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The impact of urban expansion on achieving sustainable development goals (SDGs) has become a significant research topic in the field of geographic information science. In this article, we describe a coupled cellular automata (CA)—‐What If? model to explore SDG11 “Sustainable cities and communities.” The model calculates overall residential land use demand based on historical data archives using the What If? planning support system (PSS), and then allocates it using a CA model that incorporates variables related to SDG11.2.1 and 11.7.1. Historical datasets for years 2016 and 2021 from Southwest Sydney, Australia were used to assess model accuracy, after which two residential expansion scenarios (years 2021 and 2026) were generated. Based on the modeling results, the SDG‐related spatial variables can improve the overall accuracy of CA sub‐models using an XGBoost machine learning training methodology. The simulation results of these scenarios confirm the effectiveness of the coupled CA‐What If? model, which has the potential to generate more reliable scenario results than the standalone What If? PSS for modeling urban growth of cities across Australia and internationally. [ABSTRACT FROM AUTHOR]

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]

Many modern planning systems aim to reduce average within-city commuting time to 30 min or less, a concept termed the 30-minute city. However, travel time for many large cities exceeds planning targets, and this can subsequently affect commuter health and wellbeing. Although data is often lacking for the 'first-mile' and 'last-mile' segments of public transport journeys, realistic calculations of the 30-minute city and other chrono-urbanism targets need to include door-to-door travel time. Here, we describe an approach to estimate door-to-door public transport travel time by enriching a synthetic population with smart card data without the need for mobile phone or travel survey data. The algorithm is applied to Sydney, Australia, and is used to measure how effectively a chrono-urbanism target is met in terms of door-to-door travel time compared to travel time without the first- and last-mile. Only 21.7% of validated commuters were modelled to have door-to-door travel time of 30 min or less for the journey to work. This is substantially lower than the 62.0% estimated using calculations without the first- and last-mile. [ABSTRACT FROM AUTHOR]

Greater public transport use may occur through meeting average travel times of 30 min or less, termed the "30-min city". The quantification of public transport-related physical activity associated with the 30-min city is under-researched but needed to support policy interventions. In this study, latent walking steps associated with modal shifts from car use to public transport/walking are investigated using a synthetic population and trip planning tool in Sydney, Australia. Areas were identified where the largest opportunities for public and active transport investments could be made in terms of density of car commuters and potential physical activity. Analysis of socio-economics with mean potential steps and with mean travel times were also conducted. Mode shifts to public transport/walking that are within 30 min one-way commute time were associated with a mean of 1732 daily potential steps per car commuter. However, 57 % of car commuters do not have a potential public transport/walking alternative that can be made within 30 min, which supports the need to reorganise jobs and housing and/or invest in faster public transport modes. A focus should be on delivering interventions in areas with excessive commuting times. Interactive visualisations are presented to aid policymakers to encourage mode shifts to public transport/walking. • Potential 2427 daily steps if car commuters shifted to public transport/walking. • Potential 1732 daily steps for 30-min city shifts to public transport/walking. • No 30-min public transport/walking alternatives for 57 % of car commuters. [ABSTRACT FROM AUTHOR]

A key component of cellular automata (CA) models is the transition rules that determine the transformation of cells at each iteration. However, most previous studies use a single set of transition rules across the entire study region, and therefore do not fully account for spatial heterogeneity. In this research, a vector CA model has been implemented that calibrates transition rules by taking the entire study region and partitioned sub‐regions into consideration. The changes in residential areas were modelled for the city of Ipswich, Queensland, Australia, from 1999 to 2016. The results confirm that the spatially partitioned rules can generate more accurate and stable results compared to calibrated rules using the whole study area, with an increase of mean producer's spatial accuracy of 72.07 and 75.59% in two sub‐regions (2‐2 and 2‐3). The implementation of CA models with partitioned transition rules enables a better understanding of spatial heterogeneity in land use change. [ABSTRACT FROM AUTHOR]

• Long-term monitored cave drip water hydrology time-series for years 2014–––2017. • Functional Principal Component Analysis (FPCA) identified modes of drip variation. • Three flow types classified: storage baseflow, fracture baseflow, and overflow. • FPCA results are validated with stable isotope drip water data. Understanding the mechanisms controlling spatial heterogeneity of drip water percolation into caves is essential for interpreting karst aquifer recharge and speleothem isotopic and geochemical records for paleoclimate analyses. Here we present the first analysis of drip rate variability using a novel time-varying Functional Principal Component Analysis (FPCA), validated against drip water stable isotope composition. Twenty-six drip sites were monitored across Harrie Wood Cave, south-east Australia, over a 2.5 year period. A positive relationship of cave drip water hydrology with precipitation and soil moisture was identified, with soil moisture recording the strongest relationship. FPCA was used to classify drip-water flow (percolation) pathways based on temporal shifts in the drip rate time series. Our results reveal that three percolation classes can be used to explain water movement within the cave: storage baseflow, fracture baseflow and overflow. The successful application of FPCA in this study suggests that this statistical technique will be useful for the analysis and interpretation of other large, discontinuous hydrological datasets. [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]

This is the Fifth Special Issue on Spatial Ecology in the International Journal of Geographical Information Science, following issues previously published in 2011, 2012, 2014, and 2016 (Skidmore I et al i . Movement ecology has emerged as a prominent focus in this issue, reflecting its rapid growth as a subfield of ecology (Nathan I et al i . Species distribution and diversity, habitat selection and connectivity: introduction to the third special issue on spatial ecology. Towards an integrated science of movement: converging research on animal movement ecology and human mobility science. [Extracted from the article]

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]

Aim Conservation is often prioritized by identifying regional clusters of threatened or endemic species. Another approach is to assess the evolutionary distinctiveness of groups of taxa using phylodiversity measures. However, quantification of evolutionary history has traditionally not accounted for its uneven geographical distribution due to the variation in species ranges. We assess the efficacy of phylogenetic endemism ( PE) to predict high extinction risk in comparison to estimates of species range restriction (weighted endemism, WE) and phylogenetic diversity ( PD). PE measures the relative range restriction of evolutionary history (lineages), while WE concentrates on the tips of the tree of life, treating all such branches as being of equal length. Location/Methods Using New Zealand's endemic skinks and geckos, we mapped the geographical variation in their extinction risk, PE, WE and PD and measured the extent to which extinction risk exhibited phylogenetic clustering for each group. Correlations between geographical concentrations of high skink and gecko extinction risk with PE, WE and PD were calculated. Results PE was predictive of spatial clusters of high extinction risk for geckos ( r2 = 0.34, P < 0.001) while WE was markedly less so ( r2 = 0.19, P < 0.001). The reverse applied to skinks, with WE most predictive of high risk ( r2 = 0.26, P < 0.001). The phylogenetic signal of extinction risk was significantly conserved for geckos, but was weaker and non-significant for skinks. PE and WE were not predictive of low risk. PD was not predictive of risk. Main conclusions PE and related measures may be predictive of extinction risk when risk is phylogenetically conserved. Mapping the geographical variation in PE could be a useful first assessment of extinction risk for many groups because phylogenies are increasingly available, while full risk status categories are not. These findings might apply to other groups and locations and warrant further investigation. [ABSTRACT FROM AUTHOR]

Background: Low phosphorus (P) soils have been described as a widespread characteristic of the Australian continent and associated with sclerophyll leaf traits. In that context we ask: what proportion of the continent is low-P and how much does this vary between regions? Methods: 9234 locations sampled for soil total P from the Australian National Site Soil Data Collation were analysed. In order to make some adjustment for uneven spatial sampling we area-weighted the data using subregions from the Interim Bioregionalisation of Australia. Results: Topsoil total P concentrations ≤100 mg kg were widespread, but not a majority of the continent (estimated 25 %). The western Monsoon Tropics (65 %), southwestern Australia (50 %), and southeast South Australia (38 %) were estimated to have larger fractions of the sampled landscape ≤100 mg kg than eastern Australia (13.5 %), but not a lower range of values. Total P values across the continent included a large fraction (33 %) in the range 101-250 mg kg. Conclusions: Continent-wide soil P levels low enough to favour long leaf lifespans for nutrient conservation and a variety of sclerophyll traits were widespread. It is time to move away from the qualitative dichotomies between low- and high-P that have characterised discussion of Australian vegetation, to a more quantitative view. [ABSTRACT FROM AUTHOR]

Patterns in space use and activity were compared for wild and hatchery-reared Mulloway ( Argyrosomus japonicus ) using acoustic telemetry. Acoustic tags were implanted in four wild (42 ± 2 cm; mean ± SE), and four hatchery-reared (42 ± 1 cm; mean ± SE) Mulloway, and movements were simultaneously monitored for up to 288 h in an 11 km section of river. Across all fish, space utilisation contours developed from weighted kernel density estimates ranged between 2–51 ha (90% or total area) and 1–28 ha (50% or core area), and contained up to 99% optimal habitat area. Hatchery-reared fish used significantly larger total and core areas, and activity rates of hatchery-reared fish were consistently higher than wild fish. A period of settlement or acclimation appeared to occur during the first 5 days following release for hatchery-reared fish, and their movement tended to contract back to within the habitat patch into which they were released from the 6–12th day following release. The movement ranges of wild fish were largely invariant between the two periods. The relevance of this research to understanding broader ecological processes is discussed. Acoustic telemetry presents a useful approach for studying post-release dynamics of hatchery-reared fish and their wild counterparts. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including human-wildlife interactions and conflicts in space and time, the use of toponyms as a means of identifying historical vegetation types and the continued use of cost-path analysis in spatial ecology to represent landscape connectivity.

Phylodiversity measures summarise the phylogenetic diversity patterns of groups of organisms. By using branches of the tree of life, rather than its tips (e.g., species), phylodiversity measures provide important additional information about biodiversity that can improve conservation policy and outcomes. As a biodiverse nation with a strong legislative and policy framework, Australia provides an opportunity to use phylogenetic information to inform conservation decision-making. We explored the application of phylodiversity measures across Australia with a focus on two highly biodiverse regions, the south west of Western Australia (SWWA) and the South East Queensland bioregion (SEQ). We analysed seven diverse groups of organisms spanning five separate phyla on the evolutionary tree of life, the plant genera Acacia and Daviesia , mammals, hylid frogs, myobatrachid frogs, passerine birds, and camaenid land snails. We measured species richness, weighted species endemism (WE) and two phylodiversity measures, phylogenetic diversity (PD) and phylogenetic endemism (PE), as well as their respective complementarity scores (a measure of gains and losses) at 20 km resolution. Higher PD was identified within SEQ for all fauna groups, whereas more PD was found in SWWA for both plant groups. PD and PD complementarity were strongly correlated with species richness and species complementarity for most groups but less so for plants. PD and PE were found to complement traditional species-based measures for all groups studied: PD and PE follow similar spatial patterns to richness and WE, but highlighted different areas that would not be identified by conventional species-based biodiversity analyses alone. The application of phylodiversity measures, particularly the novel weighted complementary measures considered here, in conservation can enhance protection of the evolutionary history that contributes to present day biodiversity values of areas. Phylogenetic measures in conservation can include important elements of biodiversity in conservation planning, such as evolutionary potential and feature diversity that will improve decision-making and lead to better biodiversity conservation outcomes. [ABSTRACT FROM AUTHOR]

We assessed the human impact on regions identified as the environmental central niche for the chacma baboon (Papio ursinus) across southern Africa. This central niche is the area within an animal's natural range that is most insulated from changes to the environmental variables that influence that animal's distribution. We used an environmental envelope model constructed with geographic information system software to predict the geographic extent of the central niche. The predicted chacma baboon central niche was 389 000 km2, with substantial overlap with human settlements in several countries. Of note is that although Botswana contains nearly 60 000 km2 of predicted central niche, the International Union for the Conservation of Nature chacma baboon distribution map implies that much of this area is uninhabited by baboons. A regional assessment of the province of KwaZulu-Natal (South Africa) suggests more than 95% of its central niche is uninhabited. Additionally, the very limited and likely disturbed central niche area in Lesotho coupled with the unknown status of chacma baboons within Lesotho warrants further attention. Overall, it appears likely that significant proportions of the predicted central niche in southern Africa are currently uninhabited by the chacma baboon. These uninhabited areas correspond with areas of high human population density and anthropogenic land alteration. The remaining central niche areas that are still inhabited are potentially key areas for conservation and are important for ensuring the sustainability of future populations. However, these areas may be undergoing degradation whilst also becoming more inaccessible to baboons, thus increasing the difficulty of conservation efforts. This preliminary assessment highlights the urgent need for detailed assessments at a finer scale. [ABSTRACT FROM AUTHOR]

The effective use of satellite image time series for examining vegetation response patterns across regional extents requires a method which accounts for variation at the seasonal scale while simultaneously detecting abrupt changes in any long term trends. The Breaks for Additive Seasonal and Trend (BFAST) algorithm has been developed to do this. However, its effectiveness in semi-arid regions, where vegetation response is typically aseasonal, has yet to be assessed. In this research the BFAST algorithm was assessed for a semi-arid study area in the Paroo catchment of far north-western New South Wales, Australia. Moderate Resolution Imaging Spectroradiometer (MODIS) EVI time series were decomposed using BFAST for 270 sample pixels to assess the algorithm's ability to detect abrupt changes in vegetation response caused by known fires and floods. The algorithm was also applied across the study area to examine regional patterns in the timing and magnitude of abrupt changes and the direction and magnitude of the long term trends. The timing of breaks detected by BFAST corresponded with the timing of known floods in the study region for between 68% and 79% of breaks detected across the sample pixels, depending on the parameters used in the decomposition. BFAST was not, however, able to accurately detect fires in the Paroo region, with agreement between the timing of breaks and fires occurring in only 3% of breaks detected. This most likely reflects the low EVI values present before a fire event, which would be typical of semi-arid zones. Spatial patterns in the timing of abrupt changes and greening and browning trends across the study area were a function of land cover and vegetation type. These results indicate that BFAST is able to detect abrupt changes in vegetation greening caused by known floods in semi-arid regions. The presence of spatial patterns in the results also indicates that the algorithm is sensitive to vegetation cover type. BFAST is therefore able to detect abrupt trend changes in regions where vegetation response is not expected to show strong seasonal patterns and could be used in further applications such as classification or regional vegetation modelling in semi-arid environments. [ABSTRACT FROM AUTHOR]

Previous research focusing on broad-scale or geographically invariant species-environment dependencies suggest that temperature-related variables explain more of the variation in reptile distributions than precipitation. However, species-environment relationships may exhibit considerable spatial variation contingent upon the geographic nuances that vary between locations. Broad-scale, geographically invariant analyses may mask this local variation and their findings may not generalize to different locations at local scales. We assess how reptile-climatic relationships change with varying spatial scale, location, and direction. Since the spatial distributions of diversity and endemism hotspots differ for other species groups, we also assess whether reptile species turnover and endemism hotspots are influenced differently by climatic predictors. Using New Zealand reptiles as an example, the variation in species turnover, endemism and turnover in climatic variables was measured using directional moving window analyses, rotated through 360°. Correlations between the species turnover, endemism and climatic turnover results generated by each rotation of the moving window were analysed using multivariate generalized linear models applied at national, regional, and local scales. At national-scale, temperature turnover consistently exhibited the greatest influence on species turnover and endemism, but model predictive capacity was low (typically r2 = 0.05, P < 0.001). At regional scales the relative influence of temperature and precipitation turnover varied between regions, although model predictive capacity was also generally low. Climatic turnover was considerably more predictive of species turnover and endemism at local scales (e.g., r2 = 0.65, P < 0.001). While temperature turnover had the greatest effect in one locale (the northern North Island), there was substantial variation in the relative influence of temperature and precipitation predictors in the remaining four locales. Species turnover and endemism hotspots often occurred in different locations. Climatic predictors had a smaller influence on endemism. Our results caution against assuming that variability in temperature will always be most predictive of reptile biodiversity across different spatial scales, locations and directions. The influence of climatic turnover on the species turnover and endemism of other taxa may exhibit similar patterns of spatial variation. Such intricate variation might be discerned more readily if studies at broad scales are complemented by geographically variant, local-scale analyses. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including cost path analyses, landscapes and species.

Species ranges are often represented using polygons, with the attendant issues that they show uniform ranges with abrupt boundaries and can overestimate species ranges. We demonstrate that such uniform species ranges can be supplemented by mapping the gradational variation in species turnover across a landscape. Directional variation in species turnover for 15 skink species (Reptilia: Scincidae) and topographic and climatic turnover in south-eastern Australia were measured using directional moving window analyses, rotated through 360°. The resultant species turnover maps were compared with published polygon range maps for two species within the group (Liopholis whitiiandL. inornata). We also assessed how the relationships between species and environmental turnover varied in areas of low or high species turnover. Continuous transitions between distinct areas of low and high species turnover were mapped. Low turnover comprised only 19% of theL. whitiipolygon species range within the study area extent. These low turnover areas were more densely populated byL. whitii(67% of observations), whereas areas of medium to high turnover contained substantially fewer observations (25%). Regions with the highest species turnover contained only 6% of observations.L. inornataobservations were also clustered in low species turnover areas. Averaged climatic and elevation values were higher in low-turnover areas despite their close adjacency to high-turnover zones. The environmental turnover in low species turnover regions was also lower than in high-turnover areas. Correlations between environmental turnover and low species turnover areas were positive, whereas the opposite relationship applied in high species turnover areas. We identified both abrupt and gradual distributional breaks between separate reptile assemblages; an example of the latter is located in the Hunter Valley in the south-eastern coastal region. This break has been mapped using solid, uniform lines in species ranges and thus implicitly as an abrupt break. Environmental conditions may be more favourable to skinks in low-turnover areas. SinceL. whitiiand other skink species have very large populations in low-turnover areas, other squamate species may also be more likely to occur in these areas. This has potential implications for conservation prioritisation. The turnover maps used here can supplement the information provided about reptile distributions by the equivalent polygon ranges. This approach can be applied to point occurrence data for any taxonomic group or any similar georeferenced diversity data set. [ABSTRACT FROM AUTHOR]

It is commonly accepted that species interactions such as granivory are more intense in the tropics. However, this has rarely been tested. A global dataset of post-dispersal seed removal by invertebrates and vertebrates for 79 native plant species from semi-natural and natural terrestrial habitats ranging from 55° N to 45° S, was compiled from the global literature to test the hypothesis that post-dispersal seed removal by invertebrates and vertebrates is more intense at lower latitudes. We also quantified the relationship between post-dispersal seed removal by vertebrates and by invertebrates to global climatic features including temperature, actual evapotranspiration (AET) and rainfall seasonality. Linear mixed effect models were applied to describe the relationships between seed removal and latitude, hemisphere and climatic variables controlling for the effect of seed mass. Post-dispersal seed removal by invertebrates was negatively related to latitude. In contrast, post-dispersal seed removal by vertebrates was positively but weakly related to latitude. Mean annual temperature and actual evapotranspiration were positively related to post-dispersal seed removal by invertebrates, but not to post-dispersal seed removal by vertebrates, which was only marginally negatively related to rainfall seasonality. The inclusion of seed mass improved the fit of all models, but the term for seed mass was not significant in any model. Although a good climatic model for predicting post-dispersal seed predation by vertebrates at the global level was not found, our results suggest different and opposite latitudinal patterns of post-dispersal seed removal by invertebrates vs vertebrates. This is the first time that a negative relationship between post-dispersal seed removal by invertebrates and latitude, and a positive relationship with temperature and AET have been documented at a global-scale. These results have important implications for understanding global patterns in plant-animal interactions, and the factors that shape plant reproductive ecology, and also for predicting how this plant-animal interaction might respond to climate change. [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 Concern about climate change, with the subsequent emergence of carbon markets and policy initiatives such as REDD (reducing carbon emissions by decreasing deforestation and forest degradation), have focused attention on assessing and monitoring terrestrial carbon reserves. Most effort has focused on above-ground forest biomass. Soil has received less attention despite containing more carbon than above-ground terrestrial biomass and the atmosphere combined. Our aim was to explore how well soil carbon concentration could be estimated on three continents from existing climate, topography and vegetation-cover data. Location Peru, Brazil, Argentina, Australia, China. Methods Soil carbon concentration and leaf area index ( LAI) as well as GIS-derived climate and topography variables for 65 temperate and 43 tropical, forest and woodland ecosystems, were either directly measured or estimated from freely available global datasets. We then used multiple regressions to determine how well soil carbon concentration could be predicted from LAI, climate and topography at a given site. We compared our measurements with top soil carbon estimates from the Food and Agriculture Organization of the United Nations ( FAO) harmonized world soil map. Results Our empirical model based on estimates of temperature, water availability and plant productivity provided a good estimate of soil carbon concentrations ( R2 = 0.79). In contrast, the values of topsoil carbon concentrations from the FAO harmonized world soil map correlated poorly with the measured values of soil carbon concentration ( R2 = 0.0011). Main conclusions The lack of correlation between the measured values of soil carbon and the values from the FAO harmonized world soil map indicate that substantial improvements in the production of soil carbon maps are needed and possible. Our results demonstrate that the inclusion of freely available GIS data offers improved estimates of soil carbon and will allow the creation of more accurate soil carbon maps. [ABSTRACT FROM AUTHOR]

Predictive spatial modeling has become a key research tool for species distribution modeling where actual data are limited. Although qualitative maps and distribution descriptions for chacma baboons ( Papio ursinus) are freely available, quantitative data are limited and do not provide the empirical information required to make informed decisions about issues such as population assessment, conservation, and management. Here we present the first quantitative, repeatable, and detailed predicted spatial distribution of the chacma baboon across southern Africa. Our distribution is at a finer level of detail than has previously been available. We used an environmental envelope model implemented within a geographic information system to achieve this. The model used environmental layers representing water availability, temperature and altitude, and model parameters determined from georeferenced observational data. The data extracted from the environmental layers suggest chacma baboons inhabit areas with mean minimum temperatures of the coolest month as low as −6.1 °C, mean maximum temperatures of the warmest month as high as 38.2 °C, mean annual rainfall up to 1,555 mm, and altitude up to 3,286 m. Our model demonstrates that the distribution of chacma baboons may be limited by temperature and rainfall, with the predicted northern extent of its range being temperature dependent. The model also implies that some areas well known for chacma baboon occupation today may in fact be marginal habitat. The resulting map highlights areas of suitable habitat in southern Africa. In addition, a linear 'patchy' corridor was identified following the East African Rift Valley connecting the southern habitat with northeast Africa. We find the greatest proportion of suitable habitat to be located in South Africa. This modeling approach is generic and would be suitable to analyze other primate species across similar geographic extents. [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]

Knowledge of species compositional turnover, the rate of change in the number of species shared between locations along geographic and environmental gradients, is important for conservation planning. Spatially global models relating species and environmental turnover are well established. However, to date there has been no explicit assessment of the effects of geographical variation in parameters (spatial non-stationarity) and directional dependence (anisotropy) on these models. Such processes are well known to affect other geospatial analyses. Here, we assess how these affect the shape, goodness of fit and composition of species turnover–environment relationships. We use the eastern Australian distribution of species in the Myrtaceae, an important family of vascular plants in the region. We obtained distribution data for Myrtaceae species from herbarium records and corresponding environmental attributes (mean of 1 km gridded cell values aggregated to 10 km grid cells). Species compositional turnover was quantified using the Sørensen pairwise dissimilarity index. The turnover–environment relationship was analysed using generalised dissimilarity modelling (GDM), a purpose-designed statistical regression technique. The data were divided into three sets of spatially local subsamples: 27 rectangular east–west-aligned coastal–inland bands, 8 north–south coastally aligned bands and 12 symmetrical omnidirectional blocks. A separate GDM was fitted to each spatially local subsample. The results display marked evidence of spatial variation in the shape, goodness of fit and composition of local species turnover–environment relationships, with this variation appearing strongly directional. The observed spatial structure of local biodiversity–environment relationships, expressed as species compositional turnover, is unsurprising considering both the steep east–west environmental gradients associated with Australia's eastern ranges and the known decreasing sampling intensity in the same direction. Local spatial non-stationarity and anisotropy are expected outcomes irrespective of the chosen turnover index, study taxa or statistical model used. Currently, it is difficult to separate genuine biogeographic effects from data bias. Future analyses could better account for the observed spatial structure of both biodiversity–environment relationships and data bias by incorporating directionality in data subsampling strategies and explicit biogeographic predictors in model design. [ABSTRACT FROM PUBLISHER]

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]

Abstract: The definition of the spatial relatedness between infectious and susceptible animal groups is a fundamental component of spatio-temporal modelling of disease outbreaks. A common neighbourhood definition for disease spread in wild and feral animal populations is the distance between the centroids of neighbouring group home ranges. This distance can be used to define neighbourhood interactions, and also to describe the probability of successful disease transmission. Key limitations of this approach are (1) that a susceptible neighbour of an infectious group with an overlapping home range – but whose centroid lies outside the home range of an infectious group – will not be considered for disease transmission, and (2) the degree of overlap between the home ranges is not taken into account for those groups with centroids inside the infectious home range. We assessed the impact of both distance-based and range overlap methods of disease transmission on model-predicted disease spread. Range overlap was calculated using home ranges modelled as circles. We used the Sirca geographic automata model, with the population data from a nine-county study area in Texas that we have previously described. For each method we applied 100 model repetitions, each of 100 time steps, to 30 index locations. The results show that the rate of disease spread for the range-overlap method is clearly less than the distance-based method, with median outbreaks modelled using the latter being 1.4–1.45 times larger. However, the two methods show similar overall trends in the area infected, and the range-overlap median (48 and 120 for cattle and pigs, respectively) falls within the 5th–95th percentile range of the distance-based method (0–96 and 0–252 for cattle and pigs, respectively). These differences can be attributed to the calculation of the interaction probabilities in the two methods, with overlap weights generally resulting in lower interaction probabilities. The definition of spatial neighbourhood has important implications for models used in decision-support systems for disease preparedness and response. This research presents a first step towards more realistic representations that could be used in spatio-temporal models of disease outbreaks. [Copyright &y& Elsevier]

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]

There is an ongoing debate concerning the relationship between the disciplinary ends of the broad spectrum that is geography and also the relationship between geography and other disciplines, including the extent to which it is self-focussed or inward looking. These issues were assessed using an analysis of citation relationships between journals in the Thompson Scientific Journal Citation Reports databases at the category level. Thirty-four categories were used, comparing the two geography categories (‘Geography’, representing human geography and ‘Geography, Physical’, representing physical geography) with 32 other cognate categories. A matrix of the citation relationships between each category was developed using a relatedness factor that corrects for the opportunity for citations to occur. The resultant matrix of factors indicates that human geography journals are considerably more likely to cite their own papers than are those of physical geography, but that they are by no means the most self-citing of the journals assessed. Both human and physical geography journals have strong citation relationships with several other disciplines, with those for human geography most often being net export relationships in the sense of a balance of trade. This finding contradicts previous assertions that human geography imports more than it exports. The citation relationships of physical geography are smaller than those of human geography, and are typically small net imports. The relationship between human and physical geography journals is a small net export from physical geography to human geography, but their total trade volume is considerably smaller than their respective relationships with other disciplines. These results are likely to be caused by many factors in addition to the actual relatedness between disciplines and sub-disciplines, but they do represent a benchmark against which more detailed analyses can be assessed. [ABSTRACT FROM AUTHOR]

The highly skewed sex ratio at birth (SRB) in China has stimulated numerous studies. However, the geographic distribution of SRB is seldom investigated, particularly at the county level. The need for an understanding at this level has increased since the Chinese government initiated its 'Care for Girls' campaign to improve the survival rate of females. This campaign has been initiated in a set of pilot counties. In this article we assess the effectiveness of the set of pilot counties in Shandong province and propose two alternate configurations. To do this, we first assess the spatial distribution of the SRB values by county in Shandong, expressed as a z-score (zSRB) after correcting for the biologically expected SRB value and population size of zero-aged children. A local Moran's Ii analysis of the zSRB values indicates a significant high-high cluster in the southwest of the province. The Ii, zSRB and female deficit (the difference of the observed from biologically expected number of zero-aged females) were then used to define two alternate configurations for the pilot counties. A comparison of the current and alternate configurations against a Monte Carlo randomisation analysis shows that the current configuration is significantly different from a random selection (p < 0.05) for the two criteria of maximising the aggregate female deficit and maximising the zSRB. Although this is a good result, both alternate configurations were more significant (p < 0.001), and therefore represent potentially better configurations for the campaign given the criteria used. The spatial analysis approach developed here could be used to improve the effectiveness of the Care-for-Girls campaign in Shandong province, and elsewhere in China. [ABSTRACT FROM AUTHOR]

We present a new, broadly applicable measure of the spatial restriction of phylogenetic diversity, termed phylogenetic endemism (PE). PE combines the widely used phylogenetic diversity and weighted endemism measures to identify areas where substantial components of phylogenetic diversity are restricted. Such areas are likely to be of considerable importance for conservation. PE has a number of desirable properties not combined in previous approaches. It assesses endemism consistently, independent of taxonomic status or level, and independent of previously defined political or biological regions. The results can be directly compared between areas because they are based on equivalent spatial units. PE builds on previous phylogenetic analyses of endemism, but provides a more general solution for mapping endemism of lineages. We illustrate the broad applicability of PE using examples of Australian organisms having contrasting life histories: pea-flowered shrubs of the genus Daviesia (Fabaceae) and the Australian species of the Australo-Papuan tree frog radiation within the family Hylidae. [ABSTRACT FROM AUTHOR]

Abstract: We investigated how the size and distribution of wild deer and feral pigs – species that might act as potential foot-and-mouth disease (FMD) virus maintenance hosts – might affect the persistence and spread of FMD. We used a susceptible-latent-infected-recovered geographic-automata model and spatially referenced data from southern Texas, USA. Within this study area, 100 locations were randomly selected and FMD virus spread was simulated (50 simulations each) at each location. As expected, the predicted sizes (km2) of the wild deer outbreaks were highly correlated (r SP >0.95) with the number of deer at incursion locations, the total number of deer within 2km of incursion locations, and the minimum and maximum deer herd size within 2km of incursion locations. However, the predicted sizes of the feral pig outbreaks were only moderately correlated (r SP 0.63–0.67) with the total, maximum and variance of the number of feral pigs within 2km of incursion locations. Lack of continuity within the feral pig herd distribution across the landscape makes predicting disease spread more difficult than for deer, a more homogenously distributed species. When assessing the potential of wild and feral animal species at a locality to act as maintenance hosts of FMD virus, estimates of the population size and distribution might serve as a useful indicator of potential outbreaks in some circumstances. [Copyright &y& Elsevier]

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]

Abstract: The construction of habitat models is a repeatable technique for describing and mapping species distributions, the utility of which lies in enabling management to predict where a species is likely to occur within a landscape. Typically, habitat models have been used to establish habitat requirements for threatened species; however they have equal applicability for modelling local populations of common species. Often, few data exist on local populations of common species, and issues of abundance and habitat selection at varying scales are rarely addressed. We provide a habitat suitability model for the common wombat (Vombatus ursinus) in southern New South Wales. This species is currently perceived as abundant throughout its extensive range across temperate regions of eastern Australia, yet little factual survey data exist and populations appear under threat. We use wombat burrows to reflect habitat selection and as our basis for ecological modelling. We found that environmental variables representing proximity to cover, measures of vegetation and proximity to watercourses are important predictors of burrow presence. Extrapolation of habitat models identified an abundance of habitat suitable for burrows. However, burrows in many suitable areas were abandoned. Our estimate of the population size was similar to the total annual mortality associated with road-kill. Theoretically, given the availability of suitable habitat, common wombat populations in the region should be thriving. It seems likely that this area once supported a much higher number of wombats; however limiting factors such as road mortality and disease have reduced the populations. The persistence of wombats in the study region must be supported by migration from other populations. Our findings challenge the perception that wombats are currently common and not in need of monitoring, suggesting that perceptions of abundance are often clouded by socio-political motives rather than informed by biological and ecological factors. [Copyright &y& Elsevier]

Abstract: We investigated the potential role of feral pigs and wild deer as FMD reservoirs with a susceptible–latent–infected–recovered geographic-automata model, using spatially referenced data from southern Texas, USA. An uncontrolled FMD outbreak initiated in feral pigs and in wild deer might infect up to 698 (90% prediction interval 181, 1387) and 1557 (823, 2118) cattle and affect an area of 166km2 (53, 306) and 455km2 (301, 588), respectively. The predicted spread of FMD virus infection was influenced by assumptions we made regarding the number of incursion sites and the number of neighborhood interactions between herds. Our approach explicitly incorporates the spatial relationships between domesticated and non-domesticated animal populations, providing a new framework to explore the impacts, costs, and strategies for the control of foreign animal diseases with a potential wildlife reservoir. [Copyright &y& Elsevier]

Aim To determine the relationship between the distribution of climate, climatic heterogeneity and pteridophyte species richness gradients in Australia, using an approach that does not assume potential relationships are spatially invariant and allows for scale effects (extent of analysis) to be explicitly examined. Location Australia, extending from 10° S to 43° S and 112° E to 153° E. Method Species richness within 50 × 50 km grid cells was determined using point distribution data. Climatic surfaces representing the distribution and availability of water and energy at 1 km and 5 km cell resolutions were obtained. Climate at the 50 km resolution of analysis was represented by their mean and standard deviation in that area. Relationships were assessed using geographically weighted linear regression at a range of spatial bandwidths to investigate scale effects. Results The parameters and the predictive strength of all models varied across space at all extents of analysis. Overall, climatic variables representing water availability were more highly correlated to pteridophyte richness gradients in Australia than those representing energy. Their variance in cells further increased the strength of the relationships in topographically heterogeneous regions. Relationships with water were strong across all extents of analysis, particularly in the tropical and subtropical parts of the continent. Water availability explained less of the variation in richness at higher latitudes. Main conclusions This study brings into question the ability of aspatial and single-extent models, searching for a unified explanation of macro-scaled patterns in gradients of diversity, to adequately represent reality. It showed that, across Australia, there is a positive relationship between pteridophyte species richness and water availability but the strength and nature of the relationship varies spatially with scale in a highly complex manner. The spatial variance, or actual complexity, in these relationships could not have been demonstrated had a traditional aspatial global regression approach been used. Regional scale variation in relationships may be at least as important as more general relationships for a true understanding of the distribution of broad-scale diversity. [ABSTRACT FROM AUTHOR]

Abstract: We describe an approach to modelling the spatio-temporal spread of foot and mouth disease through feral animal and unfenced livestock populations. We used a susceptible-infected-recovered model, implemented in a cellular automata framework, to assess the spread of FMD across two regions of Queensland, Australia. Following a sensitivity analysis on the infectious states, scenario analyses were conducted using feral pigs only as the susceptible population, and then with the addition of livestock, and initiated in the wet season and in the dry season. The results indicate that, depending on the season the outbreak is initiated, and without the implementation of control measures, an outbreak of Foot and Mouth Disease around Winton could continue unchecked, while an outbreak around Cape York may die out naturally. The approach explicitly incorporates the spatial relationships between the populations through which the disease spreads and provides a framework by which the spread of disease outbreaks can be explored through varying the model parameters. It highlights the emergence and importance of spatio-temporal patterns, something that previous modelling of FMD in feral animal and unfenced livestock populations has lacked. [Copyright &y& Elsevier]

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]

In this paper we assess the utility of mapping regolith properties as continuously varying fields using environmental correlation over large spatial areas. The assessment is based on a comparison of results from spatially global and local analysis methods.The two methods used are a feed-forward, back propagation neural network, applied globally, and moving window regression, applied locally. These methods are applied to five regolith properties from a field site at Weipa, Queensland, Australia. The properties considered are the proportions of oxides of aluminum, iron, silica and titanium present in samples, as well as depth to the base of the bauxite layer. These are inferred using a set of surface measurable features, consisting of Landsat data, geomorphometric indices, and distances from streams and swamps.The moving window regression results show a much stronger relationship than do those from the spatially global neural networks. The implication is that the scale of the analysis required for environmental correlation is of the order of hundreds of metres, and that spatially global analyses may incur an automatic reduction in accuracy by not modelling geographically local relationships. In this case, this effect is up to 45% error at a tolerance near half of a standard deviation. [Copyright &y& Elsevier]

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]

Analyses within the field of GIS are increasingly applying stochastic methods and systems that make use of pseudo-random number generators (PRNGs). Examples include Monte Carlo techniques, dynamic modelling, stochastic simulation, artificial life and simulated data development. PRNGs have inherent biases, and this will in turn bias any analyses using them. Therefore, the validity of stochastic analyses is reliant on the PRNG employed. Despite this, the effect of PRNGs in spatial analyses has never been completely explored, particularly a comparison of different PRNGs. Exacerbating the problem is that GIS articles applying Monte Carlo or other stochastic methods rarely report which PRNG is employed. It thus appears likely that GIS researchers rarely, if ever, check the suitability of the PRNG employed for their analyses or simulations. This paper presents a discussion of some of the characteristics of PRNGs and specific issues from a geospatial standpoint, including a demonstration of the differences in the results of a Monte Carlo analysis obtained using two different PRNGs. It then makes recommendations for the application of PRNGs in spatial analyses, including recommending specific PRNGs that have attributes appropriate for geospatial analysis. The paper concludes with a call for more research into the application of PRNGs to spatial analyses to fully understand the impact of biases, especially before they are routinely used in the wider spatial analysis community. [ABSTRACT FROM AUTHOR]

This paper describes a method of improving spatial analyses by using a process model to define the sampling window. This method allows the sample to adapt to changing conditions as they occur in the dataset, rather than applying the same geometric shape to all locations. Such a sampling method can be used to reduce the noise in the sample, and thus generate more sensible results. The general approach may be applied to other processes that influence or control the distribution of spatial variables, provided the processes are known and can be modelled. The method also enables exploration of the degree to which a spatial variable is controlled by an assumed driving process. In this study the sampling windows for each location are defined using uphill and downhill watersheds, and are applied to geochemical variables across a 1100 km2 area in Weipa, Queensland, Australia. The utility of the approach is assessed using variograms and the Getis-Ord G[sub i]* statistic. Results indicate an improvement over omnidirectional and wedge-shaped sampling, with the most improvement where the variable is highly mobile in solution. These areas are considered to be under modern hydrological control. Most errors in the example are attributed to the effect of other landscape processes, such as aeolian transport and marine incursions. [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]

The analysis of regional scale patterns of diversity allows insights into the processes that have shaped modern biodiversity at the macro‐scale. Previous analyses studying biogeographic regionalisation across different high‐level taxa have shown similar trends at a global scale. However, incorporating phylogenetic methods when comparing biogeographic regionalisation between subgroups facilitates identification of mechanisms leading to the biogeographic distribution of specific taxa. We analysed the spatial trends of phylogenetic diversity and phylogenetic endemism of 325 species of New World bats, using updated range maps of the modern distributions. These analyses showed phylogeographic signals that reflect the different evolutionary histories of these families. Zoogeographical zones were detected based on range‐weighted phylogenetic turnover. Values of high phylogenetic diversity and endemism were distributed differently across families, suggesting niche conservatism, but a general latitudinal trend of diversity was evident across taxa. Overall, two main bioregions were shared across New World bat taxa (Nearctic and Neotropical), with two additional subregions (Andean and La Platan). We found strong support for an additional transitional zone in the Pacific coast of South America for Emballonuridae and Molossidae. Differences in regionalisation across families indicate that niche conservatism, in situ diversification and dispersal ability are major drivers for the regionalisation of New World bats, within a dual‐centre of diversification scenario. We also found strong inter‐familial support for an independent Caribbean biogeographic region. [ABSTRACT FROM AUTHOR]

New World bats represent over one third of global bat species and encompass the widest adaptive radiation among bats. Modern bat diversity in the Americas resulted from a mixture of migrations and colonisations of different taxa throughout the Cenozoic. Traditionally, these taxa are conceived as either South or North American, based on the location of their centres of diversification. To better understand the spatial and temporal processes behind modern biogeographic patterns of New World bat fauna, we investigated phylogenetic diversity (PD) and endemism (PE) for 325 American bat species using distribution maps and a species‐level phylogenetic supertree of bats. Randomisation tests were used to evaluate the statistical significance of our results, and to derive a categorical analysis of neo‐ and palaeo‐endemism (CANAPE) to deconstruct significant endemism into its different components. PD and PE showed different patterns than those previously reported for New World bats based on traditional measures of diversity. We found multiple centres of significant endemism across the New World for most bat families, extending the hypothesis of dual centres of diversification, previously proposed for Emballonuridae, Phyllostomidae and Mormoopidae, to Molossidae and Vespertilionidae. Our results indicate that Central America and southern North America played important roles in the diversification of New World bats, as did the Andes in the diversification of Vespertilionidae in South America. [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: A key ecological debate is whether ecosystem functions are distinctly influenced by biological diversity across broad scales. Although recent work has emphasized the importance of links between ecosystem functions and measures of ecological specialization as proxies of biodiversity, few studies have analysed macroecological relationships empirically in diverse environments. We tested whether gross primary productivity (GPP) in the Australian Wet Tropics (WT) was distinctly related to community‐level measures of the ecological specialization of component tree species across climate space, after accounting for climate drivers. Location: Wet Tropics, Australia. Time period: 1976–2012. Major taxa studied: Nine hundred and forty‐eight WT tree species. Methods: Using all geographically valid herbarium records for WT trees, we quantified the realized climatic niche widths using continental surfaces for maximum temperature of the warmest period and total annual rainfall. The median realized niche width for all tree species occurring at 510 sites was used to approximate ecological specialization within communities. To separate climatic effects on GPP, we applied a novel analysis using the difference in GPP and the difference in median community realized niche width between site pairs with similar climatic conditions. Linear models were then run on the difference in GPP between site pairs (response) and the difference in climatic niche widths (predictor). Results: For climatically similar sites in drier areas, GPP was higher in sites composed of species with narrower temperature niches (average R2 = 0.087, average t‐statistic = −3.45). Conversely, for climatically similar sites in drier areas, GPP was lower in sites composed of species with narrower rainfall niches (average R2 = 0.171, average t‐statistic = 5.06). Main conclusions: Wet Tropics sites with more thermal specialists had higher productivity, whereas sites with more moisture specialists had lower productivity. These findings suggest that physiological specialization across climate space can influence primary productivity at broad scales, but in inconsistent ways. [ABSTRACT FROM AUTHOR]