Assessing congruence of opportunistic records and systematic surveys for predicting Hispaniolan mammal species distributions

Comparative assessment of the relative information content of different independent spatial data types is necessary to evaluate whether they provide congruent biogeographic signals for predicting species ranges. Opportunistic occurrence records and systematically collected survey data are available from the Dominican Republic for Hispaniola’s surviving endemic non‐volant mammals, the Hispaniolan solenodon (Solenodon paradoxus) and Hispaniolan hutia (Plagiodontia aedium); opportunistic records (archaeological, historical and recent) exist from across the entire country, and systematic survey data have been collected from seven protected areas. Species distribution models were developed in maxent for solenodons and hutias using both data types, with species habitat suitability and potential country‐level distribution predicted using seven biotic and abiotic environmental variables. Three different models were produced and compared for each species: (a) opportunistic model, with starting model incorporating abiotic‐only predictors; (b) total survey model, with starting model incorporating biotic and abiotic predictors; and (c) reduced survey model, with starting model incorporating abiotic‐only predictors to allow further comparison with the opportunistic model. All models predict suitable environmental conditions for both solenodons and hutias across a broadly congruent, relatively large area of the Dominican Republic, providing a spatial baseline of conservation‐priority landscapes that might support native mammals. Correlation between total and reduced survey models is high for both species, indicating the substantial explanatory power of abiotic variables for predicting Hispaniolan mammal distributions. However, correlation between survey models and opportunistic models is only moderately positive. Species distribution models derived from different data types can provide different predictions about habitat suitability and conservation‐priority landscapes for threatened species, likely reflecting incompleteness and bias in spatial sampling associated with both data types. Models derived using both opportunistic and systematic data must therefore be applied critically and cautiously.     

Detection of plot-level changes in ectomycorrhizal communities across years in an old-growth mixed-conifer forest

Understanding spatial and temporal patterns present in ectomycorrhizal fungal community structure is critical to understanding both the scale and duration of the potential impact these fungi have on the plant community. While recent studies consider the spatial structure of ectomycorrhizal communities, few studies consider how this changes over time. Ectomycorrhizal root biomass and the similarity of community composition were measured at scales up to 20 cm replicated in nine plots and over 3 yr. Soil cores were additionally stratified into three depths. Annual occurrence of the dominant ectomycorrhizal species was constant at larger spatial scales but varied more across years at a fine spatial scale. Turnover of ectomycorrhizal species between years was observed frequently at scales < 20 cm. The ectomycorrhizal community within a plot was more similar across years than it was to other plots sampled in the same year. Our results demonstrate the dynamic nature of the ectomycorrhizal community even in the absence of large-scale disturbances. The potential role of root turnover and drought stress is discussed.     

Phylogenetic turnover during subtropical forest succession across environmental and phylogenetic scales

Although spatial and temporal patterns of phylogenetic community structure during succession are inherently interlinked and assembly processes vary with environmental and phylogenetic scales, successional studies of community assembly have yet to integrate spatial and temporal components of community structure, while accounting for scaling issues. To gain insight into the processes that generate biodiversity after disturbance, we combine analyses of spatial and temporal phylogenetic turnover across phylogenetic scales, accounting for covariation with environmental differences. We compared phylogenetic turnover, at the species‐ and individual‐level, within and between five successional stages, representing woody plant communities in a subtropical forest chronosequence. We decomposed turnover at different phylogenetic depths and assessed its covariation with between‐plot abiotic differences. Phylogenetic turnover between stages was low relative to species turnover and was not explained by abiotic differences. However, within the late‐successional stages, there was high presence‐/absence‐based turnover (clustering) that occurred deep in the phylogeny and covaried with environmental differentiation. Our results support a deterministic model of community assembly where (i) phylogenetic composition is constrained through successional time, but (ii) toward late succession, species sorting into preferred habitats according to niche traits that are conserved deep in phylogeny, becomes increasingly important.     

Alternative growth and energy storage responses to mortality threats in damselflies

The role of physiology in mediating the growth/predation risk trade‐off has been largely ignored. We examined effects of predation risk on relationships between growth and storage molecules in Enallagma aspersum and Ischnura verticalis damselfly larvae that differ in this trade‐off. In laboratory and field experiments, both species had similar growth and mortality rates and similar concentrations of storage molecules in the absence of mortality threats. However, in the presence of dragonfly predators Ischnura larvae had higher mortality rates and grew faster than Enallagma larvae. Consistent with the difference in growth rate, Enallagma's total protein concentrations decreased under predation risk while those of Ischnura did not. Glucose and glycogen concentrations were not affected, while triglyceride concentrations were lower under predation risk in Enallagma but not in Ischnura. Species differences at the physiological level to the presence of mortality threats may be crucial to understanding patterns in metamorphic and post‐metamorphic traits.     

Spatial modelling of species turnover identifies climate ecotones,climate change tipping points and vulnerable taxonomic groups

There is an expectation that climate change will drive turnover in the composition of ecological communities. Established methods for predicting the degree of turnover and spatial areas and taxonomic groups that will be most affected from real data are lacking. We tested a combination of spatial modelling tools to make these predictions. Using data from systematic vegetation survey plots from the Adelaide Geosyncline region, southern Australia, we modelled species turnover as a function of bioclimatic and geographic distances and predicted turnover using future climate change scenarios for 2030 and 2070. We conducted bioclimatic gradient analysis (CCA) on species composition data and mapped zones of higher turnover. The method for detecting these zones was tested using a simulation of continuous turnover. A phylogeny was generated for recorded species and correlations of occurrences of phylogenetic groups with species turnover were calculated. Significant turnover was predicted for the least severe climate change scenarios and near‐complete species turnover for the most severe scenario. Gradient analysis revealed discrete transitional zones with more rapid turnover, which were interpreted as a mesic–arid ecotone. Turnover occurred at family level and with increasing temperature and decreasing rainfall there was a shift from the prevalence of Ericaceae, Myrtaceae, Haloragaceae, Cyperaceae, and Xanthorrhoeaceae to that of Amaranthaceae, Malvaceae, Scrophulariaceae, Sapindaceae, and Solanaceae. The mesic end of this climate gradient had relatively low rates of turnover and was interpreted as a refugium with a tipping point. The translation of spatial patterns to temporal change is dependent partly upon scales at which community assembly processes operate and predicts relative vulnerability, but not rates of change, which can only be measured through monitoring. The approach can be applied at any spatial or taxonomic scale subject to sufficient data resolution and can inform management decisions as to biases in climate change risks.     

Environmental gradients and the structure of freshwater snail communities

A fundamental goal of ecology is to understand the factors that influence community structure and, consequently, generate heterogeneity in species richness across habitats. While niche‐assembly (e.g. species‐sorting) and dispersal‐assembly mechanisms are widely recognized as factors structuring communities, there remains substantial debate concerning the relative importance of each of these mechanisms. Using freshwater snails as a model system, we explore how abiotic and biotic factors interact with dispersal to structure local communities and generate regional patterns in species richness. Our data set consisted of 24 snail species from 43 ponds and lakes surveyed for seven years on the Univ. of Michigan's E. S. George Reserve and Pinckney State Recreation Area near Ann Arbor, Michigan. We found that heterogeneity in habitat conditions mediated species‐sorting mechanism to drive patterns in snail species richness across sites. In particular, physical environmental variables (i.e. habitat area, hydroperiod, and canopy cover), pH, and fish presence accounted for the majority of variation in the species richness across sites. We also found evidence of Gleasonian structure (i.e. significant species turnover with stochastic species loss) in the metacommunity. Turnover in snail species distributions was driven by the replacement of several pulmonate species with prosobranch species at the pond permanence transition. Turnover appeared to be driven by physiological constraints associated with differences in respiration mode between the snail orders and shell characteristics that deter molluscivorous fish. In contrast to these niche‐assembly mechanisms, there was no evidence that dispersal‐assembly mechanisms were structuring the communities. This suggests that niche‐assembly mechanisms are more important than dispersal‐assembly mechanisms for structuring local snail communities.     

Top predators determine how biodiversity is partitioned across time and space

Natural ecosystems are shaped along two fundamental axes, space and time, but how biodiversity is partitioned along both axes is not well understood. Here, we show that the relationship between temporal and spatial biodiversity patterns can vary predictably according to habitat characteristics. By quantifying seasonal and annual changes in larval dragonfly communities across a natural predation gradient we demonstrate that variation in the identity of top predator species is associated with systematic differences in spatio‐temporal β‐diversity patterns, leading to consistent differences in relative partitioning of biodiversity between time and space across habitats. As the size of top predators increased (from invertebrates to fish) habitats showed lower species turnover across sites and years, but relatively larger seasonal turnover within a site, which ultimately shifted the relative partitioning of biodiversity across time and space. These results extend community assembly theory by identifying common mechanisms that link spatial and temporal patterns of β‐diversity.     

Spatial congruence of ecological transition at the regional scale in South Africa

Aim To determine whether patterns of avian species turnover reflect either biome or climate transitions at a regional scale, and whether anthropogenic landscape transformation affects those patterns. Location South Africa and Lesotho. Methods Biome and land transformation data were used to identify sets of transition areas, and avian species occurrence data were used to measure species turnover rates (β‐diversity). Spatial congruence between areas of biome transition, areas of high vegetation heterogeneity, high climatic heterogeneity, and high β‐diversity was assessed using random draw techniques. Spatial overlap in anthropogenically transformed areas, areas of high climatic heterogeneity and high β‐diversity areas was also assessed. Results Biome transition areas had greater vegetation heterogeneity, climatic heterogeneity, and β‐diversity than expected by chance. For the land transformation transition areas, this was only true for land transformation heterogeneity values and for one of the β‐diversity measures. Avian presence/absence data clearly separated the biome types but not the land transformation types. Main conclusions Biome edges have elevated climatic and vegetation heterogeneity. More importantly, elevated β‐diversity in the avifauna is clearly reflected in the heterogeneous biome transition areas. Thus, there is spatial congruence in biome transition areas (identified on vegetation and climatic grounds) and avian turnover patterns. However, there is no congruence between avian turnover and land transformation transition areas. This suggests that biogeographical patterns can be recovered using modern data despite landscape transformation.     

Metacommunity‐scale biodiversity regulation and the self‐organised emergence of macroecological patterns

There exist a number of key macroecological patterns whose ubiquity suggests that the spatio‐temporal structure of ecological communities is governed by some universal mechanisms. The nature of these mechanisms, however, remains poorly understood. Here, we probe spatio‐temporal patterns in species richness and community composition using a simple metacommunity assembly model. Despite making no a priori assumptions regarding biotic spatial structure or the distribution of biomass across species, model metacommunities self‐organise to reproduce well‐documented patterns including characteristic species abundance distributions, range size distributions and species area relations. Also in agreement with observations, species richness in our model attains an equilibrium despite continuous species turnover. Crucially, it is in the neighbourhood of the equilibrium that we observe the emergence of these key macroecological patterns. Biodiversity equilibria in models occur due to the onset of ecological structural instability, a population‐dynamical mechanism. This strongly suggests a causal link between local community processes and macroecological phenomena.     

Fragmentation and pre-existing species turnover determine land-snail assemblages of tropical rain forest

Aim The main aims of the study were: (1) to investigate the effect of fragment age in relation to other patch‐ and landscape‐scale measures of forest fragmentation, and (2) to assess the relative importance of fragmentation, habitat degradation (i.e. degradation caused by selective logging and past shifting cultivation) and putative pre‐existing species turnover in structuring current land‐snail assemblages. Location South‐western Sri Lanka. Methods The land‐snail fauna was sampled using standardized belt transects. Fifty‐seven transects were sampled in 21 lowland rain forest fragments (c. 1–33,000 ha). The spatial arrangement of fragments in the study area was explicitly considered in an effort to take into account the non‐random nature of fragmentation and degradation and the possibility that current species composition may reflect patterns of species turnover that existed prior to fragmentation. The data set of 57 land‐snail species and 28 environmental and spatial variables was analysed using canonical correspondence analysis and partial canonical correspondence analysis. Results Fragment age, mean shape complexity (i.e. a landscape‐scale measure of shape complexity), altitude, and the spatial variables x (longitude), y (latitude) and y² explained significant variation in land‐snail species composition. None of the three nominal variables quantifying habitat degradation was significantly correlated with variation in species composition. The independent effects of fragment age and mean shape complexity were similar. The combined effect of the spatial variables alone was larger than the independent effects of fragment age, mean shape complexity or altitude, but was of the same order of magnitude. The total variation explained by the spatial variables was comparable to the total non‐spatial variation accounted for by fragment age, mean shape complexity and altitude. Main conclusions Fragment age was found to be one of only two key determinants (the other was shape complexity at the landscape scale) driving fragmentation‐related changes in community composition. The influence of pre‐fragmentation patterns of species turnover on assemblage structure can be stronger than the effects of fragmentation measures, such as age, and may override the effects of forest degradation. Thus, strong patterns of pre‐existing turnover may potentially confound interpretation of the effects of forest fragmentation and degradation.     

Assessing species richness trends: Declines of bees and bumblebees in the Netherlands since 1945

Estimating and predicting temporal trends in species richness is of general importance, but notably difficult because detection probabilities of species are imperfect and many datasets were collected in an opportunistic manner. We need to improve our capabilities to assess richness trends using datasets collected in unstandardized procedures with potential collection bias. Two methods are proposed and applied to estimate richness change, which both incorporate models for sampling effects and detection probability: (a) nonlinear species accumulation curves with an error variance model and (b) Pradel capture–recapture models. The methods are used to assess nationwide temporal trends (1945–2018) in the species richness of wild bees in the Netherlands. Previously, a decelerating decline in wild bee species richness was inferred for part of this dataset. Among the species accumulation curves, those with nonconstant changes in species richness are preferred. However, when analyzing data subsets, constant changes became selected for non‐Bombus bees (for samples in collections) and bumblebees (for spatial grid cells sampled in three periods). Smaller richness declines are predicted for non‐Bombus bees than bumblebees. However, when relative losses are calculated from confidence intervals limits, they overlap and touch zero loss. Capture–recapture analysis applied to species encounter histories infers a constant colonization rate per year and constant local species survival for bumblebees and other bees. This approach predicts a 6% reduction in non‐Bombus species richness from 1945 to 2018 and a significant 19% reduction for bumblebees. Statistical modeling to detect species richness time trends should be systematically complemented with model checking and simulations to interpret the results. Data inspection, assessing model selection bias, and comparisons of trends in data subsets were essential model checking strategies in this analysis. Opportunistic data will not satisfy the assumptions of most models and this should be kept in mind throughout.     

Identifying and correcting spatial bias in opportunistic citizen science data for wild ungulates in Norway

Many publications make use of opportunistic data, such as citizen science observation data, to infer large‐scale properties of species’ distributions. However, the few publications that use opportunistic citizen science data to study animal ecology at a habitat level do so without accounting for spatial biases in opportunistic records or using methods that are difficult to generalize. In this study, we explore the biases that exist in opportunistic observations and suggest an approach to correct for them. We first examined the extent of the biases in opportunistic citizen science observations of three wild ungulate species in Norway by comparing them to data from GPS telemetry. We then quantified the extent of the biases by specifying a model of the biases. From the bias model, we sampled available locations within the species’ home range. Along with opportunistic observations, we used the corrected availability locations to estimate a resource selection function (RSF). We tested this method with simulations and empirical datasets for the three species. We compared the results of our correction method to RSFs obtained using opportunistic observations without correction and to RSFs using GPS‐telemetry data. Finally, we compared habitat suitability maps obtained using each of these models. Opportunistic observations are more affected by human access and visibility than locations derived from GPS telemetry. This has consequences for drawing inferences about species’ ecology. Models naïvely using opportunistic observations in habitat‐use studies can result in spurious inferences. However, sampling availability locations based on the spatial biases in opportunistic data improves the estimation of the species’ RSFs and predicted habitat suitability maps in some cases. This study highlights the challenges and opportunities of using opportunistic observations in habitat‐use studies. While our method is not foolproof it is a first step toward unlocking the potential of opportunistic citizen science data for habitat‐use studies.     

From species distributions to meta‐communities

The extent that biotic interactions and dispersal influence species ranges and diversity patterns across scales remains an open question. Answering this question requires framing an analysis on the frontier between species distribution modelling (SDM), which ignores biotic interactions and dispersal limitation, and community ecology, which provides specific predictions on community and meta‐community structure and resulting diversity patterns such as species richness and functional diversity. Using both empirical and simulated datasets, we tested whether predicted occurrences from fine‐resolution SDMs provide good estimates of community structure and diversity patterns at resolutions ranging from a resolution typical of studies within reserves (250 m) to that typical of a regional biodiversity study (5 km). For both datasets, we show that the imprint of biotic interactions and dispersal limitation quickly vanishes when spatial resolution is reduced, which demonstrates the value of SDMs for tracking the imprint of community assembly processes across scales.     

The limited spatial scale of dispersal in soil arthropods revealed with whole‐community haplotype‐level metabarcoding

Soil arthropod communities are highly diverse and critical for ecosystem functioning. However, our knowledge of spatial structure and the underlying processes of community assembly are scarce, hampered by limited empirical data on species diversity and turnover. We implement a high‐throughput sequencing approach to generate comparative data for thousands of arthropods at three hierarchical levels: genetic, species and supra‐specific lineages. A joint analysis of the spatial arrangement across these levels can reveal the predominant processes driving the variation in biological assemblages at the local scale. This multihierarchical approach was performed using haplotype‐level COI metabarcoding of entire communities of mites, springtails and beetles from three Iberian mountain regions. Tens of thousands of specimens were extracted from deep and superficial soil layers and produced comparative phylogeographic data for >1,000 codistributed species and nearly 3,000 haplotypes. Local assemblage composition differed greatly between grasslands and forests and, within each habitat, showed strong spatial structure and high endemicity. Distance decay was high at all levels, even at the scale of a few kilometres or less. The local distance decay patterns were self‐similar for the haplotypes and higher hierarchical entities, and this fractal structure was similar in all regions, suggesting that uniform processes of limited dispersal determine local‐scale community assembly. Our results from whole‐community metabarcoding provide insight into how dispersal limitations constrain mesofauna community structure within local spatial settings over evolutionary timescales. If generalized across wider areas, the high turnover and endemicity in the soil locally may indicate extremely high richness globally, challenging our current estimations of total arthropod diversity on Earth.     

Bacterial profiling of White Plague Disease across corals and oceans indicates a conserved and distinct disease microbiome

Coral diseases are characterized by microbial community shifts in coral mucus and tissue, but causes and consequences of these changes are vaguely understood due to the complexity and dynamics of coral‐associated bacteria. We used 16S rRNA gene microarrays to assay differences in bacterial assemblages of healthy and diseased colonies displaying White Plague Disease (WPD) signs from two closely related Caribbean coral species, Orbicella faveolata and Orbicella franksi. Analysis of differentially abundant operational taxonomic units (OTUs) revealed strong differences between healthy and diseased specimens, but not between coral species. A subsequent comparison to data from two Indo‐Pacific coral species (Pavona duerdeni and Porites lutea) revealed distinct microbial community patterns associated with ocean basin, coral species and health state. Coral species were clearly separated by site, but also, the relatedness of the underlying bacterial community structures resembled the phylogenetic relationship of the coral hosts. In diseased samples, bacterial richness increased and putatively opportunistic bacteria were consistently more abundant highlighting the role of opportunistic conditions in structuring microbial community patterns during disease. Our comparative analysis shows that it is possible to derive conserved bacterial footprints of diseased coral holobionts that might help in identifying key bacterial species related to the underlying etiopathology. Furthermore, our data demonstrate that similar‐appearing disease phenotypes produce microbial community patterns that are consistent over coral species and oceans, irrespective of the putative underlying pathogen. Consequently, profiling coral diseases by microbial community structure over multiple coral species might allow the development of a comparative disease framework that can inform on cause and relatedness of coral diseases.     

Dispersal ability links to cross‐scale species diversity patterns across the Eurasian Arctic tundra

Aim The role of dispersal in structuring biodiversity across spatial scales is controversial. If dispersal controls regional and local community assembly, it should also affect the degree of spatial species turnover as well as the extent to which regional communities are represented in local communities. Here we provide the first integrated assessment of relationships between dispersal ability and local‐to‐regional spatial aspects of species diversity across a large geographical area. Location Northern Eurasia. Methods Using a cross‐scale analysis covering local (0.64 m²) to continental (the Eurasian Arctic biome) scales, we compared slope parameters of the dissimilarity‐to‐distance relationship in species composition and the local‐to‐regional relationship in species richness among three plant‐like groups that differ in dispersal ability: lichens with the highest dispersal ability; mosses and moss allies with intermediate dispersal ability; and seed plants with the lowest dispersal ability. Results Diversity patterns generally differed between the three groups according to their dispersal ability, even after controlling for niche‐based processes. Increasing dispersal ability is linked to decreasing spatial species turnover and an increasing ratio of local to regional species richness. All comparisons supported our expectations, except for the slope of the local‐to‐regional relationship in species richness for mosses and moss allies which was not significantly steeper than that of seed plants. Main conclusions The negative link between dispersal ability and spatial species turnover and the corresponding positive link between dispersal ability and the ratio of local‐to‐regional species richness support the idea that dispersal affects community structure and diversity patterns across spatial scales.     

Food‐web structure varies along environmental gradients in a high‐latitude marine ecosystem

Large‐scale patterns in species diversity and community composition are associated with environmental gradients, but the implications of these patterns for food‐web structure are still unclear. Here, we investigated how spatial patterns in food‐web structure are associated with environmental gradients in the Barents Sea, a highly productive shelf sea of the Arctic Ocean. We compared food webs from 25 subregions in the Barents Sea and examined spatial correlations among food‐web metrics, and between metrics and spatial variability in seawater temperature, bottom depth and number of days with ice cover. Several food‐web metrics were positively associated with seawater temperature: connectance, level of omnivory, clustering, cannibalism, and high variability in generalism, while other food‐web metrics such as modularity and vulnerability were positively associated with sea ice and negatively with temperature. Food‐web metrics positively associated with habitat heterogeneity were: number of species, link density, omnivory, path length, and trophic level. This finding suggests that habitat heterogeneity promotes food‐web complexity in terms of number of species and link density. Our analyses reveal that spatial variation in food‐web structure along the environmental gradients is partly related to species turnover. However, the higher interaction turnover compared to species turnover along these gradients indicates a consistent modification of food‐web structure, implying that interacting species may co‐vary in space. In conclusion, our study shows how environmental heterogeneity, via environmental filtering, influences not only turnover in species composition, but also the structure of food webs over large spatial scales.     

Accounting for spatial autocorrelation in null models of tree species association

A commonly used null model for species association among forest trees is a well‐mixed community (WMC). A WMC represents a non‐spatial, or spatially implicit, model, in which species form nearest‐neighbor pairs at a rate equal to the product of their community proportions. WMC models assume that the outcome of random dispersal and demographic processes is complete spatial randomness (CSR) in the species’ spatial distributions. Yet, stochastic dispersal processes often lead to spatial autocorrelation (SAC) in tree species densities, giving rise to clustering, segregation, and other nonrandom patterns. Although methods exist to account for SAC in spatially‐explicit models, its impact on non‐spatial models often remains unaccounted for. To investigate the potential for SAC to bias tests based upon non‐spatial models, we developed a spatially‐heterogeneous (SH) modelling approach that incorporates measured levels of SAC. Using the mapped locations of individuals in a tropical tree community, we tested the hypothesis that the identity of nearest‐neighbors represents a random draw from neighborhood species pools. Correlograms of Moran's I confirmed that, for 50 of 51 dominant species, stem density was significantly autocorrelated over distances ranging from 50 to 200 m. The observed patterns of SAC were consistent with dispersal limitation, with most species occurring in distinct patches. For nearly all of the 106 species in the community, the frequency of pairwise association was statistically indistinguishable from that projected by the null models. However, model comparisons revealed that non‐spatial models more strongly underestimated observed species‐pair frequencies, particularly for conspecific pairs. Overall, the CSR models projected more significant facilitative interactions than did SH models, yielding a more liberal test of niche differences. Our results underscore the importance of accounting for stochastic spatial processes in tests of association, regardless of whether spatial or non‐spatial models are employed.     

Fine‐scale quantification of floral and faunal breaks and their geographic correlates,with an example from south‐eastern Australia

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.