Cohesive Regions Research Articles

Flexure Performance of Textile-Reinforced Cementitious Composites with Novel Inclined Reinforcements.

Textile-reinforced cementitious composites have great potential to offer novel design opportunities for thin-section structures thanks to their superior material capabilities. In this work, new cementitious composites with novel reinforcement configurations are developed, which have superior mechanical properties. The cementitious composites contain inclined through-the-thickness reinforcements, and their enhanced performance on thin-section material hardening under flexural loading is demonstrated. Furthermore, a new practical FE modeling approach is proposed that involves the combined use of multiple cohesive regions and 1D reinforcement elements that pass through these regions with a bilinear material law. This approach provides a new computationally efficient modelling framework whereby reinforcement pull-out during hardening is readily captured without resorting to computationally demanding interface laws between the reinforcement and the cementititous matrix. The model can model enhanced hardening of new configurations and provides comparable results with the experimental findings. The model can be used in the modelling and design of novel cementitious composites with engineered reinforcement configurations. Overall, this study aims to open up new avenues for the smart material design of cementitious composites with novel structural reinforcements.

Mixed pituitary adenoma/pituitary neuroendocrine tumor-gangliocytoma: Immunohistochemical insights.

Mixed pituitary adenoma/PitNET-gangliocytomas (PA/PitNET-GC) have been reported in small series over the past 20 years; some had limited immunohistochemistry (IHC) data. We interrogated our experience over 20 years, focusing on patterns of the GC component and IHC results for anterior pituitary hormones, transcription factors, NFP, and CAM5.2. A search of cases from 2002 to 2023 yielded 20 cases: 7M:13F, ages 20-71 years; 17 macroadenomas, 1 microadenoma, 2 ectopic. GC was co-associated with 4 corticotroph, 2 densely granulated lactotroph, 5 mixed lactotroph-somatotroph, 1 immature PIT1-lineage tumor, and 8 sparsely granulated GH; the latter all had a minor lactotroph component. Patterns were: discrete nodular foci of GC (9/20), extensive GC differentiation often overshadowing the PA/PitNET (7/20), and intimate admixture of smaller bands of neuropil and individual metaplastic ganglion cells within PA/PitNET (4/20). NFP highlighted small cohesive regions of neuropil and identified greater axonal content, including individual axons within "pure" PA/PitNET areas, than appreciated on H&E. CAM5.2 IHC often revealed cells with neuronal morphologies to a greater extent than NFP and in different areas within the same tumor. These data suggest that the combined use of NFP and CAM5.2 IHC best reveals transition from PA to GC phenotype, with CAM5.2 positivity reflecting earlier stages of transformation.

Zoogeographical regions in the Atlantic Forest: patterns and potential drivers

AbstractAimTo delineate present‐day zoogeographical regions of terrestrial vertebrates (frogs, lizards, snakes, birds and non‐volant mammals) in the Atlantic Forest. Within each taxonomic group, we examine the relative importance of abrupt climatic transitions, orographic barriers, past climate change and rivers in shaping zoogeographical boundaries.LocationSouth America's Atlantic Forest.MethodsWe applied a network‐based method to delineate zoogeographical regions, using distribution data (range maps) for 455 species of frogs, 103 lizards, 220 snakes, 917 birds and 202 non‐volant mammals, in 50 × 50 km grid cells. We used hierarchical generalized linear mixed‐effects models to test environmental predictors associated with zoogeographical boundaries. Finally, we intersected the bioregion maps delineated for each group to identify general patterns across all vertebrates.ResultsWe identified four zoogeographical regions for birds and snakes, and five for frogs, lizards and non‐volant mammals. Depending on the group, contemporary and past climate conditions, elevation variation and/or rivers were associated with zoogeographical boundaries. The combined maps indicate that the Atlantic Forest retains four spatially cohesive zoogeographical regions based on present‐day distribution of vertebrates.Main conclusionsCross‐taxon congruence indicates that the geographical and environmental characteristics of the Atlantic Forest have a strong influence on the location of zoogeographical regions for vertebrates. In contrast, transition zones appear to be associated with the spatial distribution of life history traits of each group, potentially explaining the observed differences in the number of bioregions across groups and the position of zoogeographical boundaries. This work paves the way for further research into the evolutionary assembly of the Atlantic Forest's zoogeographical regions and may help inform conservation priorities for maintaining their distinctive faunas.

Strengthening aluminum matrix composite with additively manufactured 316L stainless steel lattice reinforcement: Processing methodology, mechanical performance and deformation mechanism

This study investigates various processing approaches, interface characteristics, and mechanical properties of an aluminum (Al) matrix composite reinforced with additively manufactured (AM) 316L stainless-steel (SS) lattice. The AM-316L-SS lattice, boasting a 30 % infill density, was fabricated using the laser powder bed fusion technique. The Al-matrix was integrated with the AM-316L-SS reinforcement through experimentation involving pre-stirring of the molten Al under pressurized and unpressurized die-casting conditions. A well-bonded interface, with cohesive regions, was obtained in the pre-stirred structures. In contrast, regions of decohesion were displayed in cast structures without pre-stirring, leading to the presence of pores and the manifestation of imperfect bond interfaces. Compression tests conducted on the sound composite demonstrated enhanced mechanical properties, with a compressive strength of approximately 163 MPa, significantly higher than that of the pure Al-matrix (approximately 80 MPa). Localized interface cracking was initiated by stress gradients and plastic deformation, leading to microcrack propagation into the Al-matrix.

Investigation of Lagrangian Areas of Minimal Stretching (LAMS) in a turbulent boundary layer

In this paper the three-dimensional finite-time Lyapunov exponent (FTLE) field of a direct numerical simulation of a flat-plate turbulent boundary layer is analysed in several wall-parallel sections. The data consider a case at a low subsonic Mach number with a moderate positive pressure gradient in the streamwise direction. In contrast to other studies mainly focusing on the maxima of the FTLE field, particular emphasis is placed on the regions of minimal stretching between the vortices and shear layers of the three-dimensional turbulent flow field. These visually appear as contiguous islands or ‘valleys’ between the ‘ridges’ of the FTLE maxima, both at forward and backward integration of the flow field in time. To clearly distinguish the structures investigated from their more common counterparts (e.g. Lagrangian coherent structures, LCS), the acronym LAMS (Lagrangian areas of minimal stretching) is proposed to denote the associated cohesive fluid regions. Consistent with intuition, the largest LAMS occur near the boundary-layer edge, where large regions of homogeneous laminar external flow coexist with upwelling turbulent structures. Compensating for turbulent regions pushing upward, they sink from there down toward the wall, becoming smaller and longer. This process is associated with an increased relative velocity of the LAMS compared with the mean flow, which is observed over the whole boundary layer in the range $y^+ \gtrsim 10$ . Furthermore, it is observed that the Q4 (sweep) events contained in the LAMS clearly dominate over Q2 (ejection) events above $y^+ \approx 10$ . Thereby, local maxima occur at $y^+ \approx 20$ and near the boundary-layer edge. Below $y^+ \approx 10$ , the relationship reverses. Sweeping LAMS from above $y^+ \approx 10$ and ejecting LAMS from below meet in the layer where the maximal vortical activity occurs. The latter is caused by mostly streamwise oriented vortices with maximal vortex stretching in the streamwise direction. Overall, LAMS are associated with cohesive fluid regions between the surrounding vortices and shear layers that both drop down from the boundary-layer edge toward the wall in the outer region of the boundary layer and lift from the wall in the near-wall region.

Competitiveness and cohesion in Romania's regional development: a territorial approach

The assessment of the socio-economic disparities at the regional level is one of the priority development topics. In particular, in formerly socialistic-planned countries, the development driven by the transition period, the accession to the European Union and the economic crisis, the regional disparities are present. The main aim of the research has been to identify the most competitive and the most cohesive Development Regions in Romania by computing, mapping and analysing two secondary indices (Territorial Competitiveness and Territorial Cohesion). Overall, the investigation shows that economic performance is more consolidated in central and western regions based on their mature and innovative industries, better-developed services and urbanisation/suburbanisation processes, while the eastern and southern development regions, with predominantly rural traits, experienced a significant industrial decline and social deprivation. The most competitive Development Region is Bucharest-Ilfov, given the advantage conferred by Bucharest Capital City, the main economic and social polarising centre in Romania. For reducing regional disparities, the Cohesion Policy should allocate increased funds for countries with least developed regions. The study provides the result of quantitative and qualitative analysis on the regional-level territorial disparities in Romania that could easily be considered as guidelines in the decision-making process while trying to achieve the competitiveness and cohesion goals.

An empirical analysis of dockless bike-sharing utilization and its explanatory factors: Case study from Shanghai, China

Revealing dockless bike-sharing utilization pattern and its explanatory factors are essential for urban planners and operators to improve the utilization and turnover of public bikes. This study explores the dockless bike-sharing utilization pattern from the perspective of bike using GPS-based bike origin-destination data collected in Shanghai, China. In this paper, utilization patterns are captured by decoupling several spatially cohesive regions with intensive bike use via non-negative matrix factorization. We then measure the utilization efficiency of bikes within each sub-region by calculating Time to booking (ToB) for each bike and explore how the built environment and social-demographic characteristics influence the bike-sharing utilization with ordinary least squares (OLS) regression and geographically weighted regression (GWR) models. The matrix factorization results indicate that the shared bikes mainly serve a certain area instead of the whole city. In addition, the GWR model shows higher explanatory power (Adjusted R2 = 0.774) than the OLS regression model (Adjusted R2 = 0.520), which suggests a close relationship between bike-sharing utilization and the selected explanatory variables. The coefficients of the GWR model reveal the spatial variations of the linkage between bike-sharing utilization and its explanatory factors across the study area. This study can shed light on understanding the demand and supply of shared bikes for rebalancing and provide support for operators to improve the dockless bike-sharing utilization efficiency.

Microdrilling of AA (6351)-SiC-B4C Composite Using Hybrid Micro-ECDM Process

Abstract In the present work, the microdrilling of a metal matrix composite (MMC) is performed by a combination of microelectrical discharge and electrochemical machining (the hybrid micro-ECDM process). The difficulties on machining the cohesive regions on the composite are studied through the control of machining parameters. The kerf/side gap of the holes, energetic regimes on the machined surface, and the surface texture are analyzed through optical microscope, scanning electron microscope, and energy dispersive spectroscopic images. From the observed results, it is found that the machining time increases with an increase in the discharge current and decrease in voltage. The fluctuations in material removal and the eccentricity towards the microdrill are also due to the change in current amplitude. Further, the formation of recast layer and the micropores on the machined surface are analyzed, and it is found that they are not completely eliminated but can be reduced with a change in process parameters.

“Dendrology” in Numerical Weather Prediction: What Random Forests and Logistic Regression Tell Us about Forecasting Extreme Precipitation

Three different statistical algorithms are applied to forecast locally extreme precipitation across the contiguous United States (CONUS) as quantified by 1- and 10-yr average recurrence interval (ARI) exceedances for 1200–1200 UTC forecasts spanning forecast hours 36–60 and 60–84, denoted, respectively, day 2 and day 3. Predictors come from nearly 11 years of reforecasts from NOAA’s Second-Generation Global Ensemble Forecast System Reforecast (GEFS/R) model and derive from a variety of thermodynamic and kinematic variables that characterize the meteorological regime in addition to the quantitative precipitation forecast (QPF) output from the ensemble. In addition to encompassing nine different atmospheric fields, predictors also vary in space and time relative to the forecast point. Distinct models are trained for eight different hydrometeorologically cohesive regions of the CONUS. One algorithm supplies the GEFS/R predictors directly to a random forest (RF) procedure to produce extreme precipitation forecasts; the second also employs RFs, but the predictors instead undergo principal component analysis (PCA), and extracted leading components are supplied to the RF. In the last algorithm, dimension-reduced predictors are supplied to a logistic regression (LR) algorithm instead of an RF. A companion paper investigated the quality of the forecasts produced by these models and other RF-based forecast models. This study is an extension of that work and explores the internals of these trained models and what physical and statistical insights they reveal about forecasting extreme precipitation from a global, convection-parameterized model.

Aridity drives plant biogeographical sub regions in the Caatinga, the largest tropical dry forest and woodland block in South America.

Our aims were to quantify and map the plant sub regions of the the Caatinga, that covers 844,453 km2 and is the largest block of seasonally dry forest in South America. We performed spatial analyses of the largest dataset of woody plant distributions in this region assembled to date (of 2,666 shrub and tree species; 260 localities), compared these distributions with the current phytogeographic regionalizations, and investigated the potential environmental drivers of the floristic patterns in these sub regions. Phytogeographical regions were identified using quantitative analyses of species turnover calculated as Simpson dissimilarity index. We applied an interpolation method to map NMDS axes of compositional variation over the entire extent of the Caatinga, and then classified the compositional dissimilarity according to the number of biogeographical sub regions identified a priori using k-means analysis. We used multinomial logistic regression models to investigate the influence of contemporary climatic productivity, topographic complexity, soil characteristics, climate stability since the last glacial maximum, and the human footprint in explaining the identified sub regions. We identified nine spatially cohesive biogeographical sub regions. Current productivity, as indicated by an aridity index, was the only explanatory variable retained in the best model, explaining nearly half of the floristic variability between sub regions. The highest rates of endemism within the Caatinga were in the Core and Periphery Chapada Diamantina sub regions. Our findings suggest that the topographic complexity, soil variation, and human footprint in the Caatinga act on woody plant distributions at local scales and not as determinants of broad floristic patterns. The lack of effect of climatic stability since the last glacial maximum probably results from the fact that a single measure of climatic stability does not adequately capture the highly dynamic climatic shifts the region suffered during the Pleistocene. There was limited overlap between our results and previous Caatinga classifications.

A Sparse Non-Negative Matrix Factorization Framework for Identifying Functional Units of Tongue Behavior From MRI.

Muscle coordination patterns of lingual behaviors are synergies generated by deforming local muscle groups in a variety of ways. Functional units are functional muscle groups of local structural elements within the tongue that compress, expand, and move in a cohesive and consistent manner. Identifying the functional units using tagged-magnetic resonance imaging (MRI) sheds light on the mechanisms of normal and pathological muscle coordination patterns, yielding improvement in surgical planning, treatment, or rehabilitation procedures. In this paper, to mine this information, we propose a matrix factorization and probabilistic graphical model framework to produce building blocks and their associated weighting map using motion quantities extracted from tagged-MRI. Our tagged-MRI imaging and accurate voxel-level tracking provide previously unavailable internal tongue motion patterns, thus revealing the inner workings of the tongue during speech or other lingual behaviors. We then employ spectral clustering on the weighting map to identify the cohesive regions defined by the tongue motion that may involve multiple or undocumented regions. To evaluate our method, we perform a series of experiments. We first use two-dimensional images and synthetic data to demonstrate the accuracy of our method. We then use three-dimensional synthetic and in vivo tongue motion data using protrusion and simple speech tasks to identify subject-specific and data-driven functional units of the tongue in localized regions.

High‐Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

AbstractThe aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary conditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal‐length time slices (2045–2054 and 2085–2094) are compared with a historical decade (1995–2004). Probability density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm‐side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm‐side shift with decreased variability. Using “business‐as‐usual” scenario, 5‐day heat waves are projected to occur at least 5–10 times per year in most CONUS and ≥95°F days will increase by 1–2 months by the end of the century.

Biogeographical patterns in vertebrate assemblages of the Czech Republic: regional division in the context of species' distributions in Europe

This study attempts to explore biogeographical patterns in vertebrate assemblages of the Czech Republic and to delineate faunal biogeographical regions of the country. We focused on native terrestrial species and first explored main gradients in the composition of their assemblages. The first gradient revealed by Principal Coordinate Analysis was best correlated with climatic variables, whereas the second gradient can be ascribed rather to longitude and to the associated habitat change. Using the spatially constrained clustering, the Czech Republic was divided into five cohesive regions and species above-average associated with these regions showed distinct distributions within the European continent. Delineated regions also significantly differed at least in three considered environmental variables. We provided clear evidence that species distribution data gathered by national mapping support main biogeographical patterns suggested by previously published expert-based classifications of the country. We also demonstrated that the fauna of the Czech Republic shows a biogeographical pattern very similar to that showed by natural habitats defined in terms of plant communities. This indicates that both fauna and flora of the Czech Republic yield to the same environmental forces and biogeographical processes such as spreading of faunistic and floristic elements from the adjacent Carpathian Mountains and the Pannonian Basin.

Overcoming barriers to institutional integration in European second-tier urban regions

ABSTRACTWithin the debates about the socio-economic advantages of cohesive urban regions, several barriers to institutional integration are said to exist, especially when a metropolitan government is absent and integration relies on inter-municipal cooperation. Some barriers are associated with different urban region structures, such as the asymmetric power relations and sociocultural contrasts between municipalities in systems with dominant core cities, or the lack of a leading city to overcome fragmentation and provide a shared identity in polycentric urban regions (PURs). This paper investigates whether urban regions formed around second-tier cities, whose features depart from both dominant core and PUR models, are able to mitigate these barriers when pursuing integration strategies. The analysis relies on interviews with municipal leaders in three representative European case studies, examining how they perceive the barriers to inter-municipal relations in second-tier urban regions. The findings show that perceptions vary not only between regions, with the three cases following different trajectories of integration, but also within regions, according to the geographical and socio-economic context of municipalities and the legacy of past relations. In general, barriers to integration are not minimized without explicit efforts to rebalance power relations, approach political cultures, mobilize core city leadership and develop a metropolitan identity.

Understanding operation behaviors of taxicabs in cities by matrix factorization

Taxicabs play significant roles in public transport systems in large cities. To meet repetitive demands of daily intra-urban travels, cabdrivers acquire self-organized habitual operation behaviors in space and time, largely with assistance of their longitudinal operating experience. Recognizing those collective operation behavior patterns of taxicabs will enable us to better design and implement public transport services and urban development plan. In this paper, we systematically study patterns of the spatial supply of 6000+ taxicabs in Wuhan, China based on a monthly collection of their digital traces and the non-negative matrix factorization method. We successfully identify a set of high-level statistical features of the spatial operation behaviors of taxicabs in Wuhan, providing valuable insights to our knowledge of the demand and supply of taxicabs in (similar) large cities. First, we decouple several spatially cohesive regions with intensive internal taxicab travels (termed as demand regions), which intuitively reveal the well-known multi-sectored urban configuration of Wuhan. Second, by applying the non-negative matrix factorization to taxicab's longitudinal traces, we uncover remarkably self-organized operation patterns of cabdrivers in space (termed as supply regions) as reactions to the sectored distribution of daily travel behaviors. We find that a large proportion of cabdrivers frequently operate within single specific service area and a small proportion of taxicabs works as shifting tools between different service areas. Last, we focus on performances of taxicabs with distinct spatial operation behaviors and unveil their statistical characteristics in terms of frequency, duration and distance with passenger on board. Our work demonstrates the great potential to understand and improve urban mobility and public transport system from cabdrivers' collective intelligence.

Crack path simulation in a particle-toughened interlayer within a polymer composite laminate

With recent advances in computational resources and the development of arbitrary cracking methods, such as the Augmented Finite Element Method (A-FEM), more complex simulations can now be represented featuring multiple interacting cracks. It has been established that Mode I crack propagation in particle-toughened interlayers within some toughened Carbon Fibre Reinforced Polymer (CFRP) laminates involves a discontinuous process zone, rather than a distinct crack tip. This results from multiple cracks forming ahead of the main crack that subsequently coalesce, leaving behind bridging ligaments that may then provide traction across the crack flanks. An idealised two-dimensional A-FEM model is presented in this work, which represents the ‘particles’ as one-dimensional cohesive regions. The model shows that variables such as particle spacing, distribution, strength and toughness, and fibre interface strength can be tailored in order to maintain the crack path within the interlayer. This competition between crack paths is important, as a reduction in composite toughness is reported when the crack path migrates to the fibre interface. The simulations are complemented by time-resolved Synchrotron Radiation Computed Tomography (SRCT) data, which identify the chronology of the damage processes, along with the effects of particle distribution on the crack path and the formation of bridging ligaments.

How do regional economies respond to crises? The geography of job creation and destruction in Sweden (1990–2010)

Using Swedish longitudinal micro-data, the aim of this paper is to analyse how regional economies respond to crises. This is made possible by linking gross employment flows to the notion of regional resilience. Our findings indicate that despite a steady national employment growth, only the three metropolitan regions have fully recovered from the recession of 1990. Further, we show evidence of high levels of job creation and destruction in both declining and expanding regions and sectors, and that the creation of jobs is mainly attributable to employment growth in incumbent firms, while job destruction is primarily due to exits and micro-plants. Although the geography of resistance to crises and the ability of adaptability in the aftermath vary, our findings suggest that cohesive (i.e., with many skill-related industries) and diverse (i.e., with a high degree of unrelated variety) regions are more resilient over time. We also find that resistance to future shocks (e.g., the 2008 recession) is highly dependent on the resistance to previous crises. In all, this suggests that the long-term evolution of regional economies also influences their future resilience.

A novel pattern mining approach for identifying cognitive activity in EEG based functional brain networks.

The complex nature of neuronal interactions of the human brain has posed many challenges to the research community. To explore the underlying mechanisms of neuronal activity of cohesive brain regions during different cognitive activities, many innovative mathematical and computational models are required. This paper presents a novel Common Functional Pattern Mining approach to demonstrate the similar patterns of interactions due to common behavior of certain brain regions. The electrode sites of EEG-based functional brain network are modeled as a set of transactions and node-based complex network measures as itemsets. These itemsets are transformed into a graph data structure called Functional Pattern Graph. By mining this Functional Pattern Graph, the common functional patterns due to specific brain functioning can be identified. The empirical analyses show the efficiency of the proposed approach in identifying the extent to which the electrode sites (transactions) are similar during various cognitive load states.

Identification of a Non-Pentapeptide Region Associated with Rapid Mycobacterial Evolution

A large portion of the coding capacity of Mycobacterium tuberculosis is devoted to the production of proteins containing several copies of the pentapeptide-2 repeat, namely the PE/PPE_MPTR proteins. Protein domain repeats have a variety of binding properties and are involved in protein-protein interactions as well as binding to other ligands such as DNA and RNA. They are not as common in prokaryotes, compared to eukaryotes, but the enrichment of pentapeptide-2 repeats in Mycobacteria constitutes an exception to that rule. The genes encoding the PE/PPE_MPTR proteins have undergone many rearrangements and here we have identified the expansion patterns across the Mycobacteria. We have performed a reclassification of the PE/PPE_MPTR proteins using cohesive regions rather than sparse domain architectures. It is clear that these proteins have undergone large insertions of several pentapeptide-2 domains appearing adjacent to one another in a repetitive pattern. Further, we have identified a non-pentapeptide motif associated with rapid mycobacterial evolution. The sequence composition of this region suggests a different structure compared to pentapeptide-2 repeats. By studying the evolution of the PE/PPE_MPTR proteins, we have distinguished features pertaining to tuberculosis-inducing species. Further studies of the non-pentapeptide region associated with repeat expansions promises to shed light on the pathogenicity of Mycobacterium tuberculosis.

Biogeographic distribution patterns and their correlates in the diverse frog fauna of the Atlantic Forest hotspot.

Anurans are a highly diverse group in the Atlantic Forest hotspot (AF), yet distribution patterns and species richness gradients are not randomly distributed throughout the biome. Thus, we explore how anuran species are distributed in this complex and biodiverse hotspot, and hypothesize that this group can be distinguished by different cohesive regions. We used range maps of 497 species to obtain a presence/absence data grid, resolved to 50×50 km grain size, which was submitted to k-means clustering with v-fold cross-validation to determine the biogeographic regions. We also explored the extent to which current environmental variables, topography, and floristic structure of the AF are expected to identify the cluster patterns recognized by the k-means clustering. The biogeographic patterns found for amphibians are broadly congruent with ecoregions identified in the AF, but their edges, and sometimes the whole extent of some clusters, present much less resolved pattern compared to previous classification. We also identified that climate, topography, and vegetation structure of the AF explained a high percentage of variance of the cluster patterns identified, but the magnitude of the regression coefficients shifted regarding their importance in explaining the variance for each cluster. Specifically, we propose that the anuran fauna of the AF can be split into four biogeographic regions: a) less diverse and widely-ranged species that predominantly occur in the inland semideciduous forests; b) northern small-ranged species that presumably evolved within the Pleistocene forest refugia; c) highly diverse and small-ranged species from the southeastern Brazilian mountain chain and its adjacent semideciduous forest; and d) southern species from the Araucaria forest. Finally, the high congruence among the cluster patterns and previous eco-regions identified for the AF suggests that preserving the underlying habitat structure helps to preserve the historical and ecological signals that underlie the geographic distribution of AF anurans.