cells found here overlap with existing nature reserves. Main conclusions These spatial phylogenetic methods are feasible to apply to a whole flora at the continental scale. Observed richness or PD is inadequate to fully understand the patterns of biodiversity. The combination of statistical tests applied here can be used to better explain biodiversity patterns and the evolutionary and ecological processes that have created them. The spatial phylogenetic methods used in this paper can be also be used to identify conservation priorities at any geographical scale or taxonomic level. [ABSTRACT FROM AUTHOR]

Compared to species turnover, patterns of phylogenetic turnover provide extra information about the spatial structure of biodiversity, for example providing more informative comparisons between the biota of sites which share no species. To harness this information for broad-scale spatial analysis, we present phylo-GDM, a technique for interpolating the spatial structure of phylogenetic turnover between sampled locations in relation to environment, based on generalised dissimilarity modelling (GDM). Using a database of over 150 000 location records for 114 myobatrachid frog species in Australia, linked to a species-level phylogeny inferred from 2467 base pairs of mitochondrial DNA, we calculated species and phylogenetic turnover between pairs of sites. We show how phylogenetic turnover extended the range of informative comparison of compositional turnover to more biologically and environmentally dissimilar sites. We generated GDM models which predict species and phylogenetic turnover across Australia, and tested the fit of models for different ages within the phylogeny to find the phylogenetic tree depth at which the relationship to current day environment is greatest. We also incorporated explanatory variables based on biogeographic patterns, to represent broad-scale turnover resulting from divergent evolutionary histories. We found that while the predictive power of our models was lower for full phylogenetic turnover than for species turnover, models based on the more recent components of the phylogeny (closer to the tips) outperformed species models and full phylogenetic models. Phylo-GDM has considerable potential as a method for incorporating phylogenetic relationships into biodiversity analyses in ways not previously possible. Because phylogenies do not require named taxa, phylo-GDM may also provide a means of including lineages with poorly resolved taxonomy (e.g. from metagenomic sequencing) into biodiversity planning and phylogeographic analysis. [ABSTRACT FROM AUTHOR]

Aim To develop a biogeographical regionalization of Australian Acacia species and to investigate their environmental correlates. Location Australia. Methods We used a previously published framework for delineating biogeographical regions. We calculated species turnover patterns of 1020 Australian Acacia species with distributions estimated from 171,758 georeferenced herbarium records aggregated to 100 km × 100 km cells (868 across Australia). An agglomerative cluster analysis using a matrix of pairwise Simpson's beta (βsim) dissimilarity values was applied. Eleven environmental variables at the same resolution as the aggregated herbarium records were used to explore the correlates of the βsim patterns using a non-metric multidimensional scaling ( NMDS) analysis. We also used an ANOVA to test the significance of the environmental changes between each pair of biogeographical regions. Results Five major Acacia biogeographical regions were proposed. These bioregions were broadly similar to the biomes of Australia. A new subdivision of the Eremaean biome was proposed for Acacia. The most influential environmental variables for the individual bioregions were: (1) temperature seasonality and topographic flatness for the south-western temperate bioregion; (2) precipitation during the coldest quarter of the year for the south-eastern temperate bioregion; (3) annual precipitation, annual mean temperature and precipitation seasonality for the monsoonal bioregion; and (4) percentage of sand in the top 30 cm of the soil, rock grain size, annual mean radiation and annual mean temperature for the Eremaean south and north regions. The NMDS analysis provided support for the observed biogeographical patterns. The statistical test showed a highly significant difference between the environments of the proposed bioregions. Climatic variables were consistent predictors across regions, whereas the influence of soils and topographic features varied among bioregions. Main conclusions The major Acacia biogeographical regions correspond well to historical bioregionalizations, suggesting that the environmental drivers of diversification in Acacia are broadly similar to those that act on the flora as a whole. Climate seasonality combined with annual values and non-climatic factors provide support for the proposed biogeographical regionalization for Acacia. [ABSTRACT FROM AUTHOR]

Aim We assess how much of species' ranges are present within protected areas and how different land units within protected areas contribute to overall protection, both within their region and at continental scales. We do this using the plant family Myrtaceae in relation to the globally important Greater Blue Mountains World Heritage Area ( GBMWHA) in New South Wales, Australia. Location South-eastern Australia. Methods Compiling data throughout the region and nationally, we considered two spatially based quantitative measures of endemism (relative range restriction): weighted endemism ( WE) and corrected weighted endemism ( CWE). In both measures, species are weighted by the proportion of their ranges found within the analysis window, with the ranges calculated as the total number of cells in which they occur (10 km × 10 km in this research). We also derived a novel expectation for the contribution of each species to the endemism scores at each taxonomic level based on the additive properties of the metrics and their relationship to species richness. We used this expectation to assess the proportional contribution of each genus to the endemism scores. Results The degree to which Myrtaceae species within the GBMWHA are endemic to the GBMWHA area is 16%, meaning that an average of 16% of the ranges of species found in the GBMWHA are restricted to that area. The figure for those species with ranges less than or equal to the median (80 cells) is 33%. The genus Eucalyptus contributes the most to the endemism scores obtained, but no more than would be expected given its number of species. The genus Leptospermum is 3.7% less restricted to the GBMWHA than would be expected, while the genus Melaleuca is 5% more restricted than expected. Main conclusions Centres of high endemism within the GBMWHA and surrounds were identified. This research presents a template for quantifying endemism for regions at local to global scales. Spatially-based quantitative measures of endemism, such as outlined here, are an important means to quantify and visualize these aspects of conservation significance for the management of protected areas. [ABSTRACT FROM AUTHOR]

Levees, channels and water storages built on the world's floodplain wetlands control flows for irrigation, flood mitigation and erosion management. Assessing their distribution and hydrological impacts through time and across broad extents is limited by significant costs and technical challenges. We tested the effectiveness of three new semi-automated geographic information systems and traditional visual interpretation techniques for detecting earthworks. We used commercially or freely available two-dimensional and three-dimensional spatial imagery within 19 quadrats in an agricultural floodplain of the Murray-Darling Basin, southeastern Australia. Semi-automated digital elevation model (DEM) analysis performed best for spatial accuracy (78% of earthworks correctly predicted within 25 m), overall classification accuracy (97.7%) and kappa (0.64), compared with traditional visual interpretation techniques using Landsat TM (52%, 96.3%, 0.39), SPOT (53%, 95.8%, 0.27) and aerial photography (72%, 97.2%, 0.31). DEM analysis also outperformed semi-automated image segmentation (16%, 93%, 0.29) and integrated analysis (75%, 96.0%, 0.43) that used spectral information. Semi-automated techniques were slow (DEM analysis: 27 418 s/km2; integrated analysis: 27 737 s/km2; and image segmentation: 1439 s/km2) compared with visual interpretation (Landsat TM: 109 s/km2; SPOT: 166 s/km2; and aerial photography: 276 s/km2); however, processing speed of semi-automated techniques can be further increased without compromising accuracy. Semi-automated techniques also offered operational autonomy following model calibration. High quality, cost-effective earthwork mapping techniques, particularly the semi-automated techniques in this study, are critical for understanding and managing ecosystem health, flood risk and water security in developed floodplains worldwide and should be implemented by governing institutions. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Aim We introduce a method to quantify shared breaks in aggregate biotic distributions and their relationships to geographic variables. The method is based on quantification of distributional taxic and abiotic data that can be applied over multiple spatial scales. We aim to show biogeographic breaks and varying transition zones at a fine level of detail (5-km resolution) and develop an approach to assess existing bioregionalization schemes. Location Global applicability, using an example from New South Wales in south-eastern Australia. Methods Moving window analyses, rotated in 15° increments through 360°, are used to assess the degree of anisotropic spatial turnover between sets of gridded cells containing georeferenced species observations. Patterns of biotic turnover are compared with equivalent analyses for elevation and lithology. Identified breaks are assessed against an existing bioregionalization scheme (Interim Biogeographic Regionalisation of Australia, IBRA). Results There was fine-scale concordance between turnover patterns and several IBRA bioregions. Breaks in turnover of flora and fauna corresponded with the boundaries of the Hunter Valley and Sydney Basin regions, particularly the boundary between the Brigalow Belt South and Sydney Basin. Low-turnover zones were quantified; prominent examples are the Sydney Cataract and Wyong bioregions. Turnover along many boundaries was gradational, confirming that mapped breaks are not abrupt. A previously unidentified break was identified in the South East Corner bioregion. Spatial turnover patterns were similar between biota and were reflected in mean correlation coefficients between turnover in each group: mammals-reptiles ( r = 0.70, P << 0.01); mammals-flora ( r = 0.56, P << 0.01); and reptiles-flora ( r = 0.51, P << 0.01). Generally, patterns of abiotic turnover reflected biotic turnover, although mean turnover correlations were weaker than between biota. Main conclusions Using this method we were able to characterize taxic breaks and overlaps in detail and at a spatially fine resolution. For our study region, we confirm the overall integrity of the IBRA framework, but suggest that it may benefit from revision in some respects. [ABSTRACT FROM AUTHOR]

To reconstruct an indigenous language known solely from historical wordlists, the linguist needs to decide which source wordlists are most relevant, i.e. which sources are most likely to be attestations of the language to be reconstructed. There is little published research on methods appropriate to this task, and yet there is increasing attention to indigenous language reconstruction in support of language revival and revitalisation in education and community contexts. This paper 1 describes a replicable and relatively objective method for comparing lexical similarity within a set of historical sources. The method described draws on the use of measures of lexical similarity in linguistics and the use of measures of endemism in biogeography. The method is illustrated via an analysis of historical sources for Aboriginal languages from the greater Sydney region, New South Wales, Australia. The sample is used to describe the overall similarity and difference between wordlists from this region, and to identify which wordlists are most similar to the wordlist recorded by the surveyor R. H. Mathews (e.g. 1903) as Darkinyung language. [ABSTRACT FROM AUTHOR]

Question: Predictive vegetation modelling relies on the use of environmental variables, which are usually derived from abase data set with some level of error, and this error is propagated to any subsequently derived environmental variables. The question for this study is: What is the level of error and uncertainty in environmental variables based on the error propagated from a Digital Elevation Model (DEM) and how does it vary for both direct and indirect variables? Location: Kioloa region, New South Wales, Australia Methods: The level of error in a DEM is assessed and used to develop an error model for analysing error propagation to derived environmental variables. We tested both indirect (elevation, slope, aspect, topographic position) and direct (aver- age air temperature, net solar radiation, and topographic wetness index) variables for their robustness to propagated error from the DEM. Results: It is shown that the direct environmental variable net solar radiation is less affected by error in the DEM than the indirect variables aspect and slope, but that regional conditions such as slope steepness and cloudiness can influence this outcome. However, the indirect environmental variable topographic position was less affected by error in the DEM than topographic wetness index. Interestingly, the results disagreed with the current assumption that indirect variables are necessarily less sensitive to propagated error because they are less derived. Conclusions: The results indicate that variables exhibit both systematic bias and instability under uncertainty. There is a clear need to consider the sensitivity of variables to error in their base data sets in addition to the question of whether to use direct or indirect variables. [ABSTRACT FROM AUTHOR]

The aim of this research is to develop and investigate methods for the spatial analysis of diversity based on genetic and taxonomic units of difference. We use monophyletic groups of species to assess the potential for these diversity indices to elucidate the geographical components of macro-scaled evolutionary processes.The range occupied byPultenaeaspecies in temperate and sub-tropical eastern Australia, extending from western South Australia (133° E–32° S) to Tasmania (146° E–43° S) to coastal central Queensland (148° E–20° S).We applied a series of both spatially explicit and spatially implicit analyses to explore the nature of diversity patterns in the genusPultenaea, Fabaceae. We first analysed the eastern species as a whole and then the phylogenetic groups within them. We delineated patterns of endemism and biotic (taxon) regions that have been traditionally circumscribed in biogeographical studies of taxa. Centres of endemism were calculated using corrected weighted endemism at a range of spatial scales. Biotic regions were defined by comparing the similarity of species assemblages of grid cells using the Jaccard index and clustering similar cells using hierarchical clustering. On the basis that genetically coherent areas were likely to be more evolutionary informative than species patterns, genetic indices of similarity and difference were derived. A matrix of similarity distances between taxa was generated based on the number of shared informative characters of two sections oftrnL-FandndhFchloroplast nuclear regions. To identify genetically similar areas, we clustered cells using the mean genetic similarities of the species contained within each pair of cells. Measures of the mean genetic similarity of species in areas were delineated using a geographically local multi-scalar approach. Resultant patterns of genetic diversity are interpreted in relation to theories of the evolutionary relationships between species and species groups.Centres ofPultenaeaendemism were defined, those of clades 1 congruent with the spatially separated centres of clades 2 and 3. The taxonomic classification analysis defined cells with shared groups of species, which in some cases clustered when plotted in geographic space, defining biotic regions. In some instances the distribution of biotic regions was congruent with centres of endemism, however larger scale groupings were also apparent. In clade 1 one set of species was replaced by another along the extent of the range, with some connectivity between some geographically disjunct regions due to the presence of widespread species. In the combined analysis of clade 2 and 3 species the major biotic (taxonomic) groups with geographic coherence were defined by species in the respective clades, representing the geographic separation of these clades. However distinctive biotic regions within these main groupings of clades 2 and 3 were also apparent. Clustering cells using the mean genetic similarities of the species contained within each pair of cells indicated that some of the taxonomically defined biotic boundaries were the result of changes in composition of closely related species. This was most apparent in clades 1 and 2 where most cells were highly genetically similar. In clade 3 genetically distinct groups remained and were in part defined by sister taxa with disjunct distributions. Gradients in mean genetic similarity became more apparent from small to larger scales of analysis. At larger scales of analysis, regions of different levels of genetic diversity were delineated. Regions with highest diversity levels (lowest level of similarity) often represented regions where the ranges of phylogenetically distinctive species intergraded.The combined analysis of diversity, phylogeny and geography has potential to reveal macro-scaled evolutionary patterns from which evolutionary processes may be inferred. The spatial genetic diversity indices developed in this study contribute new methods for identifying coherent evolutionary units in the landscape, which overcome some of the limitations of using taxonomic data, and from which the role of geography in evolutionary processes can be tested. We also conclude that a multiple-index approach to diversity pattern analysis is useful, especially where patterns may be the result of a long history of different environmental changes and related evolutionary events. The analysis contributes to the knowledge of large-scale diversity patterns ofPultenaeawhich has relevance for the assessment of the conservation status of the genus. [ABSTRACT FROM AUTHOR]

Abstract Aim To develop an approach for assessing the spatial scale of centres of endemism among species level data. Location Australia. Methods Endemism is inherently scale dependent. Therefore, the Corrected Weighted Endemism (CWE) index used by Crisp et al. [J. Biogeogr. (2001)28:183] is extended to account for species samples in local neighbourhoods as a Spatial CWE index. This then allows an analysis of how the degree of endemism of a location (cell) changes with spatial scale. The quality of the Spatial CWE index results are assessed using three spatial randomizations at the species level with and without preserving species richness and distributional patterns. We show that CWE is equivalent to beta diversity and predict that it should show high rates of change around centres of endemism. Results Similar patterns to those found by Crisp et al. using a data set of vascular flora from Australia are retrieved, but the extent to which they are scale dependent is more easily identified. For example, the Central Australian centre discounted by Crisp et al. is identified when a three-cell radius neighbourhood is used. However, the level of endemism in this centre is no greater than in the margins of many of the coastal centres of endemism. Most of the identified centres of endemism are better than random at all scales and are increasingly so as the spatial scale increases. As predicted, the highest rate of change in Spatial CWE (beta diversity) is most often between zero- and one-cell radius neighbours in most centres of endemism. Main conclusions The explicit incorporation of geographical space in analyses allows for a greater understanding of the scale-dependence of phenomena, in this case endemism and beta diversity. [ABSTRACT FROM AUTHOR]