Guiding Field Surveys of Brazilian Vulnerable Baetidae (Ephemeroptera) through Species Distribution Modeling

Guiding Field Surveys of Brazilian Vulnerable Baetidae (Ephemeroptera) through Species Distribution Modeling | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Guiding Field Surveys of Brazilian Vulnerable Baetidae (Ephemeroptera) through Species Distribution Modeling Gabriel Franco Borghetti, Ana Luiza-Andrade, Fabiana Criste Massariol, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8673498/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The Atlantic Forest ranks among the most endangered tropical forests worldwide, only 28% of the original vegetation cover remains. Recent modeling studies indicate a drastic reduction in suitable habitat for all Ephemeroptera across the Atlantic Forest biome in the near future. Preliminary analyses of extinction risk in the Brazil considered four species of Baetidae (Ephemeroptera) as facing a significant risk of extinction, three of them endemic, with restricted distribution, and from the Atlantic Forest biome. Given the ecological importance and the limited distributional knowledge of these taxa, this study aims to apply current environmental modelling approaches to identify potential occurrence sites for three species ( Adebrotus lugoi, Camelobaetidius juparana , and Camelobaetidius spinosus ) that are at risk of extinction, thereby guiding field search for new populations. The models indicated restricted and fragmented distributions for Adebrotus lugoi, Camelobaetidius juparana , and C. spinosus , consistent with the habitat loss in the Atlantic Forest. Adebrotus lugoi showed a strong dependence on thermal stability variables (bio8, bio9), typical of groundwater-influenced streams, which contributes to its restriction to high-elevation areas. Camelobaetidius juparana was primarily influenced by slope (50.4%), being associated with steep, oxygen-rich streams characterized by stable substrates; it also exhibited sensitivity to precipitation seasonality (bio16, bio19). Camelobaetidius spinosus responded mainly to temperature seasonality (bio7) and precipitation during cold periods (bio19), indicating adaptation to high-elevation environments with pronounced thermal variation and reproduction synchronized with the dry winter season. These results highlight fine-scale niche differentiation among the species, with high thermal and hydrological specialization. The strong dependence on climatic variables—rather than on land use (13.4% contribution for A. lugoi )—suggests that climate change represents the main threat to their persistence. Conservation strategies should prioritize the identification and protection of thermal and hydrological microrefugia, as well as microhabitat-scale restoration. In this perspective, based on models were proposed priority sampling sites for each species. impacts habitat loss mayflies endangered validation Figures Figure 1 Introduction Climate change, historically associated with long-term processes, has become an increasingly urgent and observable phenomenon, with measurable ecological effects occurring over just a few decades (dos Santos et al.2023). These rapid changes are strongly linked to land use and conversion activities, especially the deforestation of native forests for agriculture, pastures, and urban expansion (Hill et al. 2002 ; Parmesan and Yohe 2003 ). Such alterations have intensified the ongoing climate crisis and accelerated biodiversity loss, impacting even short-term ecological dynamics and species distributions (Vancine et al 2024 ). The vulnerability of species under these changing conditions can be influenced by several key factors: population size, dispersal capacity, and the availability of suitable ecological requirements to survival, growth, and reproduction (Prakash 2021 ). There is growing and consistent evidence that land use and climate change have already led to significant shifts in abundance, distribution, and diversity (Lenoir et al. 2020 ; Pilotto et al. 2020 ; Wilson and Fox 2021 ) underscoring the need for urgent conservation action. Despite their evident ecological importance, aquatic insects remain largely neglected in conservation literature (Chowdhury 2021), and strategies for their protection and management are underdeveloped compared to those for vertebrate species. Only recently have data been presented showing a general pattern of decline in insect diversity and abundance driven by factors such as agricultural intensification, habitat loss and fragmentation, pollution, invasive species, pesticide use, and climate change (Dicks et al. 2021 ; Outhwaite et al. 2022 ). Neotropical streams are among the most biodiverse aquatic ecosystems worldwide, yet their ecological organization and biodiversity drivers remain underexplored (Valente-Neto et al. 2025 ). Among freshwater invertebrates, some orders - such as Ephemeroptera - are particularly sensitive to environmental changes and play a central role in biomonitoring due to their low tolerance to disturbances, especially elevated temperatures (Kitchin 2005 ; Ramulifho et al. 2020 ; Rosenberg and Resh 1993 ). These insects are especially diverse in lotic ecosystems (rivers and streams), where they function as primary consumers of algae and periphyton and serve as a crucial food source for higher trophic levels, including fish and other aquatic invertebrates (Brittain 1982 ; Salles 2006 ). Despite their ecological relevance, it was only in 2022 that the order Ephemeroptera was effectively recognized as essential for the assessment of aquatic environments in Brazil, being included in the national list of species threatened with extinction (Brasil 2022). Preliminary analyses of extinction risk in the country considered seven species from this order as facing a significant risk of extinction (Brasil 2022), all of them from the Atlantic Forest biome. The Atlantic Forest ranks among the most endangered tropical forests worldwide (Safar et al. 2020 ), about 60% of Brazil’s population lives within the region originally occupied by this biome (Scarano and Ceotto 2015 ), and only 28% of the original vegetation cover remains (Rezende et al. 2018 ; Vale et al. 2021 ). Recent modeling studies indicate a drastic reduction in suitable habitat for Ephemeroptera across the Atlantic Forest biome in the near future (Souza et al. 2024 ).The species currently classified as threatened often have extremely restricted distributions, based on few historical records. This lack of data hampers both the validation of extinction risk assessments and the implementation of effective conservation actions. The difficulty in locating populations may be a direct results of substantial population declines, suggesting that some species could already be at brink of extinction. Within Ephemeroptera, the family Baetidae stands out as one of the most diverse groups, comprising over 1,000 species worldwide (Gattolliat & Nieto 2009). In the Neotropical region, genera such as Adebrotus and Camelobaetidius remain poorly studied, with most species described from limited material and type localities (Salles et al. 2014). The three vulnerable species addressed in this study— A. lugoi , C. juparana , and C. spinosus —were all described within the last two decades and are each known from fewer than ten collection records. This extremely limited data highlights the urgent need for targeted field surveys and updated modelling efforts to better assess their current conservation status and predict potential distribution under future climate scenarios. Modelling species with few known occurrences remains a controversial topic, often referred to as the rare-species modelling paradox (Lomba et al. 2010). Paradoxically, the species that most urgently need modelling are those with the greatest methodological limitations (Raia et al. 2020; Svenning et al. 2011; Varela et al. 2011). This challenge represents one of the main obstacles to studying and locating species with a high probability of extinction, such as those considered rare. Currently, there is no robust methodological tool capable of fully mitigating the uncertainty associated with species distribution modelling for conservation planning in this context. Therefore, the most effective approach involves generating models by integrating available occurrence data with satellite imagery to propose specific coordinates for field surveys —still the only precise form of model validation (Johnson et al. 2023). An iterative process of model creation, validation, evaluation, and refinement (Sofaer et al. 2019) can provide a comprehensive framework for defining the distribution and conservation needs of at-risk species, while minimizing uncertainty and improving model accuracy. Given the ecological importance and the limited distributional knowledge of these taxa, this study aims to apply current environmental modelling approaches to identify potential occurrence sites for three Ephemeroptera species ( Adebrotus lugoi , Camelobaetidius juparana , and Camelobaetidius spinosus ) that are at risk of extinction, thereby guiding targeted field research. Material and Methods Species, Occurrence Data, And Study Area The distribution modeling was conducted for three Ephemeroptera species threatened with extinction in Brazil (Brazil 2022): Adebrotus lugoi Salles, 2010, Camelobaetidius juparana , Boldrini & Salles, 2012 and Camelobaetidius spinosus , Boldrini & Salles, 2012. Occurrence records were obtained from the taxonomic bibliography of each species, EphemBrazil database (Salles et al 2023), and unpublished occurrence records of FCM. Records with taxonomical uncertainty (potential misidentification) were not used. The choice of the Atlantic Forest biome as an accessible (or calibration) area took into account the evolutionary history of the species. All are part of the biome, with a potential broad distribution in the pre-fragmentation past. Environmental Variables All 19 bioclimatic variables from WorldClim v2.1 (https://www.worldclim.org/data/index.html) for current periods were selected (Fick & Hijmans, 2017). In addition to the climatic variables, five terrain variables were chosen: elevation, slope, flowacc (number of cells with small stream flow/capture), flow length (number of cells with upstream streams) (site: https://www.earthenv.org/streams), and land use (LI et al., 2017). All variables have a resolution at the equator of approximately 1 x 1 km. To avoid multicollinearity and reduce the number of variables, a Pearson Correlation was performed with a threshold of 0.7. The models were created using Annual temperature range (BIO5-BIO6), Mean temperature of the wettest quarter, Mean temperature of the driest quarter, Precipitation of the wettest quarter, Precipitation of the driest quarter, Precipitation of the warmest quarter, Precipitation of the coldest quarter, Slope, Land use. Modelling procedures and evaluation Pseudo-absences points were environmentally constrained based on the Bioclim model and within a 5 km buffer around known geographical locations and based on the lowest suitable region predicted (Lobo et al. 2010). The number of pseudo-absences points used was equivalent to the number of presences. This decision to employ pseudo-absence plotting methods limited to specific environmental and geographic conditions has proven to be more effective compared to random allocation methods (Iturbide et al. 2015). Models were constructed using three algorithms, Bioclim (BIO - Presence) (HIJMANS et al., 2017), Domain (DOM - Presence) (HIJMANS et al., 2017), and Random Forest (RDF - Presence and Pseudo-absence) (LIAW; WIENER, 2002). The challenge of modeling rare, endemic, and restricted species is a well-known phenomenon (BREINER et al., 2015). This difficulty arises primarily from the low sample size and limited spatial replications when fitting climate data (BOTTS et al., 2013; BREINER et al., 2015; GALANTE et al., 2018). We use a random bootstrap partitioning, with 10 replicates with 70% of the data used to fit, method usually used to taxa with fewer than 10 occurrences (e.g. Cardoso et al 2023). To validate the performance of the models, the metrics Area Under the Curve (AUC), Jaccard, Sørensen, and Fpb were used (ANDRADE et al., 2020) (see supplementary material). However, given the endemism and spatial restriction, which result in a small number of occurrences, the models were also validated by experts, who assessed whether the models made biological sense. The Jaccard metric was used to calculate threshold-dependent metrics. This metric is independent of correct absences (True Negative) and are less influenced by the extent of the accessible area and/or the pseudo-absence allocation method used (prevalence), making it a recommended choice (Leroy et al. 2018). The final models were generated using the ensemble method, mean the best-performing algorithms, using Jaccard. This approach ensure the inclusion of high-quality predictions in the final model. The ensemble models were binarized using a threshold that maximized the Jaccard metric, resulting in optimal values of sensitivity (1.0) and specificity (1.0). We evaluated the model extrapolation using Mobility-Oriented Parity (MOP) analysis (OWENS et al., 2013). The ensemble models were limited by assuming a potential distribution only in cells up to 5% of extrapolation. All analyses were conducted using the ENMTML package (ANDRADE et al., 2020) in the R 4.1.2 environment. The open-source software QGIS version 3.16.2 was used to produce maps and to locate species occurrence records. The "QuickMapService" plugin, which provides a collection of satellite imagery for terrestrial visualization, was to select the watercourses with the best suitability, with projection EPSG 4326. Results Environmental Variable Importance In the current condition, the three studied species exhibited distinct patterns of suitability and distribution. Overall, temperature-related variables showed the highest mean contribution across species, followed by precipitation metrics and slope, suggesting that thermal and hydrological regimes are key predictors of habitat suitability for these Ephemeroptera (Table 1). Adebrotus lugoi models were dominated by temperature-related variables, particularly Mean Temperature of Wettest Quarter (bio8: 24.7%) and Mean Temperature of Driest Quarter (bio9: 20.7%), suggesting strong dependence on thermal stability throughout the year. Land use (13.4%) also contributed significantly, indicating sensitivity to habitat degradation. Camelobaetidius juparana showed the strongest association with topographic variables, with slope contributing 50.4% (bio 21) to model predictions, followed by precipitation variables (bio16: 12.8%). This pattern reflects the species' preference for steep, well-drained headwater streams with high oxygen levels. Camelobaetidius spinosus responded primarily to temperature seasonality (bio7: 20.7%) and thermal extremes (bio8: 22.5%), combined with precipitation patterns during dry periods (bio17, bio19: 18.3% each). These results suggest that, even under current conditions, these species already face significant limitations in terms of suitable habitat, which reinforces their vulnerability Table 1. Average contribution (%) of environmental variables in ecological niche models for three Ephemeroptera species. Variable A. lugoi C. juparana C. spinosus bio7 (Temperature Annual Range) 5,10% 5,10% 20,70% bio8 (Mean Temperature of Wettest Quarter) 24,70% 7,20% 22,50% bio9 (Mean Temperature of Driest Quarter) 20,70% 6,80% 3,00% bio16 (Precipitation of Wettest Quarter) 1,10% 12,80% 6,40% bio17 (Precipitation of Driest Quarter) 5,70% 5,00% 18,30% bio18 (Precipitation of Warmest Quarter) 4,50% 5,10% 4,10% bio19 (Precipitation of Coldest Quarter) 10,80% 7,50% 18,30% bio21 (Slope) 14,00% 50,40% 6,20% bio24 (Land cover) 13,40% 0,20% 0,40% Current Distribution Patterns Under current conditions, all three species exhibited highly restricted and fragmented potential distributions, concentrated in Atlantic Forest remnants of southeastern Brazil (Figure 1). Total suitable habitat area was limited for all species: A. lugoi (2,847 km²), C. juparana (4,163 km²), and C. spinosus (3,291 km²). These areas represent less than 2% of the original Atlantic Forest extent in southeastern Brazil, highlighting the severe habitat restriction faced by these endemic species. Adebrotus lugoi showed a fragmented distribution with suitable areas mainly in Espírito Santo and scattered fragments in eastern Minas Gerais. The model indicated high suitability in specific regions of Espírito Santo (> 0.80), were confined mainly to the Northern region of Espírito Santo and nearby protected areas. Camelobaetidius juparana displayed broader, yet discontinuous suitability across Minas Gerais, Espírito Santo, and Rio de Janeiro, following steep slopes and high-elevation areas in the Serra do Mar and Mantiqueira ranges. Camelobaetidius spinosus , on the other hand, despite having medium suitability in several states (such as MG, SP, and RJ), but confirmed records only from Minas Gerais, it’s predicted distribution was concentrated in high-elevation zones of the Espinhaço and Mantiqueira ranges, with isolated patches in the Serra do Caparaó. Our models highlighted priority sampling sites combining high suitability (>0.60) and proximity to known records. For A. lugoi , Rio Cotaxé (-40.421655, -18.539256) and Rio Bananal (-40.295608, -19.254604) in Espírito Santo showed top suitability, consistent with its preference for stable thermal regimes (bio8: 24.7%) and intact riparian forests (Souza et al., 2024). For C. juparana , Cachoeira da Fumaça (-41.719706, -21.023790) and Rio Muriaé (-41.751730, -21.303870) reached optimal suitability (>0.80), driven by steep slopes (bio21: 50.4%) that sustain oxygen-rich habitats (Salles, 2006). For C. spinosus , despite post-Mariana habitat degradation (Brasil/IBAMA, 2015), Cachoeira Santana (-42.491744, -19.616520) remains notable for its marginal suitability (0.40) and relative isolation from impacted areas.. Discussion The restricted and fragmented distributions of Adebrotus lugoi , Camelobaetidius juparana , and Camelobaetidius spinosus revealed by our models align with broader patterns of habitat loss in the Atlantic Forest, where only 28% of original vegetation remains (Rezende et al., 2018 ). This biome’s degradation has disproportionately impacted aquatic insects, as highlighted by Souza et al. ( 2024 ), who projected severe habitat suitability declines for Ephemeroptera under climate change. Our results extend their work by pinpointing potential microrefugia for three overlooked species, emphasizing the role of temperature stability (e.g., A. lugoi ’s dependence on bio8, Mean Temperature of Wettest Quarter) and hydrological regimes (e.g., C. juparana ’s association with slope and precipitation seasonality). The distinct environmental drivers identified for each species reflect fine-scale niche differentiation within the Baetidae family (Taylor et al. 2020 ), supporting the hypothesis that specialized habitat requirements contribute to their rarity and endemism. A. lugoi ’s dependence on thermal stability (high contribution of bio8 and bio9) suggests adaptation to spring-fed or groundwater-influenced streams that buffer temperature fluctuations—a habitat increasingly rare in the fragmented Atlantic Forest landscape (Safar et al., 2020 ). This thermal specialization may explain the species’ restriction to high-elevation sites, where groundwater discharge is more common and forest cover provides additional thermal buffering (de Andrade et al., 2024)] The overwhelming importance of slope for C. juparana (50.4% contribution) indicates strong selection for high-gradient streams that maintain elevated dissolved oxygen and stable substrates required for larval development. This aligns with broader Baetidae ecology, where rheophilic species show narrow tolerance ranges for flow velocity and substrate stability (Brittain, 1982 : Kubendran et al., 2017 ). The association with precipitation seasonality (bio16, bio19) further suggests sensitivity to hydrological regime alterations, making the species particularly vulnerable to projected precipitation shifts in the Atlantic Forest (Vale et al. 2021 ). C. spinosus showed the strongest response to temperature seasonality (bio7), indicating adaptation to environments with pronounced thermal variation—a trait characteristic of high-elevation Atlantic Forest sites where diurnal and seasonal temperature ranges are amplified by altitude and reduced canopy cover (Safar et al., 2020 ). Its dependence on precipitation during cold periods (bio19) may reflect breeding synchronized with winter dry seasons, when reduced flows expose suitable oviposition sites. This temporal specialization could explain its rarity and restricted distribution, as disruption of seasonal rainfall directly affects reproductive success. The Atlantic Forest’s vulnerability to climate shifts (Scarano & Ceotto, 2015 ) exacerbates threats to these Baetidae. C. spinosus , for instance, showed dependence on annual temperature range (bio7, 20.7%), a variable expected to intensify under global warming (Vale et al., 2021 ). Such niche specificity, combined with limited dispersal, may explain why the species persists only in Minas Gerais despite moderate suitability in neighboring states—a pattern echoing Ferreira et al. ( 2019 ) and recent findings linking stream fragmentation to reduced aquatic insect gene flow (Castillo-Pérez et al. 2025 ). While land use (bio24) significantly influenced A. lugoi (13.4% contribution), its minimal effects on Camelobaetidius spp. suggests that these species face greater risk from climate-related factors than direct habitat alteration. This contrasts with Safar et al. ( 2020 ), who emphasized forest resilience, but supports their argument that microhabitat-scale restauration is critical for conservation. Conclusion This study provides the first comprehensive assessment of potential habitat distributions of three endangered Baetidae species ( Adebrotus lugoi , Camelobaetidius juparana , and Camelobaetidius spinosus ) endemic to Atlantic Forest streams. Our distribution models identified distinct range patterns for each species, with high-suitability areas concentrated in remnant fragments of the Atlantic Forest—a biome that has lost over 70% of its original cover. These findings underscore the vulnerability of these organisms, whose survival critically depends on conserving aquatic habitats amid escalating climate change and anthropogenic pressures. The proposal of precise locations for the search for new populations, allowing the empirical validation of the models, greater clarity is expected regarding the vulnerability of these species. The methodological approach, combining ecological niche modeling with a precise indication of locations to be sampled, proved essential for addressing uncertainties inherent in studying rare species. The scarcity of historical records and the complexity of these insects' microhabitat requirements highlight the need for further research to refine model accuracy. From a conservation perspective, our results carry immediate implications. Protecting forest remnants in Espírito Santo, Minas Gerais, and Rio de Janeiro—particularly in priority areas identified by the models—is urgent to prevent the extinction of these species. Integrating these findings into public policies for ecological restoration and biodiversity monitoring could represent a significant leap forward in safeguarding Neotropical aquatic insects, which remain overlooked in national action plans. While science plays a pivotal role, effective conservation will require coordinated efforts among researchers, environmental managers, and local communities. Ultimately, this study not only maps critical habitats for endangered mayflies but also exposes the delicate balance between aquatic insects and their rapidly changing environments. The Atlantic Forest's plight mirrors global biodiversity crises, making these species both indicators and victims of ecosystem degradation. Declarations Funding We would like to thank the Rondônia Foundation for Supporting the Development of Scientific and Technological Actions and Research in the State of Rondônia (FAPERO) for funding the projects “Resistance and resilience of aquatic organisms in streams threatened by anthropogenic activities in the Amazon” (0012.067617/2022-90 / grant n°199/2022)” and “0012.068211/2022-24 - Ecology and Conservation of Ephemeroptera (Insecta): an approach from Brazil and the state of Rondônia.”; National Council for Scientific and Technological Development (CNPq) for funding the project “Diversity of Ephemeroptera (Insecta) in Brazil: expanding the frontiers of knowledge generation and dissemination” (process: 408346/2023-0, Call CNPq/MCTI/Nº10/2023); and PPBio Amazônia Ocidental (CNPq, processos 441260/2023-3 e 441228/2023-2). Author Contribution GFM, ALA, FCM and PVC contributed to the study conception and design; data acquisition and analysis; to the writing and correction of the text. All authors read and approved the final manuscript. Acknowledgements To UNIR (Federal University of Rondônia) for providing the computers in the Multi-User Space, which proved essential for the analyses conducted in this study. We would like to thank the Rondônia Foundation for Supporting the Development of Scientific and Technological Actions and Research in the State of Rondônia (FAPERO) for funding the projects “Resistance and resilience of aquatic organisms in streams threatened by anthropogenic activities in the Amazon” (0012.067617/2022-90 / grant n°199/2022)” and “0012.068211/2022-24 - Ecology and Conservation of Ephemeroptera (Insecta): an approach from Brazil and the state of Rondônia.” We also acknowledge the Public Call MCTI/FINEP/FNDCT Infrastructure for the Legal Amazon 2024 - Pró-Amazônia, reference 2359/24 - Strengthening Research Infrastructure in Rondônia as a strategy to reduce asymmetries and expand research in the Amazon: Subproject: Consolidating Biological Collections in Rondônia to expand the study of Amazonian Biodiversity; Centro Avançado de Pesquisa-Ação da Conservação e Recuperação Ecossistêmica da Amazônia - CAPACREAM (CNPq Proc. 444350/2024-1); National Council for Scientific and Technological Development (CNPq) for funding the project “Diversity of Ephemeroptera (Insecta) in Brazil: expanding the frontiers of knowledge generation and dissemination” (process: 408346/2023-0, Call CNPq/MCTI/Nº10/2023); and PPBio Amazônia Ocidental (CNPq, processos 441260/2023-3 e 441228/2023-2). 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Science of The Total Environment, 948 , 174824. https://doi.org/10.1016/j.scitotenv.2024.174824 Taylor, C. L., Barker, N. P., Barber-James, H. M., & Pereira-da-Conceicoa, L. L. (2020). Habitat requirements affect genetic variation in three species of mayfly (Ephemeroptera, Baetidae) from South Africa. ZooKeys, 936, 1-27. https://doi.org/10.3897/ZOOKEYS.936.38587 Vale, M. M., et al. (2021). Climate change and biodiversity in the Atlantic Forest: Best climatic models, predicted changes and impacts, and adaptation options. In M. C. M. Marques & C. E. V. Grelle (Eds.), The Atlantic Forest (pp. 151-170). Springer. https://doi.org/10.1007/978-3-030-55322-7 Valente-Neto, F., Mello, J. L. S., Pestana, G. C., et al. (2025). Ecological perspectives on the organization of biodiversity in Neotropical streams. Hydrobiologia, 852, 3025–3047. https://doi.org/10.1007/s10750-024-05631-1 Vancine, M. H., Muylaert, R. L., Niebuhr, B. B., Oshima, J. E. F., Tonetti, V., Bernardo, R., De Angelo, C., Rosa, M. R., Grohmann, C. H., & Ribeiro, M. C. (2024). The Atlantic Forest of South America: Spatiotemporal dynamics of the vegetation and implications for conservation. Biological Conservation , 291, 110499. https://doi.org/10.1016/j.biocon.2024.110499 Wilson, R. J., & Fox, R. (2021). Insect responses to global change offer signposts for biodiversity and conservation. Ecological Entomology, 46 (4), 699-717. https://doi.org/10.1111/een.12970 Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8673498","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":593970478,"identity":"a65da630-b179-42ab-9c57-5615c698e20f","order_by":0,"name":"Gabriel Franco Borghetti","email":"data:image/png;base64,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","orcid":"","institution":"Universidade Federal de Rondônia (UNIR)","correspondingAuthor":true,"prefix":"","firstName":"Gabriel","middleName":"Franco","lastName":"Borghetti","suffix":""},{"id":593970479,"identity":"48b5e384-a9be-41e8-bcc3-9c09b85f83c4","order_by":1,"name":"Ana Luiza-Andrade","email":"","orcid":"","institution":"Universidade Federal de Rondônia (UNIR)","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"","lastName":"Luiza-Andrade","suffix":""},{"id":593970480,"identity":"dba98cd7-d439-4d2a-b66e-7c04782f4de1","order_by":2,"name":"Fabiana Criste Massariol","email":"","orcid":"","institution":"Prefeitura municipal de Vila Velha","correspondingAuthor":false,"prefix":"","firstName":"Fabiana","middleName":"Criste","lastName":"Massariol","suffix":""},{"id":593970481,"identity":"53f6c873-ca51-42e3-9464-20c185d45135","order_by":3,"name":"Paulo Vilela Cruz","email":"","orcid":"","institution":"Universidade Federal de Rondônia (UNIR)","correspondingAuthor":false,"prefix":"","firstName":"Paulo","middleName":"Vilela","lastName":"Cruz","suffix":""}],"badges":[],"createdAt":"2026-01-22 22:53:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8673498/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8673498/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103225608,"identity":"29d5b2cf-c219-4208-a3d0-b274298a797e","added_by":"auto","created_at":"2026-02-23 10:58:58","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":208928,"visible":true,"origin":"","legend":"\u003cp\u003ePotential distribution of endangered species of Baetidae under current conditions. A. \u003cem\u003eAdebrotus lugoi\u003c/em\u003e; B. \u003cem\u003eCamelobaetidius juparana; \u003c/em\u003eC. \u003cem\u003eCamelobaetidius spinosus\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8673498/v1/e7a375e4d8bfab959051d00b.jpeg"},{"id":109249454,"identity":"9bf36375-d882-4471-8cbc-7834bf7cd1b3","added_by":"auto","created_at":"2026-05-14 08:53:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":421822,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8673498/v1/bddefaf4-63bf-4ae9-b237-ded104a262f0.pdf"},{"id":103505647,"identity":"01ebc302-bcf5-4653-88ef-59637850152b","added_by":"auto","created_at":"2026-02-26 13:32:24","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":32381,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8673498/v1/e59504169cc9f34b9e856149.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Guiding Field Surveys of Brazilian Vulnerable Baetidae (Ephemeroptera) through Species Distribution Modeling","fulltext":[{"header":"Introduction","content":"\u003cp\u003eClimate change, historically associated with long-term processes, has become an increasingly urgent and observable phenomenon, with measurable ecological effects occurring over just a few decades (dos Santos et al.2023). These rapid changes are strongly linked to land use and conversion activities, especially the deforestation of native forests for agriculture, pastures, and urban expansion (Hill et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Parmesan and Yohe \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Such alterations have intensified the ongoing climate crisis and accelerated biodiversity loss, impacting even short-term ecological dynamics and species distributions (Vancine et al \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe vulnerability of species under these changing conditions can be influenced by several key factors: population size, dispersal capacity, and the availability of suitable ecological requirements to survival, growth, and reproduction (Prakash \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). There is growing and consistent evidence that land use and climate change have already led to significant shifts in abundance, distribution, and diversity (Lenoir et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Pilotto et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wilson and Fox \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) underscoring the need for urgent conservation action.\u003c/p\u003e \u003cp\u003eDespite their evident ecological importance, aquatic insects remain largely neglected in conservation literature (Chowdhury 2021), and strategies for their protection and management are underdeveloped compared to those for vertebrate species. Only recently have data been presented showing a general pattern of decline in insect diversity and abundance driven by factors such as agricultural intensification, habitat loss and fragmentation, pollution, invasive species, pesticide use, and climate change (Dicks et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Outhwaite et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNeotropical streams are among the most biodiverse aquatic ecosystems worldwide, yet their ecological organization and biodiversity drivers remain underexplored (Valente-Neto et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Among freshwater invertebrates, some orders - such as Ephemeroptera - are particularly sensitive to environmental changes and play a central role in biomonitoring due to their low tolerance to disturbances, especially elevated temperatures (Kitchin \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Ramulifho et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Rosenberg and Resh \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). These insects are especially diverse in lotic ecosystems (rivers and streams), where they function as primary consumers of algae and periphyton and serve as a crucial food source for higher trophic levels, including fish and other aquatic invertebrates (Brittain \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Salles \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite their ecological relevance, it was only in 2022 that the order Ephemeroptera was effectively recognized as essential for the assessment of aquatic environments in Brazil, being included in the national list of species threatened with extinction (Brasil 2022). Preliminary analyses of extinction risk in the country considered seven species from this order as facing a significant risk of extinction (Brasil 2022), all of them from the Atlantic Forest biome. The Atlantic Forest ranks among the most endangered tropical forests worldwide (Safar et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), about 60% of Brazil\u0026rsquo;s population lives within the region originally occupied by this biome (Scarano and Ceotto \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and only 28% of the original vegetation cover remains (Rezende et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Vale et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecent modeling studies indicate a drastic reduction in suitable habitat for Ephemeroptera across the Atlantic Forest biome in the near future (Souza et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).The species currently classified as threatened often have extremely restricted distributions, based on few historical records. This lack of data hampers both the validation of extinction risk assessments and the implementation of effective conservation actions. The difficulty in locating populations may be a direct results of substantial population declines, suggesting that some species could already be at brink of extinction.\u003c/p\u003e \u003cp\u003eWithin Ephemeroptera, the family Baetidae stands out as one of the most diverse groups, comprising over 1,000 species worldwide (Gattolliat \u0026amp; Nieto 2009). In the Neotropical region, genera such as \u003cem\u003eAdebrotus\u003c/em\u003e and \u003cem\u003eCamelobaetidius\u003c/em\u003e remain poorly studied, with most species described from limited material and type localities (Salles et al. 2014). The three vulnerable species addressed in this study\u0026mdash;\u003cem\u003eA. lugoi\u003c/em\u003e, \u003cem\u003eC. juparana\u003c/em\u003e, and \u003cem\u003eC. spinosus\u003c/em\u003e\u0026mdash;were all described within the last two decades and are each known from fewer than ten collection records. This extremely limited data highlights the urgent need for targeted field surveys and updated modelling efforts to better assess their current conservation status and predict potential distribution under future climate scenarios.\u003c/p\u003e \u003cp\u003eModelling species with few known occurrences remains a controversial topic, often referred to as the rare-species modelling paradox (Lomba et al. 2010). Paradoxically, the species that most urgently need modelling are those with the greatest methodological limitations (Raia et al. 2020; Svenning et al. 2011; Varela et al. 2011). This challenge represents one of the main obstacles to studying and locating species with a high probability of extinction, such as those considered rare.\u003c/p\u003e \u003cp\u003eCurrently, there is no robust methodological tool capable of fully mitigating the uncertainty associated with species distribution modelling for conservation planning in this context. Therefore, the most effective approach involves generating models by integrating available occurrence data with satellite imagery to propose specific coordinates for field surveys \u0026mdash;still the only precise form of model validation (Johnson et al. 2023). An iterative process of model creation, validation, evaluation, and refinement (Sofaer et al. 2019) can provide a comprehensive framework for defining the distribution and conservation needs of at-risk species, while minimizing uncertainty and improving model accuracy.\u003c/p\u003e \u003cp\u003eGiven the ecological importance and the limited distributional knowledge of these taxa, this study aims to apply current environmental modelling approaches to identify potential occurrence sites for three Ephemeroptera species (\u003cem\u003eAdebrotus lugoi\u003c/em\u003e, \u003cem\u003eCamelobaetidius juparana\u003c/em\u003e, and \u003cem\u003eCamelobaetidius spinosus\u003c/em\u003e) that are at risk of extinction, thereby guiding targeted field research.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e\u003cstrong\u003eSpecies, Occurrence Data, And Study Area\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe distribution modeling was conducted for three Ephemeroptera species threatened with extinction in Brazil (Brazil 2022): \u003cem\u003eAdebrotus lugoi\u003c/em\u003e Salles, 2010,\u003cem\u003e\u0026nbsp;Camelobaetidius juparana\u003c/em\u003e, \u0026nbsp;Boldrini \u0026amp; Salles, 2012 and \u003cem\u003eCamelobaetidius spinosus\u003c/em\u003e, Boldrini \u0026amp; Salles, 2012.\u003c/p\u003e\n\u003cp\u003eOccurrence records were obtained from the taxonomic bibliography of each species, EphemBrazil database (Salles et al 2023), and unpublished occurrence records of FCM. Records with taxonomical uncertainty (potential misidentification) were not used.\u003c/p\u003e\n\u003cp\u003eThe choice of the Atlantic Forest biome as an accessible (or calibration) area took into account the evolutionary history of the species. All are part of the biome, with a potential broad distribution in the pre-fragmentation past.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnvironmental Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll 19 bioclimatic variables from WorldClim v2.1 (https://www.worldclim.org/data/index.html) for current periods were selected (Fick \u0026amp; Hijmans, 2017). In addition to the climatic variables, five terrain variables were chosen: elevation, slope, flowacc (number of cells with small stream flow/capture), flow length (number of cells with upstream streams) (site: https://www.earthenv.org/streams), and land use (LI et al., 2017). All variables have a resolution at the equator of approximately 1 x 1 km. To avoid multicollinearity and reduce the number of variables, a Pearson Correlation was performed with a threshold of 0.7. The models were created using Annual temperature range (BIO5-BIO6), Mean temperature of the wettest quarter, Mean temperature of the driest quarter, Precipitation of the wettest quarter, Precipitation of the driest quarter, Precipitation of the warmest quarter, Precipitation of the coldest quarter, Slope, Land use.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModelling procedures and evaluation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePseudo-absences points were environmentally constrained based on the Bioclim model and within a 5 km buffer around\u0026nbsp;known geographical locations and based on the lowest suitable region predicted (Lobo et al. 2010). The number of pseudo-absences points used was equivalent to the number of presences. This decision to employ pseudo-absence plotting methods limited to specific environmental and geographic conditions has proven to be more effective compared to random allocation methods (Iturbide et al. 2015).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eModels were constructed using three algorithms, Bioclim (BIO - Presence) (HIJMANS et al., 2017), Domain (DOM - Presence) (HIJMANS et al., 2017), and Random Forest (RDF - Presence and Pseudo-absence) (LIAW; WIENER, 2002). The challenge of modeling rare, endemic, and restricted species is a well-known phenomenon (BREINER et al., 2015). This difficulty arises primarily from the low sample size and limited spatial replications when fitting climate data (BOTTS et al., 2013; BREINER et al., 2015; GALANTE et al., 2018). We use a random bootstrap partitioning, with 10 replicates with 70% of the data used to fit, method usually used to taxa with fewer than 10 occurrences (e.g. Cardoso et al 2023).\u003c/p\u003e\n\u003cp\u003eTo validate the performance of the models, the metrics Area Under the Curve (AUC), Jaccard, S\u0026oslash;rensen, and Fpb were used (ANDRADE et al., 2020) (see supplementary material). However, given the endemism and spatial restriction, which result in a small number of occurrences, the models were also validated by experts, who assessed whether the models made biological sense. The Jaccard metric was used to calculate threshold-dependent metrics. This metric is independent of correct absences (True Negative) and are less influenced by the extent of the accessible area and/or the pseudo-absence allocation method used (prevalence), making it a recommended choice (Leroy et al. 2018).\u003c/p\u003e\n\u003cp\u003eThe final models were generated using the ensemble method, mean the best-performing algorithms, using Jaccard. \u0026nbsp;This approach ensure the inclusion of high-quality predictions in the final model. The ensemble models were binarized using a threshold that maximized the Jaccard metric, resulting in optimal values of sensitivity (1.0) and specificity (1.0).\u003c/p\u003e\n\u003cp\u003eWe evaluated the model extrapolation using Mobility-Oriented Parity (MOP) analysis (OWENS et al., 2013). The ensemble models were limited by assuming a potential distribution only in cells up to 5% of extrapolation.\u003c/p\u003e\n\u003cp\u003eAll analyses were conducted using the ENMTML package (ANDRADE et al., 2020) in the R 4.1.2 environment. The open-source software QGIS version 3.16.2 was used to produce maps and to locate species occurrence records. The \u0026quot;QuickMapService\u0026quot; plugin, which provides a collection of satellite imagery for terrestrial visualization, was to select the watercourses with the best suitability, with projection EPSG 4326.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eEnvironmental Variable Importance\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the current condition, the three studied species exhibited distinct patterns of suitability and distribution. Overall, temperature-related variables showed the highest mean contribution across species, followed by precipitation metrics and slope, suggesting that thermal and hydrological regimes are key predictors of habitat suitability for these Ephemeroptera (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAdebrotus lugoi\u003c/em\u003e models were dominated by temperature-related variables, particularly Mean Temperature of Wettest Quarter (bio8: 24.7%) and Mean Temperature of Driest Quarter (bio9: 20.7%), suggesting strong dependence on thermal stability throughout the year. Land use (13.4%) also contributed significantly, indicating sensitivity to habitat degradation.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCamelobaetidius juparana\u003c/em\u003e showed the strongest association with topographic variables, with slope contributing 50.4% (bio 21) to model predictions, followed by precipitation variables (bio16: 12.8%). This pattern reflects the species\u0026apos; preference for steep, well-drained headwater streams with high oxygen levels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCamelobaetidius spinosus\u003c/em\u003e responded primarily to temperature seasonality (bio7: 20.7%) and thermal extremes (bio8: 22.5%), combined with precipitation patterns during dry periods (bio17, bio19: 18.3% each). These results suggest that, even under current conditions, these species already face significant limitations in terms of suitable habitat, which reinforces their vulnerability\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eAverage contribution (%) of environmental variables in ecological niche models for three Ephemeroptera species.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 285px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eA. lugoi\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC. juparana\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC. spinosus\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 285px;\"\u003e\n \u003cp\u003ebio7 (Temperature Annual Range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e5,10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5,10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e20,70%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 285px;\"\u003e\n \u003cp\u003ebio8 (Mean Temperature of Wettest Quarter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e24,70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e7,20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e22,50%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 285px;\"\u003e\n \u003cp\u003ebio9 (Mean Temperature of Driest Quarter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e20,70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6,80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3,00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 285px;\"\u003e\n \u003cp\u003ebio16 (Precipitation of Wettest Quarter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e1,10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e12,80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e6,40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 285px;\"\u003e\n \u003cp\u003ebio17 (Precipitation of Driest Quarter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e5,70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5,00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e18,30%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 285px;\"\u003e\n \u003cp\u003ebio18 (Precipitation of Warmest Quarter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e4,50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5,10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e4,10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 285px;\"\u003e\n \u003cp\u003ebio19 (Precipitation of Coldest Quarter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e10,80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e7,50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e18,30%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 285px;\"\u003e\n \u003cp\u003ebio21 (Slope)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e14,00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e50,40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e6,20%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 285px;\"\u003e\n \u003cp\u003ebio24 (Land cover)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e13,40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0,20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0,40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eCurrent Distribution Patterns\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eUnder current conditions, all three species exhibited highly restricted and fragmented potential distributions, concentrated in Atlantic Forest remnants of southeastern Brazil (Figure 1). Total suitable habitat area was limited for all species: \u003cem\u003eA. lugoi\u0026nbsp;\u003c/em\u003e(2,847 km\u0026sup2;), \u003cem\u003eC. juparana\u003c/em\u003e (4,163 km\u0026sup2;), and \u003cem\u003eC. spinosus\u003c/em\u003e (3,291 km\u0026sup2;). These areas represent less than 2% of the original Atlantic Forest extent in southeastern Brazil, highlighting the severe habitat restriction faced by these endemic species.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAdebrotus lugoi\u003c/em\u003e showed a fragmented distribution with suitable areas mainly in Esp\u0026iacute;rito Santo and scattered fragments in eastern Minas Gerais. The model indicated high suitability in specific regions of Esp\u0026iacute;rito Santo (\u0026gt; 0.80), were confined mainly to the Northern region of Esp\u0026iacute;rito Santo and nearby protected areas.\u003cem\u003e\u0026nbsp;Camelobaetidius juparana\u003c/em\u003e displayed broader, yet discontinuous suitability across Minas Gerais, Esp\u0026iacute;rito Santo, and Rio de Janeiro, following steep slopes and high-elevation areas in the Serra do Mar and Mantiqueira ranges. \u003cem\u003eCamelobaetidius spinosus\u003c/em\u003e, on the other hand, despite having medium suitability in several states (such as MG, SP, and RJ), but confirmed records only from Minas Gerais, it\u0026rsquo;s predicted distribution was concentrated in high-elevation zones of the Espinha\u0026ccedil;o and Mantiqueira ranges, with isolated patches in the Serra do Capara\u0026oacute;.\u003c/p\u003e\n\u003cp\u003eOur models highlighted priority sampling sites combining high suitability (\u0026gt;0.60) and proximity to known records. For \u003cem\u003eA. lugoi\u003c/em\u003e, Rio Cotax\u0026eacute; (-40.421655, -18.539256) and Rio Bananal (-40.295608, -19.254604) in Esp\u0026iacute;rito Santo showed top suitability, consistent with its preference for stable thermal regimes (bio8: 24.7%) and intact riparian forests (Souza et al., 2024). For \u003cem\u003eC. juparana\u003c/em\u003e, Cachoeira da Fuma\u0026ccedil;a (-41.719706, -21.023790) and Rio Muria\u0026eacute; (-41.751730, -21.303870) reached optimal suitability (\u0026gt;0.80), driven by steep slopes (bio21: 50.4%) that sustain oxygen-rich habitats (Salles, 2006). For \u003cem\u003eC. spinosus\u003c/em\u003e, despite post-Mariana habitat degradation (Brasil/IBAMA, 2015), Cachoeira Santana (-42.491744, -19.616520) remains notable for its marginal suitability (0.40) and relative isolation from impacted areas..\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe restricted and fragmented distributions of \u003cem\u003eAdebrotus lugoi\u003c/em\u003e, \u003cem\u003eCamelobaetidius juparana\u003c/em\u003e, and \u003cem\u003eCamelobaetidius spinosus\u003c/em\u003e revealed by our models align with broader patterns of habitat loss in the Atlantic Forest, where only 28% of original vegetation remains (Rezende et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This biome\u0026rsquo;s degradation has disproportionately impacted aquatic insects, as highlighted by Souza et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), who projected severe habitat suitability declines for Ephemeroptera under climate change. Our results extend their work by pinpointing potential microrefugia for three overlooked species, emphasizing the role of temperature stability (e.g., \u003cem\u003eA. lugoi\u003c/em\u003e\u0026rsquo;s dependence on bio8, Mean Temperature of Wettest Quarter) and hydrological regimes (e.g., \u003cem\u003eC. juparana\u003c/em\u003e\u0026rsquo;s association with slope and precipitation seasonality).\u003c/p\u003e \u003cp\u003eThe distinct environmental drivers identified for each species reflect fine-scale niche differentiation within the Baetidae family (Taylor et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), supporting the hypothesis that specialized habitat requirements contribute to their rarity and endemism. \u003cem\u003eA. lugoi\u003c/em\u003e\u0026rsquo;s dependence on thermal stability (high contribution of bio8 and bio9) suggests adaptation to spring-fed or groundwater-influenced streams that buffer temperature fluctuations\u0026mdash;a habitat increasingly rare in the fragmented Atlantic Forest landscape (Safar et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This thermal specialization may explain the species\u0026rsquo; restriction to high-elevation sites, where groundwater discharge is more common and forest cover provides additional thermal buffering (de Andrade et al., 2024)]\u003c/p\u003e \u003cp\u003eThe overwhelming importance of slope for \u003cem\u003eC. juparana\u003c/em\u003e (50.4% contribution) indicates strong selection for high-gradient streams that maintain elevated dissolved oxygen and stable substrates required for larval development. This aligns with broader Baetidae ecology, where rheophilic species show narrow tolerance ranges for flow velocity and substrate stability (Brittain, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1982\u003c/span\u003e: Kubendran et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The association with precipitation seasonality (bio16, bio19) further suggests sensitivity to hydrological regime alterations, making the species particularly vulnerable to projected precipitation shifts in the Atlantic Forest (Vale et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. spinosus\u003c/em\u003e showed the strongest response to temperature seasonality (bio7), indicating adaptation to environments with pronounced thermal variation\u0026mdash;a trait characteristic of high-elevation Atlantic Forest sites where diurnal and seasonal temperature ranges are amplified by altitude and reduced canopy cover (Safar et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Its dependence on precipitation during cold periods (bio19) may reflect breeding synchronized with winter dry seasons, when reduced flows expose suitable oviposition sites. This temporal specialization could explain its rarity and restricted distribution, as disruption of seasonal rainfall directly affects reproductive success.\u003c/p\u003e \u003cp\u003eThe Atlantic Forest\u0026rsquo;s vulnerability to climate shifts (Scarano \u0026amp; Ceotto, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) exacerbates threats to these Baetidae. \u003cem\u003eC. spinosus\u003c/em\u003e, for instance, showed dependence on annual temperature range (bio7, 20.7%), a variable expected to intensify under global warming (Vale et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Such niche specificity, combined with limited dispersal, may explain why the species persists only in Minas Gerais despite moderate suitability in neighboring states\u0026mdash;a pattern echoing Ferreira et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and recent findings linking stream fragmentation to reduced aquatic insect gene flow (Castillo-P\u0026eacute;rez et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile land use (bio24) significantly influenced \u003cem\u003eA. lugoi\u003c/em\u003e (13.4% contribution), its minimal effects on \u003cem\u003eCamelobaetidius\u003c/em\u003e spp. suggests that these species face greater risk from climate-related factors than direct habitat alteration. This contrasts with Safar et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), who emphasized forest resilience, but supports their argument that microhabitat-scale restauration is critical for conservation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides the first comprehensive assessment of potential habitat distributions of three endangered Baetidae species (\u003cem\u003eAdebrotus lugoi\u003c/em\u003e, \u003cem\u003eCamelobaetidius juparana\u003c/em\u003e, and \u003cem\u003eCamelobaetidius spinosus\u003c/em\u003e) endemic to Atlantic Forest streams. Our distribution models identified distinct range patterns for each species, with high-suitability areas concentrated in remnant fragments of the Atlantic Forest\u0026mdash;a biome that has lost over 70% of its original cover. These findings underscore the vulnerability of these organisms, whose survival critically depends on conserving aquatic habitats amid escalating climate change and anthropogenic pressures. The proposal of precise locations for the search for new populations, allowing the empirical validation of the models, greater clarity is expected regarding the vulnerability of these species.\u003c/p\u003e \u003cp\u003eThe methodological approach, combining ecological niche modeling with a precise indication of locations to be sampled, proved essential for addressing uncertainties inherent in studying rare species. The scarcity of historical records and the complexity of these insects' microhabitat requirements highlight the need for further research to refine model accuracy.\u003c/p\u003e \u003cp\u003eFrom a conservation perspective, our results carry immediate implications. Protecting forest remnants in Esp\u0026iacute;rito Santo, Minas Gerais, and Rio de Janeiro\u0026mdash;particularly in priority areas identified by the models\u0026mdash;is urgent to prevent the extinction of these species. Integrating these findings into public policies for ecological restoration and biodiversity monitoring could represent a significant leap forward in safeguarding Neotropical aquatic insects, which remain overlooked in national action plans. While science plays a pivotal role, effective conservation will require coordinated efforts among researchers, environmental managers, and local communities.\u003c/p\u003e \u003cp\u003eUltimately, this study not only maps critical habitats for endangered mayflies but also exposes the delicate balance between aquatic insects and their rapidly changing environments. The Atlantic Forest's plight mirrors global biodiversity crises, making these species both indicators and victims of ecosystem degradation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eWe would like to thank the Rond\u0026ocirc;nia Foundation for Supporting the Development of Scientific and Technological Actions and Research in the State of Rond\u0026ocirc;nia (FAPERO) for funding the projects \u0026ldquo;Resistance and resilience of aquatic organisms in streams threatened by anthropogenic activities in the Amazon\u0026rdquo; (0012.067617/2022-90 / grant n\u0026deg;199/2022)\u0026rdquo; and \u0026ldquo;0012.068211/2022-24 - Ecology and Conservation of Ephemeroptera (Insecta): an approach from Brazil and the state of Rond\u0026ocirc;nia.\u0026rdquo;; National Council for Scientific and Technological Development (CNPq) for funding the project \u0026ldquo;Diversity of Ephemeroptera (Insecta) in Brazil: expanding the frontiers of knowledge generation and dissemination\u0026rdquo; (process: 408346/2023-0, Call CNPq/MCTI/N\u0026ordm;10/2023); and PPBio Amaz\u0026ocirc;nia Ocidental (CNPq, processos 441260/2023-3 e 441228/2023-2).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eGFM, ALA, FCM and PVC contributed to the study conception and design; data acquisition and analysis; to the writing and correction of the text. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eTo UNIR (Federal University of Rond\u0026ocirc;nia) for providing the computers in the Multi-User Space, which proved essential for the analyses conducted in this study. We would like to thank the Rond\u0026ocirc;nia Foundation for Supporting the Development of Scientific and Technological Actions and Research in the State of Rond\u0026ocirc;nia (FAPERO) for funding the projects \u0026ldquo;Resistance and resilience of aquatic organisms in streams threatened by anthropogenic activities in the Amazon\u0026rdquo; (0012.067617/2022-90 / grant n\u0026deg;199/2022)\u0026rdquo; and \u0026ldquo;0012.068211/2022-24 - Ecology and Conservation of Ephemeroptera (Insecta): an approach from Brazil and the state of Rond\u0026ocirc;nia.\u0026rdquo; We also acknowledge the Public Call MCTI/FINEP/FNDCT Infrastructure for the Legal Amazon 2024 - Pr\u0026oacute;-Amaz\u0026ocirc;nia, reference 2359/24 - Strengthening Research Infrastructure in Rond\u0026ocirc;nia as a strategy to reduce asymmetries and expand research in the Amazon: Subproject: Consolidating Biological Collections in Rond\u0026ocirc;nia to expand the study of Amazonian Biodiversity; Centro Avan\u0026ccedil;ado de Pesquisa-A\u0026ccedil;\u0026atilde;o da Conserva\u0026ccedil;\u0026atilde;o e Recupera\u0026ccedil;\u0026atilde;o Ecossist\u0026ecirc;mica da Amaz\u0026ocirc;nia - CAPACREAM (CNPq Proc. 444350/2024-1); National Council for Scientific and Technological Development (CNPq) for funding the project \u0026ldquo;Diversity of Ephemeroptera (Insecta) in Brazil: expanding the frontiers of knowledge generation and dissemination\u0026rdquo; (process: 408346/2023-0, Call CNPq/MCTI/N\u0026ordm;10/2023); and PPBio Amaz\u0026ocirc;nia Ocidental (CNPq, processos 441260/2023-3 e 441228/2023-2).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBrazil, MMA. (2022). \u003cem\u003eOrdinance MMA No. 148 of June 7, 2022. Amends Annexes to Ordinance MMA No. 443 of December 17, 2014, updating the National List of Endangered Species\u003c/em\u003e. www.gov.br/icmbio/pt-br/assuntos/centros-de-pesquisa/aves-silvestres/arquivos/portaria-148-2022.pdf \u003c/li\u003e\n\u003cli\u003eBrittain, J. E. (1982). Biology of mayflies. \u003cem\u003eAnnual Review of Entomology, 27\u003c/em\u003e, 119-147. https://doi.org/10.1146/annurev.en.27.010182.001003\u003c/li\u003e\n\u003cli\u003eCastillo‐P\u0026eacute;rez, E. U., Rivera‐Duarte, J. D., Abell\u0026aacute;n, P., del‐Val, E., Gonz\u0026aacute;lez‐Tokman, D., \u0026amp; C\u0026oacute;rdoba‐Aguilar, A. (2025). Thriving in the heat: How high temperatures and habitat disturbance shape odonate taxonomic and functional diversity in the tropics. Insect Conservation and Diversity, 18(3), 343-356.\u003c/li\u003e\n\u003cli\u003eChowdhury, S., et al. (2021). 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Insect responses to global change offer signposts for biodiversity and conservation. \u003cem\u003eEcological Entomology, 46\u003c/em\u003e(4), 699-717. https://doi.org/10.1111/een.12970\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"impacts, habitat loss, mayflies, endangered, validation","lastPublishedDoi":"10.21203/rs.3.rs-8673498/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8673498/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Atlantic Forest ranks among the most endangered tropical forests worldwide, only 28% of the original vegetation cover remains. Recent modeling studies indicate a drastic reduction in suitable habitat for all Ephemeroptera across the Atlantic Forest biome in the near future. Preliminary analyses of extinction risk in the Brazil considered four species of Baetidae (Ephemeroptera) as facing a significant risk of extinction, three of them endemic, with restricted distribution, and from the Atlantic Forest biome. Given the ecological importance and the limited distributional knowledge of these taxa, this study aims to apply current environmental modelling approaches to identify potential occurrence sites for three species (\u003cem\u003eAdebrotus lugoi, Camelobaetidius juparana\u003c/em\u003e, and \u003cem\u003eCamelobaetidius spinosus\u003c/em\u003e) that are at risk of extinction, thereby guiding field search for new populations. The models indicated restricted and fragmented distributions for \u003cem\u003eAdebrotus lugoi, Camelobaetidius juparana\u003c/em\u003e, and \u003cem\u003eC. spinosus\u003c/em\u003e, consistent with the habitat loss in the Atlantic Forest. \u003cem\u003eAdebrotus lugoi\u003c/em\u003e showed a strong dependence on thermal stability variables (bio8, bio9), typical of groundwater-influenced streams, which contributes to its restriction to high-elevation areas. \u003cem\u003eCamelobaetidius juparana\u003c/em\u003e was primarily influenced by slope (50.4%), being associated with steep, oxygen-rich streams characterized by stable substrates; it also exhibited sensitivity to precipitation seasonality (bio16, bio19). \u003cem\u003eCamelobaetidius spinosus\u003c/em\u003e responded mainly to temperature seasonality (bio7) and precipitation during cold periods (bio19), indicating adaptation to high-elevation environments with pronounced thermal variation and reproduction synchronized with the dry winter season. These results highlight fine-scale niche differentiation among the species, with high thermal and hydrological specialization. The strong dependence on climatic variables\u0026mdash;rather than on land use (13.4% contribution for \u003cem\u003eA. lugoi\u003c/em\u003e)\u0026mdash;suggests that climate change represents the main threat to their persistence. Conservation strategies should prioritize the identification and protection of thermal and hydrological microrefugia, as well as microhabitat-scale restoration. In this perspective, based on models were proposed priority sampling sites for each species.\u003c/p\u003e","manuscriptTitle":"Guiding Field Surveys of Brazilian Vulnerable Baetidae (Ephemeroptera) through Species Distribution Modeling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 10:58:54","doi":"10.21203/rs.3.rs-8673498/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ad8f42dd-7821-41db-92aa-798b6b96860e","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Withdrawn","date":"2026-05-14T07:05:39+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T07:11:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 10:58:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8673498","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8673498","identity":"rs-8673498","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}