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Biodiversity has typically been quantified using species richness, but this ignores evolutionary history. Due to the increasing availability of robust phylogenies, methods have been developed that incorporate phylogenetic relationships into quantification of biodiversity. CANAPE (categorical analysis of neo‐ and paleo‐endemism) is one such method that can provide insight into the evolutionary processes generating biodiversity. The only currently available software implementing CANAPE is Biodiverse, which is written in Perl and can be used either through a graphical user interface (GUI) or user‐developed scripts. However, many researchers, particularly in the fields of ecology and evolutionary biology, use the R programming language to conduct their analyses. Here, we present canaper, a new R package (www.r‐project.org) that provides functions to conduct CANAPE in R. canaper implements methods for efficient computation, including parallelization and encoding of community data as sparse matrices. The interface is designed for maximum simplicity and reproducibility; CANAPE can be conducted with two functions, and parallel computing can be enabled with one line of code. Our case study shows that canaper produces equivalent results to Biodiverse and can complete computations on moderately sized datasets quickly (<10 min to reproduce a canonical study). canaper allows researchers to conduct all analyses from data import and cleaning through CANAPE within R, thereby obviating the need to manually import and export data and analysis results between programs. We anticipate canaper will become a part of the toolkit for analyzing biodiversity in R. [ABSTRACT FROM AUTHOR]

Abstract: Recent floristic efforts in the Pacific Northwest (PNW) have now made it possible to characterize the broad‐scale patterns of fern and lycophyte diversity across this large and geologically‐complex region of western North America. The physiography of the PNW has been developing for over 200 million years, but Pleistocene glaciation‐induced migrations and recolonizations have strongly influenced the assembly of the flora. With the high dispersal potential of fern and lycophyte spores, the distribution patterns of pteridophytes may be representative of habitat suitability more than dispersal constraints. Our objective was to describe the biodiversity of pteridophytes in the PNW, determine the spatial distribution of that biodiversity in terms of phylogenetic diversity, identify centers of regional endemism, explore the correlations between biodiversity and environmental variables, and infer possible influences of past glaciation on the pteridophyte flora. We obtained presence‐only distribution data from two online databases. A phylogenetic tree was constructed using chloroplast DNA sequence data from GenBank. We used the Biodiverse software package to estimate and map phylogenetic diversity and phylogenetic endemism across the PNW, and to identify those regions of the PNW where diversity was higher or lower than expected in comparison to randomization models. Environmental correlates of diversity were identified using principal components analysis with bioclimatic data from WorldClim.org, and we used Maxent to predict habitat suitability for species under past and future climate conditions. We found evidence for the influence of past glaciations and glacial refugia on the patterns of pteridophyte diversity, that moisture availability and cold temperatures are strongly correlated with patterns of genus richness, phylogenetic diversity, and phylogenetic endemism. We infer that the topographic complexity of the region may be driving the assembly of the pteridophyte flora indirectly by influencing climate and precipitation patterns. [ABSTRACT FROM AUTHOR]

Objectives: We quantify spatial turnover in communities of 1939 plant and 59 mammal species at 2.5 km resolution across a topographically heterogeneous region in south-eastern Australia to identify distributional breaks and low turnover zones where multiple species distributions overlap. Environmental turnover is measured to determine how climate, topography and geology influence biotic turnover differently across a variety of biogeographic breaks and overlaps. We identify the genera driving turnover and confirm the versatility of this approach across spatial scales and locations. Methods: Directional moving window analyses, rotated through 360°, were used to measure spatial turnover variation in different directions between gridded cells containing georeferenced plant and mammal occurrences and environmental variables. Generalised linear models were used to compare taxic turnover results with equivalent analyses for geology, regolith weathering, elevation, slope, solar radiation, annual precipitation and annual mean temperature, both uniformly across the entire study area and by stratifying it into zones of high and low turnover. Identified breaks and transitions were compared to a conservation bioregionalisation framework widely used in Australia. Results/Significance: Detailed delineations of plant and mammal turnover zones with gradational boundaries denoted subtle variation in species assemblages. Turnover patterns often diverged from bioregion boundaries, though plant turnover adhered most closely. A prominent break zone contained either comparable or greater numbers of unique genera than adjacent overlaps, but these were concentrated in a small subsection relatively under-protected by conservation reserves. The environmental correlates of biotic turnover varied for different turnover zones in different subsections of the study area. Topography and temperature showed much stronger relationships with plant turnover in a topographically complex overlap, relative to a lowland overlap where weathering was most predictive. This method can quantify transitional turnover patterns from small to broad extents, at different resolutions for any location, and complements broad-scale bioregionalisation schemes in conservation planning. [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]

Biodiverse is a tool for the spatial analysis of diversity using indices based on taxonomic, phylogenetic and matrix (e.g. genetic dissimilarity) relationships. The explosion in georeferenced biological specimen and survey data means there is an increasing need for such tools. Biodiverse supports four processes: 1) linked visualisation of data distributions in geographic, taxonomic, phylogenetic and matrix spaces; 2) spatial moving window analyses including richness, endemism, phylogenetic diversity and beta diversity; 3) spatially constrained agglomerative cluster analyses; and 4) randomisations for hypothesis testing. Biodiverse is open-source and supports user developed extensions. It can be used both through a graphical user interface and scripts. Biodiverse can be downloaded from <>. [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]

The flora of China is well known for its high diversity and endemism. Identifying centers of endemism and designating conservation priorities are essential goals for biodiversity studies. However, there is no comprehensive study from a rigorous phylogenetic perspective to understand patterns of diversity and endemism and to guide biodiversity conservation in China. We conducted a spatial phylogenetic analysis of the Chinese angiosperm flora at the generic level to identify centers of neo‐ and paleo‐endemism. Our results indicate that: (i) the majority of grid cells in China with significantly high phylogenetic endemism (PE) were located in the mountainous regions; (ii) four of the nine centers of endemism recognized, located in northern and western China, were recognized for the first time; (iii) arid and semiarid regions in Northwest China were commonly linked to significant PE, consistent with other spatial phylogenetic studies worldwide; and (iv) six high‐priority conservation gaps were detected by overlaying the boundaries of China's nature reserves on all significant PE cells. Overall, we conclude that the mountains of southern and northern China contain both paleo‐endemics (ancient relictual lineages) and neo‐endemics (recently diverged lineages). The areas we highlight as conservation priorities are important for broad‐scale planning, especially in the context of evolutionary history preservation. [ABSTRACT FROM AUTHOR]

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]

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. [ABSTRACT FROM AUTHOR]

Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was to better understand how infectious disease persists in wildlife populations by integrating genetics, ecology and epidemiology approaches. Specifically, we aimed to determine whether environmental or host factors were stronger drivers of Salmonella persistence or transmission within a remote and isolated wild pig (Sus scrofa) population. We determined the Salmonella infection status of wild pigs. Salmonella isolates were genotyped and a range of data was collected on putative risk factors for Salmonella transmission. We a priori identified several plausible biological hypotheses for Salmonella prevalence (cross sectional study design) versus transmission (molecular case series study design) and fit the data to these models. There were 543 wild pig Salmonella observations, sampled at 93 unique locations. Salmonella prevalence was 41% (95% confidence interval [CI]: 37-45%). The median Salmonella DICE coefficient (or Salmonella genetic similarity) was 52% (interquartile range [IQR]: 42-62%). Using the traditional cross sectional prevalence study design, the only supported model was based on the hypothesis that abundance of available ecological resources determines Salmonella prevalence in wild pigs. In the molecular study design, spatial proximity and herd membership as well as some individual risk factors (sex, condition score and relative density) determined transmission between pigs. Traditional cross sectional surveys and molecular epidemiological approaches are complementary and together can enhance understanding of disease ecology: abundance of ecological resources critical for wildlife influences Salmonella prevalence, whereas Salmonella transmission is driven by local spatial, social, density and individual factors, rather than resources. This enhanced understanding has implications for the control of diseases in wildlife populations. Attempts to manage wildlife disease using simplistic density approaches do not acknowledge the complexity of disease ecology. [ABSTRACT FROM AUTHOR]

North America is a large continent with extensive climatic, geological, soil, and biological diversity. As biota faces threat from habitat destruction and climate change, making a quantitative assessment of biodiversity becomes critically important. Rapid digitization of plant specimen records and accumulation of DNA sequence data enable a much‐needed broad synthesis of species occurrences with phylogenetic data. In this study, the first such synthesis of a flora from such a large and diverse part of the world is attempted, all seed plants from the North American continent (here defined to include Canada, United States, and Mexico), with a focus on examining phylogenetic diversity and endemism. We collected digitized plant specimen records and chose a coarse grain for analysis, recognizing that this grain is currently necessary for reasonable completeness per sampling unit. We found that raw richness and endemism patterns largely support previous hypotheses of biodiversity hotspots. The application of phylogenetic metrics and a randomization test revealed novel results, including a significant phylogenetic clustering across the continent, a striking east–west geographical difference in the distribution of branch lengths, and the discovery of centers of neo‐ and paleoendemism in Mexico, the southwestern USA, and the southeastern USA. Finally, our examination of phylogenetic beta diversity provides a new approach to compare centers of endemism. We discuss the empirical challenges of working at the continental scale and the need for more sampling across large parts of the continent, for both DNA data for terminal taxa and spatial data for poorly understood regions, to confirm and extend these results. [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]

Conserving different spatial and temporal dimensions of biological diversity is considered necessary for maintaining ecosystem functions under predicted global change scenarios. Recent work has shifted the focus from spatially local ( α-diversity) to macroecological scales ( β- and γ-diversity), emphasizing links between macroecological biodiversity and ecosystem functions ( MB- EF relationships). However, before the outcomes of MB- EF analyses can be useful to real-world decisions, empirical modeling needs to be developed for natural ecosystems, incorporating a broader range of data inputs, environmental change scenarios, underlying mechanisms, and predictions. We outline the key conceptual and technical challenges currently faced in developing such models and in testing and calibrating the relationships assumed in these models using data from real ecosystems. These challenges are explored in relation to two potential MB- EF mechanisms: 'macroecological complementarity' and 'spatiotemporal compensation.' Several regions have been sufficiently well studied over space and time to robustly test these mechanisms by combining cutting-edge spatiotemporal methods with remotely sensed data, including plant community data sets in Australia, Europe, and North America. Assessing empirical MB- EF relationships at broad spatiotemporal scales will be crucial in ensuring these macroecological processes can be adequately considered in the management of biodiversity and ecosystem functions under global change. [ABSTRACT FROM AUTHOR]

Advances in computing power and infrastructure, increases in the number and size of ecological and environmental datasets, and the number and type of data collection methods, are revolutionizing the field of Ecology. To integrate these advances, virtual laboratories offer a unique tool to facilitate, expedite, and accelerate research into the impacts of climate change on biodiversity. We introduce the uniquely cloud-based Biodiversity and Climate Change Virtual Laboratory (BCCVL), which provides access to numerous species distribution modelling tools; a large and growing collection of biological, climate, and other environmental datasets; and a variety of experiment types to conduct research into the impact of climate change on biodiversity. Users can upload and share datasets, potentially increasing collaboration, cross-fertilisation of ideas, and innovation among the user community. Feedback confirms that the BCCVL's goals of lowering the technical requirements for species distribution modelling, and reducing time spent on such research, are being met. [ABSTRACT FROM AUTHOR]

Identifying geographical areas with the greatest representation of the tree of life is an important goal for the management and conservation of biodiversity. While there are methods available for using a single phylogenetic tree to assess spatial patterns of biodiversity, there has been limited exploration of how separate phylogenies from multiple taxonomic groups can be used jointly to map diversity and endemism. Here, we demonstrate how to apply different phylogenetic approaches to assess biodiversity across multiple taxonomic groups. We map spatial patterns of phylogenetic diversity/endemism to identify concordant areas with the greatest representation of biodiversity across multiple taxa and demonstrate the approach by applying it to the Murray-Darling basin region of southeastern Australia. The areas with significant centers of phylogenetic diversity and endemism were distributed differently for the five taxonomic groups studied (plant genera, fish, tree frogs, acacias, and eucalypts); no strong shared patterns across all five groups emerged. However, congruence was apparent between some groups in some parts of the basin. The northern region of the basin emerges from the analysis as a priority area for future conservation initiatives focused on eucalypts and tree frogs. The southern region is particularly important for conservation of the evolutionary heritage of plants and fishes. [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]