Biogeographic regionalization of Odonata (Insecta) in the Neotropics: contrasting Anisoptera and Zygoptera spatial patterns

Biogeographic regionalization of Odonata (Insecta) in the Neotropics: contrasting Anisoptera and Zygoptera spatial patterns Peter Löwenberg-Neto1, Paola E. Coelho1 1 LaboratóriodeBiogeografia,UniversidadeFederaldaIntegraçãoLatino-Americana,UNILA,FozdoIguaçu,Brazil Corresponding author: Peter Löwenberg-Neto (peter.lowenber[email protected]) Editor Marcus Vinicius Cianciaruso Received 17 October 2025♦ Accepted 11 December 2025♦ Published 18 December 2025 Frontiers of Biogeography 18, 2025, e175261|DOI 10.21425/fob.18.175261 Copyright PeterLöwenberg-NetoandPaolaE.Coelho.This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. RESEARCH ARTICLE FRONTIERS OF BIOGEOGRAPHY Thescientificjournalof TheInternationalBiogeographySociety Abstract The Neotropical region stands as a significant hotspot for Odonata diversity, yet comprehensive spatial patterns have remained less elucidated. This study aimed to provide a comprehensive biogeographical regionalization of the order Odonata across the region, specifically investigating whether its extant suborders exhibit congruent or divergent spatial patterns. Geographic distribution data for 1,533 Neotropical Odonata species (666 Anisoptera, 867 Zygoptera) were sourced from the IUCN and analyzed using the Infomap Bioregion application to delineate distinct bioregions. Spatial associations between Odonata, Anisoptera, and Zygoptera bioregions, and nine thematic regionalizations, including ecoregions, biomes, climate types, and hydrobasins, were quantified using the V-measure (global association) and relative inhomogeneity (local association). The analyses successfully delineated 13 distinct bioregions for the entire order Odonata, 14 for Anisoptera, and 19 for Zygoptera, all supported by high levels of endemism. A moderate yet differentiated spatial association was observed between Odonata bioregions and those of its suborders, with Anisoptera showing a stronger congruence than Zygoptera, indicating Zygoptera’s more fragmented and less overarching biogeographical structure. Hydrological units, particularly watersheds at levels 2 and 3, consistently emerged as the most strongly correlated of odonate bioregions, reinforcing the paramount importance of aquatic habitats for these obligate aquatic organisms. In contrast, climate-based regionalizations showed the weakest spatial association. Local inhomogeneity maps further highlighted regional convergences, with areas like the Amazon basin showing strong Anisoptera congruence, while Zygoptera displayed more fragmented patterns tied to hydrological features across Central and northern South America. These findings strongly suggest that distinct dispersal capabilities of Anisoptera and Zygoptera influenced macro-scale biogeographical patterns, with riverine systems acting as fundamental structuring elements. Highlights • Here we delineated distinct Neotropical bioregions for Odonata and their suborders, revealing pronounced spatial heterogeneity and endemism across Central America, the northern Andes, the Amazon basin, and the southern Atlantic Forest. • We demonstrated that the two suborders possess contrasting architectures: Anisoptera align closely with the overall Odonata regionalization, whereas Zygoptera exhibit a distinct, finer‑grained fragmentation. • Watershed-based partitions (levels 2 and 3) provided the strongest spatial association with odonate bioregions, identifying hydrology rather than climate as the dominant correlate regionalization. • Our results establish a theory-informed baseline for freshwater conservation, linking suborder‑specific dispersal traits with hydrography to guide spatially explicit planning in the Neotropics. Keywords Aquatic habitats, biogeographical regionalization, conservation, dispersal, endemism, hydrology, neotropics, Odonata, spatial pattern, V-measure Frontiers of Biogeography 18, 2025, e175261 Peter Löwenberg-Neto and Paola E. Coelho 2 Introduction Biogeographic regionalization provides a theory-grounded framework to partition species turnover into spatially coherent units that reflect historical and ecological processes (Kreft and Jetz 2010; Morrone 2018; Flores-Tolentino et al. 2021). Freshwater insect assemblages are expected to respond strongly to landscape connectivity and barriers, with drainage divides and hydroscapes shaping the cohesion and boundaries of regional biotas (Perron et al. 2021; Crabot et al. 2022). The order Odonata, dragonflies (Anisoptera) and damselflies (Zygoptera), is an ancient, monophyletic lineage (Kohli et al. 2021) that occupies nearly all freshwater habitats across the globe (Kalkman et al. 2008; Beatty et al. 2023). With approximately 6,364 species described and estimates reaching 7,000–7,500 (Sandall et al. 2022), odonates are ecologically pivotal, functioning as predators across life stages and serving as bioindicators of aquatic ecosystem integrity (Renner et al. 2022; Iversen et al. 2025). The remarkable global distribution of Odonata, spanning all biogeographic regions except Antarctica, underscores their profound adaptability to diverse environmental conditions (Sandall et al. 2022; Willink et al. 2024). Building upon their impressive global distribution, the Neotropical region emerges as a paramount center of odonate diversity and endemism, hosting a significant proportion of the world’s species (Kalkman et al. 2008). With approximately 2,000 described species, representing nearly 30% of global odonate diversity, the Neotropics stand out as a major hotspot for dragonflies and damselflies (Sandall et al. 2022). The exceptional diversity in the region was primarily attributed to a combination of ecological and historical factors, including the high availability and heterogeneity of aquatic habitats, the low climatic seasonality, the historical stability of its extensive tropical forests (Beatty et al. 2022) and the historical dynamics of the Amazonian hydrology (Sánchez-Herrera et al. 2020). The overarching patterns of odonate distribution were primarily shaped by intricate climatic gradients (Kalkman et al. 2022; Iversen et al. 2025). Temperature profoundly influences diversity, showing a distinct increase from polar to equatorial regions (Sandall et al. 2022; Willink et al. 2024), while precipitation dictates richness from arid to more humid environments (Mähn et al. 2023). Beyond contemporary ecological drivers, current odonate biogeographic patterns are deeply rooted in historical processes spanning millions of years (Kalkman et al. 2008; Sánchez-Herrera et al. 2022; Mähn et al. 2023). Ancient geological events acted as both dispersal corridors and significant geographic barriers, influencing the distribution of entire families (Kalkman et al. 2008; Willink et al. 2024). Similarly, past climatic shifts have profoundly impacted regional faunas (Abott et al. 2022; Kalkman et al. 2022; Standring et al. 2022). Importantly, the two main suborders of Odonata, Anisoptera and Zygoptera, differ not only morphologically (Pinto 2024), but also in their ecological requirements and dispersal abilities (Mähn et al. 2023). These biological differences influenced geographic distribution patterns and responses to biogeographic barriers which were consistently demonstrated by studies focusing on Amazonian Odonata. Juen and De Marco (2012) found that Zygoptera, characterized by lower dispersal capabilities, exhibited higher levels of endemism and more distinct distributional patterns directly influenced by riverine barriers; their cladistic analyses showed clearer separation of interfluvial areas for Zygoptera, supporting the hypothesis that major rivers acted as effective barriers for this suborder. Conversely, the same study indicated that wide rivers did not significantly impede the distribution of Anisoptera, consistent with their greater vagility (Juen and De Marco 2012). Further, Alves-Martins et al. (2018) corroborated these findings through network modularity analyses, revealing that Zygoptera communities were compositionally more similar within interfluves than between them, leading to distinct biogeographic modules that align with river boundaries (e.g., the Guiana interfluve showing unique Zygoptera composition). In contrast, Anisoptera species exhibited broader distributions extending across multiple interfluves, with their biogeographic modules appearing scattered without a strong spatial pattern linked to riverine divisions, demonstrating that large Amazonian rivers do not act as significant dispersal barriers for this suborder (Alves-Martins et al. 2018). Alves‑Martins et al. (2019) identified a Clementsian metacommunity structure, characterized by discrete groups of co-occurring species replacing each other across boundaries, for both suborders across Amazonian interfluves. For Zygoptera, this pattern was strongly associated with the influence of major rivers, affirming their role in delimiting distinct biogeographic regions and restricting species ranges. For Anisoptera, however, although a Clementsian pattern was also observed, it was predominantly driven by geographic distance and broader environmental gradients, indicating that while distribution is structured, it is less directly constrained by specific riverine boundaries than by their inherent high dispersal capacity across wider geographical extents (Alves‑Martins et al. 2019). The contrasting dispersal dynamics between Anisoptera and Zygoptera (Juen and De Marco 2012; Alves-Martins et al. 2018; Alves‑Martins et al. 2019; Oliveira‑Junior et al. 2019) underscore the importance of understanding how ecological processes interact with physical landscape features to shape species distributions. We hypothesized that suborders differ in their biogeographic architecture owing to contrasting dispersal capacities and habitat associations. Specifically, we expected Zygoptera to exhibit more fragmented regionalization, reflecting tighter dependence on local hydroscapes, whereas Anisoptera would track broader-scale hydrological connectivity and thus display more geographically cohesive regions. We further predicted higher spatial congruence between Anisoptera and the combined Odonata regionalization than between Zygoptera and Odonata. Furthermore, while climatic gradients and historical processes were recognized as broad Frontiers of Biogeography 18, 2025, e175261 Biogeographic regionalization of Odonata in the Neotropics 3 shapers of odonate distribution globally (Kalkman et al. 2022; Mähn et al. 2023; Iversen et al. 2025), the specific environmental factors driving biogeographic patterns within highly biodiverse regions like the Neotropics remain less fully elucidated. Given Odonata’s obligate aquatic larval stage (Suhling et al. 2015), the relative influence of hydrological features versus broader climatic or historical patterns in defining their regional boundaries warrants detailed investigation. Comprehensive syntheses and spatially explicit maps of Odonata distribution patterns remain notably absent for the Neotropics (Kalkman et al. 2008), creating a significant knowledge gap with direct implications for conservation planning. To address this gap, we present a biogeographical regionalization of Odonata in the Neotropical region based on the geographic occurrence of all available species. Building on the observed differences in dispersal capacity across suborders, we further analyze Anisoptera and Zygoptera distributions separately, comparing the resulting spatial patterns to those derived for the entire order. This comparative approach enabled us to determine whether these taxonomic lineages manifest congruent or divergent organizational patterns in the Neotropics. Finally, we overlay these taxonomic regionalizations with thematic regionalizations for the region, aiming to identify potential correlates of the observed bioregionalizations. Methods Species geographic distribution data The geographic distribution data for Odonata species were sourced from the International Union for Conservation of Nature (IUCN, https://www.iucnredlist.org/resources/spatial‑data‑download). IUCN expert maps constitute a widely referenced dataset for species distributions, primarily compiled to guide conservation efforts. Their construction involves compiling accurate depictions of a taxon’s range by integrating known occurrences with expert knowledge of habitat and environmental limits, and standardized GIS layers. This process adheres to a “precautionary principle,” where delineations prioritize confirmed presences and suitable habitats, intentionally minimizing the risk of erroneously assumed presences (Herkt et al. 2017). Specifically, polygons were refined by removing unsuitable habitats (e.g., based on altitude) and generated using methods such as buffering occurrence points or aligning with specific hydrological basins (IUCN SS Red List Technical Working Group 2024). The Odonata polygon shapefile was filtered to maintain only species occurring within the neotropical extent. Two cosmopolitan Anisoptera species, Trameabasilaris (Palisto de Beauvois 1817) and Pantala flavescens (Fabricius, 1798), were excluded from the dataset. The resulting polygon layer comprised 1,533 Neotropical species. Subsequently, two additional polygon layers were generated by subdividing the data into Anisoptera (n = 666) and Zygoptera (n = 867) species. Delineation of biogeographic regions The geographic distributions of Odonata, Anisoptera and Zygoptera species, provided in polygon shapefiles, were analyzed using the Infomap Bioregion application (Edler et al. 2016). The Infomap Bioregion method applies an adaptive resolution framework that dynamically adjusts cell sizes according to the spatial density of species distribution data. A bipartite network was constructed, linking cells and species, and this network was subsequently simplified using the Map Equation algorithm. Bioregions were then identified by clustering the network with Markov chain-based methods (Edler et al. 2016). The method has been widely used for biogeographical regionalizations in the Neotropical region (e.g. Ferrari et al. 2022; Löwenberg‑Neto 2024; Silva et al. 2024). The Infomap Bioregion application v.1 was conducted online through its website www.mapequation.org/bioregions/ using the following values: unit = degree; maximum cell size = 4°; minimum cell size = 1°; maximum cell capacity = 100; minimum cell capacity = 10; number of iterations = 100; Cluster cost parameter = 1.00. We used an adaptive-resolution grid to balance information density and spatial continuity. Cell size decreases where polygons densely overlap, capturing finer turnover, and increases in data‑sparse areas to avoid spurious fragmentation. Occasional ‘islands’ of cells embedded within another bioregion may arise at ecotones, near data-sparse borders, or under strong local endemism. We therefore interpret such embedded cells as either transition zones or local signals of compositional uniqueness rather than cartographic inconsistencies (Edler et al. 2016). For transparency, we retained the algorithm’s native output. Comparing Odonata bioregions with suborder bioregions We assessed the degree of spatial association between Odonata bioregionalization and suborder bioregionalizations using the V-measure (Nowosad and Stepinski 2018). The V-measure, derived from information theory, quantifies the spatial association between two categorical spatial variables, such as regionalizations or thematic maps, by assessing their mutual homogeneity and completeness within a shared geographic domain. Homogeneity quantifies the extent to which spatial units from one regionalization are wholly contained within units of the other, while completeness assesses the converse. The V-measure is the harmonic mean between homogeneity and completeness and it ranges from 0 to 1, where 0 denotes no spatial correspondence and 1 indicates perfect spatial alignment between the compared regionalizations (Nowosad and Stepinski 2018). To determine whether the observed V-measure values differed from those expected by chance, a randomization procedure was used (e.g. Falaschi et al. 2023; Gross et al. 2025). For each pairwise comparison, the observed Frontiers of Biogeography 18, 2025, e175261 Peter Löwenberg-Neto and Paola E. Coelho 4 V-measure was compared against V-measures from 1,000 randomly generated regionalizations. These randomizations were produced by sampling a number of points equal to the number of spatial units (m) in the comparison, generating Voronoi polygons, and then clipping the polygons to the study area’s boundaries. Statistical significance was assessed using a p‑value, defined as the proportion of random regionalizations with a V-measure exceeding that observed between the empirical bioregions and the compared regionalization. We further investigated their local spatial correspondence by mapping bioregions’ inhomogeneities. Inhomogeneity quantifies the extent to which a spatial unit from one regionalization overlaps multiple categories of another, thereby indicating its internal compositional variance (Nowosad and Stepinski 2018). Relative inhomogeneity (rih) is expressed on a scale from 0 to 1, with 0 reflecting perfect homogeneity, the unit is entirely comprised of one category from the comparison map, and 1 indicating maximal heterogeneity, the unit contains an even mixture of categories relative to the studied domain. Spatial association between bioregions and thematic maps We assessed the degree of spatial association between the taxonomically defined bioregions and categorical thematic maps using the V-measure and relative inhomogeneity metrics (Nowosad and Stepinski 2018). Specifically, we quantitatevely compared the bioregions of Neotropical Odonata, including both Anisoptera and Zygoptera, with nine thematic regionalizations: (1) terrestrial ecoregions (Olson et al. 2001); (2) terrestrial biomes (Olson et al. 2001); (3) climatic types (Peel et al. 2007); (4) climatic zones (Peel et al. 2007); (5) hydrobasins level 2 (Lehner and Grill 2013); (6) hydrobasins level 3 (Lehner and Grill 2013); (7) simplified terrestrial biomes (Antonelli et al. 2018b); (8) biogeographical provinces (Morrone et al. 2022); and (9) biogeographical subregions (Morrone et al. 2022). For the pairs with the highest significant V‑measures, we investigated local spatial correspondence by mapping unit inhomogeneities. Results Bioregionalizations of Odonata, Anisoptera and Zygoptera Our geographic dataset comprehended 1,533 odonata species over the Neotropical region. The distribution of Anisoptera across different families was predominantly represented by Libellulidae (43%), Gomphidae (32%), and Aeshnidae (16%). A total of 867 Zygoptera species across 13 families were analyzed, with Coenagrionidae being the richest family (61%). Species geographic distributions were counted in 1-degree grid cells and showed marked spatial heterogeneity across the study region. Notable hotspots were found predominantly in Central America, northern Andes, in the Amazon basin, and southern portions of the Atlantic Forest (Fig. 1). Using the Infomap bioregions method, we identified a total of 13 distinct bioregions for Odonata species across the study area (Fig. 2). Species richness exhibited considerable variation among bioregions, with the Pan-Amazon Complex bioregion (A) supporting the highest diversity (972 species), followed by Atlantic Forests bioregion (D, 428 species) and Tropical Andes bioregion (E, 418 species). Species’ range size in number of bioregions revealed a high degree of endemism: 834 species were exclusive to a single bioregion and 330 species occupied two bioregions. For Anisoptera species, we identified a total of 14 distinct bioregions (Fig. 3). Species richness varied markedly among these bioregions, with bioregion An‑A supporting the highest diversity (519 species), followed by An‑C (226 species) and An‑D (159 species). Species’ range sizes revealed a high degree of endemism: 324 species were exclusive to a single bioregion, while 137 species were found in two bioregions. For Zygoptera species, we identified a total of 19 distinct bioregions (Fig. 4). Species richness varied substantially among these bioregions, with bioregion Zy-A supporting the highest diversity (323 species), followed by Zy-E (276 species) and Zy‑C (229 species). Species’ range sizes revealed a pronounced degree of endemism: 444 species were exclusive to a single bioregion, while 189 species were present in two bioregions. Global and local comparisons of Odonata bioregions with suborder bioregions The quantitative comparison between the bioregions of Odonata and those of its suborders are presented in Table 1. The results revealed a moderate spatial association between Odonata bioregions and those of its suborders, with a stronger association found for Anisoptera (V = 0.638) than for Zygoptera (V = 0.481). For the comparison between Odonata and Anisoptera, relatively high values of homogeneity (h = 0.59) and completeness (c = 0.69) were observed. This indicated that, on average, Odonata bioregions were reasonably homogeneous with respect to those of Anisoptera, and each Anisoptera bioregion was relatively well represented within the Odonata bioregions. In contrast, for the comparison with Zygoptera, homogeneity remained similar (h = 0.58), but completeness was substantially lower (c = 0.41). This indicated that Zygoptera bioregions more frequently intersected multiple Odonata bioregions and exhibited greater spatial fragmentation. The local geographic correspondences between the Odonata bioregions and bioregions of the Anisoptera and Zygoptera were assessed using the relative inhomogeneity index (rih). For Anisoptera, the results indicated that bioregions, notably in Mesoamerica as well as in the Greater and Lesser Antilles, displayed high rih values Frontiers of Biogeography 18, 2025, e175261 Biogeographic regionalization of Odonata in the Neotropics 5 Figure 1. Dataset overview of Neotropical Odonata (IUCN, n = 1,533 species). Bar plots detail the number of species by suborder (topleft), by family within each suborder (top-right for Anisoptera, bottom-right for Zygoptera), and by IUCN threat category (bottom-left): DD = Data Deficient, LC = Least Concern, NT = Near Threatened, VU = Vulnerable, EN = Endangered, CR = Critically Endangered. The main map shows the geographic distribution of species richness across the Neotropical region, with colors indicating the number of species per 1-degree grid cell (quartile-based intervals). Frontiers of Biogeography 18, 2025, e175261 Peter Löwenberg-Neto and Paola E. Coelho 6 Figure 2. Bioregions of Neotropical Odonata. The map shows the delimitation of thirteen bioregions (A–M) identified for Odonata species across the Neotropical region, each represented by a distinct color. Bar plots detail species richness per bioregion (left), indicated by the number of species in each bioregion (A–M), and the number of species according to their range size (right), represented as the number of bioregions occupied by the species. For the designation of bioregion names see Suppl. material 1. Frontiers of Biogeography 18, 2025, e175261 Biogeographic regionalization of Odonata in the Neotropics 7 Figure 3. Bioregions of Neotropical Anisoptera. The map shows the delimitation of fourteen bioregions (A to N, prefix An‑) identified for Anisoptera species across the Neotropical region, each represented by a distinct color. Bar plots detail species richness per bioregion (left), indicated by the number of species in each bioregion (A–N), and the number of species according to their range size (right), represented as the number of bioregions occupied by the species. Frontiers of Biogeography 18, 2025, e175261 Peter Löwenberg-Neto and Paola E. Coelho 8 Figure 4. Bioregions of Neotropical Zygoptera. The map shows the delimitation of nineteen bioregions (A to S, prefix Zy‑) identified for Zygoptera species across the Neotropical region, each represented by a distinct color. Bar plots detail species richness per bioregion (left), indicated by the number of species in each bioregion (A–S), and the number of species according to their range size (right), represented as the number of bioregions occupied by the species. Frontiers of Biogeography 18, 2025, e175261 Biogeographic regionalization of Odonata in the Neotropics 9 (yellow, Fig. 5A). These elevated values reflected considerable compositional dissimilarity, suggesting that the distribution of Anisoptera in these areas did not align well with the Odonata bioregions. Bioregions of high inhomogeneity were also observed along southern sections of the Atlantic coast of Brazil. Conversely, Anisoptera bioregions exhibiting low inhomogeneity (dark blue) included regions within Central America and southern South America (Fig. 5A). In these locations, the bioregions of Anisoptera demonstrated greater congruence with Odonata bioregions. The spatial pattern of Odonata inhomogeneity in relation to Anisoptera bioregions, the reciprocal map (Fig. 5B), revealed that regions encompassing Mesoamerica exhibited high rih values (yellow). This pattern indicated pronounced compositional divergence, indicating that the distribution of Odonata within these areas was not well aligned with the divisions defined by Anisoptera bioregions. Localized bioregions of elevated inhomogeneity (green) were also apparent within the Andean and Atlantic Forest regions, signifying additional zones where Odonata assemblages markedly differed from the underlying Anisoptera biogeographic structure. In contrast, low rih values (dark blue) were prevalent throughout the extensive Amazon region and western portion of the southern South American (Fig. 5B). In these regions, Odonata distribution was more closely congruent with Anisoptera bioregional boundaries (Fig. 6). For Zygoptera, the results revealed that bioregions throughout Central America, the lesser Antilles, and extensive portions of northern South America exhibited high rih values (yellow, Fig. 5C). These areas of elevated inhomogeneity indicated marked compositional differences, suggesting that Zygoptera assemblages in these zones were poorly aligned with the prevailing boundaries defined by Odonata bioregions. Additional clusters with high rih values were noted along the Atlantic coast of Brazil, within Andean regions and in the southern South America cone, highlighting further zones of discordance between Zygoptera and Odonata bioregions. Conversely, low rih values (dark blue) were particularly prominent across the western Amazon, northern part of the eastern Amazon, and northeast Atlantic coast (Fig. 5C). In these areas, the distribution of Zygoptera displayed greater spatial congruence with Odonata bioregions. The spatial pattern of Odonata inhomogeneity in relation to Zygoptera bioregions (Fig. 5D) demonstrated that broad expanses across South America, notably throughout the Amazon basin, exhibited high rih values. These bioregions of elevated inhomogeneity reflect pronounced compositional differences, indicating that Odonata assemblages in these zones do not correspond closely to the boundaries defined by Zygoptera bioregions. In contrast, low rih values (dark blue) were primarily found in Mesoamerica, portions of southern South America and selected stretches along the Pacific coast (Fig. 5D). These areas exhibited a stronger spatial congruence between Odonata bioregions and Zygoptera bioregional boundaries, indicating increased internal homogeneity. In these regions, the patterns of species composition for Odonata were more closely aligned with those established for Zygoptera, highlighting zones of greater biogeographic correspondence (Fig. 6). Spatial association between bioregions and thematic maps The comparison between Odonata, Anisoptera and Zygoptera bioregions and the thematic regionalization maps using the V-measure revealed notable differences in spatial associations (Table 2). The highest values were observed for watersheds level 2 and for watersheds level 3 (Lehner and Grill 2013), followed by the simplified terrestrial biomes (Antonelli et al. 2018b). The biogeographical provinces also yielded a relatively high value, while other schemes such as biogeographical subregions (Morrone et al. 2022) Table 1. Global measures of spatial comparison between bioregions of Odonata (m = 13) and bioregions of its suborders. m = number of bioregions, h = homogeneity, c = completeness, p = proportion of random regionalizations with a V-measure exceeding that observed between the Odonata bioregions and the suborder regionalizations. Odonata vs. m h C V-measure P Anisoptera 14 0.59 0.69 0.638 0.00* Zygoptera 19 0.58 0.41 0.481 0.00* Table 2. Global measures of association between bioregions of the neotropical Odonata, Anisoptera and Zygoptera and nine thematic maps. They were ordered by decreasing value of the V-measure comparison to Odonata bioregions. m = number of regions, it refers to the total number of polygons within the thematic map counted after the polygon layer has been clipped to the boundaries of the bioregions for use in randomizations. All calculated values were statistically significant (p < 0.01). Thematic map m Odonata V-measure Anisoptera V-measure Zygoptera V-measure Watersheds level 2 (Lehner and Grill 2013) 11 0.496 0.431 0.519 Terrestrial biomes (Antonelli et al. 2018b) 12 0.494 0.405 0.478 Watersheds level 3 (Lehner and Grill 2013) 40 0.469 0.394 0.525 Biogeographic provinces (Morrone et al. 2022) 57 0.411 0.324 0.490 Terrestrial ecoregions (Olson et al. 2001) 156 0.389 0.323 0.486 Biogeographic subregions (Morrone et al. 2022) 10 0.364 0.315 0.401 Terrestrial biomes (Olson et al. 2001) 8 0.314 0.307 0.326 Climatic types (Peel et al. 2007) 31 0.212 0.212 0.179 Climatic zones (Peel et al. 2007) 5 0.196 0.197 0.241 Frontiers of Biogeography 18, 2025, e175261 Peter Löwenberg-Neto and Paola E. Coelho 16 Sánchez-Herrera M, Beatty CD, Nunes R, Salazar C, Ware JL (2020) An exploration of the complex biogeographical history of the Neotropical banner‑wing damselflies (Odonata: Polythoridae). 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Diversity 14: 757. https://doi.org/10.3390/d14090757 Willink B, Ware JL, Svensson EI (2024) Tropical Origin, Global Diversification, and Dispersal in the Pond Damselflies (Coenagrionoidea) Revealed by a New Molecular Phylogeny. Systematic Biology 73(2): 290–307. https://doi.org/10.1093/sysbio/syae004 Supplementary materials Supplementary material 1 Designation of Odonata bioregions’ names (.pdf) Link: https://doi.org/10.21425/fob.18.175261.suppl1