Hotspots in Transition: Mediterranean Amphibian Diversity Under Different Climate Scenarios

Hotspots in Transition: Mediterranean Amphibian Diversity Under Different Climate Scenarios | 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 Hotspots in Transition: Mediterranean Amphibian Diversity Under Different Climate Scenarios Can Elverici, Andrew Townsend Peterson, Utku Perktaş This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4361804/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Dec, 2024 Read the published version in Biodiversity and Conservation → Version 1 posted 3 You are reading this latest preprint version Abstract The Mediterranean Basin, a region renowned for its biodiversity, is experiencing unprecedented ecological changes owing to shifting climate patterns. This study employs ecological niche modeling to assess impacts of historical, current, and future climate scenarios on climatic suitability patterns for 36 endemic amphibian species. The study incorporates a diverse set of environmental variables to project species’ potential geographic distributions across significant climatic events, including the Last Interglacial, Last Glacial Maximum, and Mid-Holocene, as well as future projections for 2050 and 2070 under various Representative Concentration Pathways (RCPs). The resulting models underscore the congruence of predicted species-rich areas with established biodiversity hotspots, and highlight the influence of precipitation on amphibian distribution. Notably, the study reveals potential shifts in biodiversity importance of different areas across the Mediterranean landscape, with certain regions projected to transition from hotspots to coldspots and vice versa , in response to future climatic changes. These insights contribute to a broader discourse on conservation priorities, emphasizing the need for adaptive strategies that can accommodate the dynamic nature of biodiversity in response to climate change. The findings of this study serve as a call to action for preserving Mediterranean biodiversity, providing a data-driven foundation for informed conservation planning in this critical hotspot. Mediterranean Basin biodiversity hotspots amphibians ecological niche modeling climate change Figures Figure 1 Figure 2 Figure 3 INTRODUCTION The Mediterranean Basin, extending from Portugal to Jordan and Italy to Morocco, is a biodiversity hotspot renowned for its remarkable geographic diversity and distinctive climatic conditions (Maiorano et al., 2013). Defined by its position along the western edge of the Alpine-Himalayan mountain belt (Mather, 2009), this region is characterized not just by complex topography but also by the diversity of habitats that support a wide array of species, particularly amphibians (Akın et al., 2010; Bonardi et al., 2022; Canestrelli et al., 2007; Console et al., 2020; Costa et al., 2021; Dufresnes et al., 2022; Erotokritou et al., 2024; Jablonski et al., 2021; Maiorano et al., 2011; Stümpel et al., 2016). The area's unique environmental settings arise from a combination of steep mountains, deep valleys, and numerous islands, creating a mosaic of biodiversity-rich ecosystems (Blondel, 2010; Mather, 2009; Nicolaci et al., 2014). The Mediterranean climate, with its hot, dry summers and mild, wet winters, has played a pivotal role in shaping the distribution and life cycles of numerous species in the region (Lionello et al., 2006). This climatic variability, largely influenced by the Mediterranean Sea acting as a thermal reservoir, has contributed significantly to the region’s status as a biodiversity hotspot, fostering high levels of endemism and species richness (Valente and Vargas, 2013). The diverse climatic zones, spanning from continental interiors to moist mountainous terrains, have further contributed to the unique ecological dynamics of the Mediterranean Basin, underscoring the importance of comprehending the intricate interactions between climate and biodiversity in this region (Nicolaci et al., 2014). The Mediterranean Basin has experienced dramatic climatic shifts, profoundly influencing its biodiversity and ecological dynamics. Pivotal periods such as the Last Interglacial, the Last Glacial Maximum, and the Mid-Holocene have shaped the evolutionary history of the region’s flora and fauna. For instance, during the Last Glacial Maximum, the Mediterranean served as a crucial refuge for many species, offering stable environments amidst broader climatic extremes (Brito, 2005; Hewitt, 2004). This historical legacy continues to influence current biodiversity patterns and is crucial for comprehending species' adaptations and vulnerabilities. Médail and Diadema (2009) highlighted the importance of identifying and conserving refugia where biodiversity has thrived historically and can persist despite environmental pressures. The Mediterranean Basin's rich tapestry of habitats, driven by its climatic history and geographic features, supports a diverse range of species, making it a critical area for biodiversity conservation. Understanding the complex interplay between environmental conditions and biological diversity is essential for developing effective conservation measures that can safeguard the natural heritage of this region for future generations. In this study, we employed ecological niche modeling (ENM) to explore how amphibian populations in the Mediterranean Basin might respond to past and future climatic changes. We aim to pinpoint potential conservation areas that will be crucial for maintaining amphibian biodiversity in the face of increasing climatic instability, employing ENM within this biogeographic framework and investigating how amphibian distributions likely respond to current and future climate changes. The findings are intended to inform conservation strategies and safeguard the future of these ecosystems by providing fundamental insights on the climate component of the factors impacting biodiversity in this biodiversity hotspot. MATERIALS AND METHODS Occurrence Records We identified 36 amphibian species restricted to the Mediterranean Basin through an extensive review of scholarly articles. Occurrence data from 1980 through 2022 were primarily sourced from the Global Biodiversity Information Facility (GBIF), with additional data integrated from various literature sources to ensure a reasonably comprehensive dataset (GBIF.org, 2023). Selected occurrence records were verified by comparing distribution data from published literature and the IUCN Red List of Species. Duplicates and erroneous records were detected and removed from the dataset via intensive visual inspection. To minimize effects of spatial autocorrelation on models focused on these endemic species, a spatial thinning distance of either 5 km or 2 km was applied using thin_data function in ellipsenm package (version 0.3.4) in R (version 4.2.3) (Cobos et al., 2020 ). The 2 km distance was used when the number of occurrences was < 15; otherwise, a 5 km distance was implemented. Environmental Data Layers Nineteen variables of bioclimatic data for different historical and forecasted periods were sourced from WorldClim version 1.4, providing data at a 2.5’ spatial resolution. These datasets included scenarios for the current period, mid-Holocene (~ 6 kybp), Last Glacial Maximum (LGM; ~22 kybp), and Last Interglacial (LIG; ~120–140 kybp), as well as future projections for 2050 and 2070 (Hijmans et al., 2005 ). For reconstructing past climates for LGM and mid-Holocene, simulations from three general circulation models (GCMs) were employed: CCSM4, MIROC-ESM, and MPI-ESM-P; only one was available for LIG (Otto-Bliesner et al., 2006 ). Future climatic conditions were explored using the same models but using MPI-ESM-LR instead of MPI-ESM-P, each for representative concentration pathways (RCPs) 2.6, 4.5, and 8.5. To enhance the data's applicability, climatic heterogeneity for annual mean temperature (bio1) and annual precipitation (bio12) were created using the focal function with a 3x3 moving window in the terra package (version 1.7–74) in R (version 4.2.3) (Hijmans et al., 2022 ). We excluded certain variables (bio8, bio9, bio18, and bio19) because they include spatial inconsistencies among adjacent pixels (Escobar et al., 2014 ). Three additional sets of bioclimatic layers were created for analysis by reducing inclusion of climatic dimensions under pairwise, layer-to-layer correlation thresholds of 0.9, 0.8, and 0.6, using the vifcor function in the usdm package (version 2.1-7) in R (version 4.2.3) (Naimi et al., 2014 ). In the 0.6 threshold dataset, heterogeneity layers were retained. These datasets included 13, 10, 7, and 7 variables respectively, allowing for varied degrees of data complexity and specificity in ENM. M Simulations Simulating biologically realistic accessible areas for use as calibration areas in ENM enhances model performance through a biologically informed approach has recently become feasible (Barve et al. 2011 , Machado-Stredel et al. 2021 ). This methodology not only shapes the interpretation and outcomes of models (Barve et al. 2011 ), but also ensures that modeled niche dimensions and model transfers across different environmental contexts are more appropriate biologically. By incorporating key biological dynamics such as dispersal, colonization, and extinction, these simulations approximate the accessible areas for species (Soberón and Peterson 2005 ). This process allows for the establishment of biologically relevant contrasts in model calibration, thereby minimizing extrapolation errors. Adoption of a simulation-based methodology enables quantitative estimates of a species’ accessible area while accommodating its dispersal capabilities and environmental adaptability. We used the "grinnell" package (version 0.0.21) in R (version 4.2.3) to develop these simulations using default settings except for setting kernel density to 0.5, and dispersal events to 20 (Machado-Stredel et al., 2021 ). Results of simulations were used as calibration areas in ENM and later to remove areas of overprediction. Ecological Niche Modeling ENM was performed using the Maxent software and the kuenm package in R, which are established tools for such modeling (Cobos et al., 2019 ; Phillips and Dudík, 2008 ). Occurrence data were partitioned into training (75%) and testing (25%) datasets to facilitate development and evaluation of models. A comprehensive, multi-criterion approach was employed to select the most robust models, prioritizing those that were (1) predicting independent data subsets with statistical significance (partial ROC test), (2) predicting independent data subsets with < 5% omission at a 10% training presence omission threshold, and (3) relatively simple according to the corrected Akaike information criterion (AICc) (Hurvich and Tsai, 1989 ; Peterson et al., 2011 , 2008 ). This selection process was applied across a broad array of 900 candidate models generated by using 4 environmental data sets x 15 regularization multiplier values (ranging from 0.1 to 10), and 15 combinations feature classes (including linear, quadratic, product, and hinge features). Models with the lowest AICc scores were selected, indicating they provide the most concise representation of the influence of sets of bioclimatic variables on species’ distributions (Gür et al., 2018 ). Instead of relying on a single model, the median of suitable areas from the best-performing models (i.e., all models within 2 AICc units of the minimum among significant, low-omission candidate models) was used to derive final predictions, enhancing the robustness of the results. This method employed 10 replicates and specified no model extrapolation (Owens et al., 2013 ), ensuring the reliability of the findings. For model transfers to historical and projected future climate scenarios, these median-based predictions were rendered onto each temporal scenario and transformed into binary maps (suitable/unsuitable) employing a 10% training presence logistic threshold. The use of binary outputs in ecological niche modeling serves to delineate suitable areas clearly for the species under study. This approach sets clear ecological thresholds that are aligned with conservation-focused research objectives, facilitating straightforward interpretation and aiding in precise identification of areas suitable for potential conservation measures (Escobar et al., 2018 ). For all 36 amphibian species studied, binary maps were compiled for the Last Interglacial, Last Glacial Maximum, Mid-Holocene periods, the present, and future scenarios under RCPs 2.6, 4.5, and 8.5 for 2050 and 2070. RESULTS Following removal of erroneous data, remaining records were reduced to minimize sampling bias. Counts of records before and after this reduction process are detailed in Supplementary Tables S75. These curated records were subsequently used in ENM. Accessible areas delineated for each amphibian species, derived from binarized results of the ecological niche models, are illustrated in the supplementary figures. Environmental variables incorporated into the models varied by set, reflecting specific bioclimatic conditions and spatial heterogeneities considered critical for each scenario (see Supplementary table S76) From among the 900 candidate models for each species, best-performing models were selected based on their ecological validity and statistical robustness; a detailed summary of their statistics and the percent contribution of each variable presented in Supplementary Tables S1-S74. Model predictive ability assessed using the AUC metric for all species can also be seen in Supplementary Tables S1-S74. While contributions of individual variables varied among models, common trends took the form of the significant influence of bio12 (annual precipitation), bio15 (precipitation seasonality), and the spatial heterogeneity of bio12. These findings underscore the dependency of amphibian distributions on water availability, reflecting their ecological preferences and susceptibilities. Overlay of ENM results for the 36 amphibian species identified species-rich areas corresponding to current Mediterranean biodiversity hotspots (Fig. 1 ). For the Last Interglacial (LIG) (Fig. 2a), models suggest a considerable westward-shifted distribution for amphibians, particularly in Portugal and France. Last Glacial Maximum (LGM) model outputs (Fig. 2b) match well with the expansion-contraction model expectations. Suitability in the Mid-Holocene period for the 36 amphibian species (Fig. 2c) exhibited a distribution highly similar to present-day conditions. In terms of future potential distributions (2050 and 2070), model transfers indicated significant shifts in concentrations of suitable areas for amphibians in the Mediterranean Basin (Fig. 3 ). DISCUSSION This study combines ENMs for various amphibian species in the Mediterranean with a broader examination of the region's biodiversity to project and explore amphibian diversity patterns under past, present, and future climate scenarios. The Mediterranean Basin, widely recognized as a biodiversity hotspot, plays a critical role in harboring endemic and threatened species across various taxa (Maiorano et al., 2013 ; Numa et al., 2020 ). ENM, a method considered highly useful for interpreting species' ecological and historical biogeography (Perktaş et al., 2015a ), was chosen for its potential to deliver meaningful, geographically explicit conservation outcomes for this region, which is under significant threat from climate change and human activities. The Mediterranean Basin’s status as a global biodiversity focus is further emphasized by its qualification as one of the original 36 Global Biodiversity Hotspots, a distinction it earns by hosting > 1500 endemic species vascular plants and experiencing > 30% loss of its original natural vegetation (Myers et al., 2000 ; Hrdina and Romportl, 2017 ). This study focuses on endemic amphibian species, the significant number of which underscores the critical nature of the region in terms of its unique and threatened biodiversity. The geographic distributions of species in the Mediterranean have been influenced by alternating glacial and interglacial periods, as evidenced by historical climate dynamics. The expansion-contraction model, especially relevant during colder periods, is supported by the findings from Hewitt ( 2004 ) and Schmitt ( 2007 ). This model suggests species sought refuge in southern, warmer climates during glaciations (Stojak and Jędrzejewska, 2022 ). Analyses across various taxa, including mammals, plants, and invertebrates, underline the genetic impacts of these climatic shifts on historical biogeography (Gür, 2013 ; Taberlet et al., 1998 ). Notably, the LIG models show a westward distribution shift in amphibians, specifically in Portugal and France, attributed to regional climatic stability (Rioual et al., 2001 ), which is congruent with individual species' suitabilities across various taxa (Perktaş et al., 2017 ; Ülker et al., 2018 ). These patterns confirm the relevance of historical climate refugia suggested by Médail and Diadema ( 2009 ), although our LGM outputs suggest a slight misalignment, they still match current species suitability. The similarity of Mid-Holocene distributions to contemporary conditions reflects the findings by Badis et al. ( 2024 ), Wu et al. ( 2021 ), and Segatto et al. ( 2017 ), highlighting the ongoing influence of historical climates on present biodiversity patterns and emphasizing the need for targeted conservation strategies. Biodiversity hotspots have been instrumental in informing global conservation priorities, and have been used to focus conservation actions on particular regions with exceptional concentrations of endemic species undergoing significant habitat loss (Myers et al. 2000 ). As a contrasting concept, biodiversity coldspots are limited-diversity regions often explained by harsh ecological conditions (Schröter et al., 2017 ). Biodiversity hotspots have received significant attention and conservation efforts, yet coldspots remain relatively overlooked and poorly understood (Procheş, 2022 ), even though the scarce biodiversity in coldspots can be sensitive to environmental changes and human activities (Liu et al., 2023 ). These two concepts are relevant, given that current suitable areas may transition between the two states over time (REF), as has also been illustrated in this study. For example, the southern part of the Iberian Peninsula and central Anatolia appear to lose their significance, whereas northern Europe and Caucasia will have increasing significance under future climate scenarios. In the Mediterranean Basin, invasive species such as the African clawed frog ( Xenopus laevis ) and various invasive crayfish species (e.g., Procambarus clarkii and Pacifastacus leniusculus ) pose significant ecological threats. These invaders are particularly problematic because of their adaptability to Mediterranean climates and their aggressive competition with native amphibians for critical resources and habitats (Lillo et al., 2010; Mota-Ferreira & Beja, 2020 ). The presence of invasive species has been linked to reductions in the reproductive success of native species, fundamentally altering ecological interactions, and potentially leading to local extinctions even without direct habitat destruction (Clavero et al., 2010 ). Shifting distributions of species, driven by present climate change processes, is emerging as a threat to biodiversity, especially for amphibians in the Mediterranean. Moreover, the phenomenon of introgression through hybridization can present a further challenge to conserving genetic diversity in the region. Introgressive hybridization, particularly observed between native European tree frogs ( Hyla arborea ) and introduced species like H. intermedia , can significantly diminish the viability and fertility of hybrid individuals, potentially reducing the overall fitness of local amphibian populations (Dufresnes et al., 2015 ). Such genetic intermixing may lead to homogenization and eventual replacement of native gene pools, further complicating conservation efforts and threatening the unique biodiversity of the Mediterranean Basin (Dufresnes et al., 2015 ). As illustrated by Médail and Diadema ( 2009 ), the Mediterranean biodiversity hotspot is home to 52 putative or possible refugia based on studies of plant distributions. Our ENM-based analyses align these refugia with the current distributions of amphibians. Notably, influences of climate change suggest significant temporal transitions for these refugial areas, with several changing from hotspots to coldspots for our target species. These transitions are expected to affect climatic suitability of these areas by the 2050 and 2070 time horizons. Implications of different RCP scenarios are profound, with the best-case scenario RCP 2.6 showing less-dramatic shifts compared to the worst-case scenario RCP 8.5. This result indicates that some conservation priorities may need to shift towards areas that are currently regarded as coldspots, which have not traditionally been considered as areas of conservation focus (Cox and Underwood, 2011 ). For instance, whereas the Iberian Peninsula and Central Anatolia are projected to lose significant diversity, regions in central and western France are expected to gain diversity, suggesting a need to reevaluate conservation priorities and resource allocation in these emerging priority areas, especially considering the high human population density. In line with other studies, our findings confirm that the Mediterranean Basin is exceedingly vulnerable to climate change, which poses significant risks to biodiversity conservation (Almeida et al., 2022 ; Benítez-Benítez et al., 2022 ; Guiot and Cramer, 2016 ). A notable limitation of this study lies in its focus solely on climatic variables to explore distributional shifts of amphibians in the Mediterranean Basin. While this approach is critical for understanding the impacts of climate change, it inherently overlooks other significant ecological factors that can also profoundly influence amphibian populations (Costa et al., 2021 ; Dvorsky et al., 2022 ; Youngquist and Boone, 2021 ). Non-climatic threats such as vegetation distributions, habitat destruction, urbanization, pollution, and introduction of invasive species, are also at least potentially important in shaping present and future distributions of these species but are not directly accounted for in our models (Harper et al., 2008 ; Underwood et al., 2009 ; Veron et al., 2016 ). In this sense, this study should be interpreted as exploring climate-based potential geographic distributions of species. Emerging threats from diseases such as chytridiomycosis, caused by Batrachochytrium dendrobatidis , and other coinfections further exemplify the challenges that need to be integrated into full conservation planning applications of such studies (Pereira et al., 2013 ; Wuerthner et al., 2017 ). Such pathogenic factors are known to cause rapid declines in amphibian populations and could drastically alter the landscape of biodiversity in the Mediterranean, independent of or in conjunction with climate change. This study also not incorporate effects of multiple stressors beyond climatic factors, such as interactions between disease pathogens and environmental contaminants. For instance, effects of trematode infections are exacerbated by pesticide exposure, highlighting the complex interplay between biotic and abiotic factors which can influence amphibian health and survival (Kiesecker, 2002 ). These factors could significantly alter the outcomes of climate change impact predictions by either mitigating or intensifying the effects perceived solely through the lens of climatic variables. CONCLUSIONS This study leverages the potential of ENM, evaluating effects of past and future climate variation to illuminate how climate change might reshape distributions of amphibian species across the Mediterranean Basin, a key biodiversity hotspot. Our findings indicate significant shifts in climatic suitability under various climate scenarios from the past to the future, predicting a transformation in regional biodiversity significance from current hotspots to potential new conservation areas. These changes are particularly manifested in regions such as central and western France, which could become crucial future refugia for amphibian species. These insights are crucial for guiding future conservation efforts, ensuring that strategies are dynamically aligned with projected changes in habitat conditions. Although the analysis focused primarily on climate change, the implications of our findings necessitate further and future consideration of human impacts, such as urbanization and habitat alteration, particularly in densely populated Mediterranean areas. Acknowledging limitations of a study such as this one is essential for refining future research approaches. It emphasizes the need for integrated models that not only consider a broader range of environmental variables but also incorporate dynamic interactions between multiple stressors. This holistic view is crucial for developing more robust and effective conservation strategies that can address the multifaceted challenges facing amphibian populations in the Mediterranean Basin. By providing a predictive framework, this research supports proactive conservation planning, helping to safeguard Mediterranean amphibian biodiversity against the impending challenges of climate change. Declarations FUNDING CE received support from the Scientific and Technological Research Council of Turkey through the 2214-A International Research Fellowship Programme for PhD Students, under project number 1059B142200286. Author Contribution All authors contributed to the study conception and design. C.E. acquired the data and created visuals. C.E. contributed in the analysis. C.E. created the original manuscript. A.T.P. thoroughly reviewed and edited the manuscript. U.P. contributed as Supervisor. All authors reviewed the manuscript. Acknowledgement Special thanks are extended to Dr. Utku Perktaş for his guidance and insights throughout the development of this project. His expertise and feedback were invaluable in shaping the research. 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Frontiers in Zoology 4, 11. https://doi.org/10.1186/1742-9994-4-11 Schröter M, Kraemer R, Ceauşu S, Rusch GM (2017) Incorporating threat in hotspots and coldspots of biodiversity and ecosystem services. Ambio 46, 756–768. https://doi.org/10.1007/s13280-017-0922-x Segatto ALA, Reck-Kortmann M, Turchetto C., Freitas L.B (2017). Multiple markers, niche modelling, and bioregions analyses to evaluate the genetic diversity of a plant species complex. BMC Evolutionary Biology 17, 234. https://doi.org/10.1186/s12862-017-1084-y Soberón J, Peterson A.T. (2005) Interpretation of Models of Fundamental Ecological Niches and Species’ Distributional Areas. Biodiversity Informatics 2.0 https://doi.org/10.17161/bi.v2i0.4 Stojak J, Jędrzejewska B (2022) Extinction and replacement events shaped the historical biogeography of Arctic mammals in Europe: new models of species response. Mammal Review 52, 507–518. https://doi.org/10.1111/mam.12298 Stümpel N, Rajabizadeh M, Avcı A, Wüster W Joger, (2016) Phylogeny and diversification of mountain vipers ( Montivipera , Nilson et al., 2001) triggered by multiple Plio–Pleistocene refugia and high-mountain topography in the Near and Middle East. Molecular Phylogenetics and Evolution 101, 336–351. https://doi.org/10.1016/j.ympev.2016.04.025 Taberlet P, Fumagalli L, Wust‐Saucy A, Cosson, J (1998) Comparative phylogeography and postglacial colonization routes in Europe. Molecular Ecology 7, 453–464. https://doi.org/10.1046/j.1365-294x.1998.00289.x Ülker, E.D., Tavşanoğlu, Ç., Perktaş, U (2018). Ecological niche modelling of pedunculate oak ( Quercus robur ) supports the ‘expansion–contraction’model of Pleistocene biogeography. Biological Journal of the Linnean Society 123, 338–347. Underwood EC, Viers JH, Klausmeyer KR, Cox R.L. and Shaw, M.R (2009) Threats and biodiversity in the mediterranean biome. Diversity and Distributions 15, 188–197. https://doi.org/10.1111/j.1472-4642.2008.00518.x Valente LM & Vargas P (2013) Contrasting evolutionary hypotheses between two mediterranean-climate floristic hotspots: the Cape of southern Africa and the Mediterranean Basin. Journal of Biogeography 40, 2032–2046. https://doi.org/10.1111/jbi.12156 Veron S, Clergeau P, Pavoine S (2016) Loss and conservation of evolutionary history in the Mediterranean Basin. BMC Ecology 16, 43. https://doi.org/10.1186/s12898-016-0099-3 Wu Y.-M., Shen, X.-L., Tong, L., Lei, F.-W., Mu, X.-Y., Zhang, Z.-X. (2021) Impact of Past and Future Climate Change on the Potential Distribution of an Endangered Montane Shrub Lonicera oblata and Its Conservation Implications. Forests 12, 125. https://doi.org/10.3390/f12020125 Wuerthner VP, Hua J, Hoverman J.T (2017) The benefits of coinfection: trematodes alter disease outcomes associated with virus infection. Journal of Animal Ecology 86, 921–931. https://doi.org/10.1111/1365-2656.12665 Youngquist MB, Boone MD (2021) Larval development and survival of pond-breeding anurans in an agricultural landscape impacted more by phytoplankton than surrounding habitat. PLOS ONE 16, e0255058. https://doi.org/10.1371/journal.pone.0255058 Additional Declarations No competing interests reported. Supplementary Files 4supplementaryfigures.pdf 5supplementarytables.docx Cite Share Download PDF Status: Published Journal Publication published 06 Dec, 2024 Read the published version in Biodiversity and Conservation → Version 1 posted Editor assigned by journal 06 May, 2024 Submission checks completed at journal 03 May, 2024 First submitted to journal 02 May, 2024 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. 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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-4361804","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":299313535,"identity":"895c2bbe-225f-4825-a1ee-64ce02606e27","order_by":0,"name":"Can Elverici","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYDACdhBhwMAD5nwAYjZ2QlqYkbQwzgBpYSZKC4zNgy6CDfAz8xg+riiwk2FgP/zssc2vbfJ8zAyMHz7m4NYi2cxjbHjGIJmHgSfN3Di377ZhGzMDs+TMbbi1GBxmS5NsMDjAwyDBYCad23ObEaiFjZkXjxb7w2zpPyFa2L9JW/bctieoxYCZ+RgjRAuPmTTDj9uJBLVIHGY+DHRYMg8bT06ZZG/D7eQ2ZsZmvH7hb29s/Njwx86en/34Nokff27bzm9vPvjhIx4tcMAGIhjbwGQDEerh4A8pikfBKBgFo2CkAADym0Emh7sunQAAAABJRU5ErkJggg==","orcid":"","institution":"Hacettepe University","correspondingAuthor":true,"prefix":"","firstName":"Can","middleName":"","lastName":"Elverici","suffix":""},{"id":299313537,"identity":"3a1a0d0f-0c17-466d-ba47-95b2fe7a0b29","order_by":1,"name":"Andrew Townsend Peterson","email":"","orcid":"","institution":"University of Kansas","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"Townsend","lastName":"Peterson","suffix":""},{"id":299313539,"identity":"61d03e45-9e3d-4b68-ba7b-e9553c98fc63","order_by":2,"name":"Utku Perktaş","email":"","orcid":"","institution":"Hacettepe University","correspondingAuthor":false,"prefix":"","firstName":"Utku","middleName":"","lastName":"Perktaş","suffix":""}],"badges":[],"createdAt":"2024-05-03 04:09:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4361804/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4361804/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10531-024-02988-6","type":"published","date":"2024-12-06T15:58:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":56193542,"identity":"7d0b5ba1-6db6-4156-9bea-e77ed8d9cde6","added_by":"auto","created_at":"2024-05-09 17:36:42","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":124411,"visible":true,"origin":"","legend":"\u003cp\u003eModeled current suitable areas for 36 amphibian species across the Mediterranean Basin under existing bioclimatic conditions\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4361804/v1/75d1a759dc94eb9c55a6d300.jpg"},{"id":56194374,"identity":"026f6e40-1836-4946-a960-1deb063d3f10","added_by":"auto","created_at":"2024-05-09 17:52:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":99759,"visible":true,"origin":"","legend":"\u003cp\u003eModeled suitable areas for amphibian species in the Mediterranean Basin under historical bioclimatic conditions, with (a) the Last Interglacial period, (b) the Last Glacial Maximum, and (c) the Mid-Holocene\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4361804/v1/4c968a5a410c13f861f6f233.jpg"},{"id":56194014,"identity":"d81ce2a6-73df-47a0-9ee5-9c38855e8c92","added_by":"auto","created_at":"2024-05-09 17:44:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":195836,"visible":true,"origin":"","legend":"\u003cp\u003eModeled future suitable areas for amphibian species in the Mediterranean Basin under RCP scenarios 2.6, 4.5, and 8.5 for the years 2050 and 2070. Panels are as follows: (a) 2050 under RCP 2.6, (b) 2070 under RCP 2.6, (c) 2050 under RCP 4.5, (d) 2070 under RCP 4.5, (e) 2050 under RCP 8.5, (f) 2070 under RCP 8.5\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4361804/v1/943a8d7b08a08bf48525f942.jpg"},{"id":70964924,"identity":"da2001f5-e841-4fc6-a962-b37ed42932b5","added_by":"auto","created_at":"2024-12-09 16:17:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":767174,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4361804/v1/371b5baf-8474-4ef4-b4c8-cb795639f81c.pdf"},{"id":56193546,"identity":"f8cb434a-98ac-4541-ba67-f134d6de103c","added_by":"auto","created_at":"2024-05-09 17:36:43","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":51937223,"visible":true,"origin":"","legend":"","description":"","filename":"4supplementaryfigures.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4361804/v1/a69bcd463b04bcd3fbfc095f.pdf"},{"id":56195265,"identity":"6c0b67a1-755c-4d71-a1cd-dff2223562a7","added_by":"auto","created_at":"2024-05-09 18:00:46","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":92572,"visible":true,"origin":"","legend":"","description":"","filename":"5supplementarytables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4361804/v1/a7f1afef4a48ced6b5517147.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eHotspots in Transition: Mediterranean Amphibian Diversity Under Different Climate Scenarios\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe Mediterranean Basin, extending from Portugal to Jordan and Italy to Morocco, is a biodiversity hotspot renowned for its remarkable geographic diversity and distinctive climatic conditions (Maiorano et al., 2013). Defined by its position along the western edge of the Alpine-Himalayan mountain belt (Mather, 2009), this region is characterized not just by complex topography but also by the diversity of habitats that support a wide array of species, particularly amphibians (Akın et al., 2010; Bonardi et al., 2022; Canestrelli et al., 2007; Console et al., 2020; Costa et al., 2021; Dufresnes et al., 2022; Erotokritou et al., 2024; Jablonski et al., 2021; Maiorano et al., 2011; Stümpel et al., 2016). The area's unique environmental settings arise from a combination of steep mountains, deep valleys, and numerous islands, creating a mosaic of biodiversity-rich ecosystems (Blondel, 2010; Mather, 2009; Nicolaci et al., 2014).\u003c/p\u003e\n\u003cp\u003eThe Mediterranean climate, with its hot, dry summers and mild, wet winters, has played a pivotal role in shaping the distribution and life cycles of numerous species in the region (Lionello et al., 2006). This climatic variability, largely influenced by the Mediterranean Sea acting as a thermal reservoir, has contributed significantly to the region’s status as a biodiversity hotspot, fostering high levels of endemism and species richness (Valente and Vargas, 2013). The diverse climatic zones, spanning from continental interiors to moist mountainous terrains, have further contributed to the unique ecological dynamics of the Mediterranean Basin, underscoring the importance of comprehending the intricate interactions between climate and biodiversity in this region (Nicolaci et al., 2014).\u003c/p\u003e\n\u003cp\u003eThe Mediterranean Basin has experienced dramatic climatic shifts, profoundly influencing its biodiversity and ecological dynamics. Pivotal periods such as the Last Interglacial, the Last Glacial Maximum, and the Mid-Holocene have shaped the evolutionary history of the region’s flora and fauna. For instance, during the Last Glacial Maximum, the Mediterranean served as a crucial refuge for many species, offering stable environments amidst broader climatic extremes (Brito, 2005; Hewitt, 2004). This historical legacy continues to influence current biodiversity patterns and is crucial for comprehending species' adaptations and vulnerabilities.\u003c/p\u003e\n\u003cp\u003eMédail and Diadema (2009) highlighted the importance of identifying and conserving refugia where biodiversity has thrived historically and can persist despite environmental pressures. The Mediterranean Basin's rich tapestry of habitats, driven by its climatic history and geographic features, supports a diverse range of species, making it a critical area for biodiversity conservation. Understanding the complex interplay between environmental conditions and biological diversity is essential for developing effective conservation measures that can safeguard the natural heritage of this region for future generations. In this study, we employed ecological niche modeling (ENM) to explore how amphibian populations in the Mediterranean Basin might respond to past and future climatic changes. We aim to pinpoint potential conservation areas that will be crucial for maintaining amphibian biodiversity in the face of increasing climatic instability, employing ENM within this biogeographic framework and investigating how amphibian distributions likely respond to current and future climate changes. The findings are intended to inform conservation strategies and safeguard the future of these ecosystems by providing fundamental insights on the climate component of the factors impacting biodiversity in this biodiversity hotspot.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eOccurrence Records\u003c/h2\u003e \u003cp\u003eWe identified 36 amphibian species restricted to the Mediterranean Basin through an extensive review of scholarly articles. Occurrence data from 1980 through 2022 were primarily sourced from the Global Biodiversity Information Facility (GBIF), with additional data integrated from various literature sources to ensure a reasonably comprehensive dataset (GBIF.org, 2023). Selected occurrence records were verified by comparing distribution data from published literature and the IUCN Red List of Species. Duplicates and erroneous records were detected and removed from the dataset via intensive visual inspection. To minimize effects of spatial autocorrelation on models focused on these endemic species, a spatial thinning distance of either 5 km or 2 km was applied using thin_data function in ellipsenm package (version 0.3.4) in R (version 4.2.3) (Cobos et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The 2 km distance was used when the number of occurrences was \u0026lt;\u0026thinsp;15; otherwise, a 5 km distance was implemented.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eEnvironmental Data Layers\u003c/h2\u003e \u003cp\u003eNineteen variables of bioclimatic data for different historical and forecasted periods were sourced from WorldClim version 1.4, providing data at a 2.5\u0026rsquo; spatial resolution. These datasets included scenarios for the current period, mid-Holocene (~\u0026thinsp;6 kybp), Last Glacial Maximum (LGM; ~22 kybp), and Last Interglacial (LIG; ~120\u0026ndash;140 kybp), as well as future projections for 2050 and 2070 (Hijmans et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). For reconstructing past climates for LGM and mid-Holocene, simulations from three general circulation models (GCMs) were employed: CCSM4, MIROC-ESM, and MPI-ESM-P; only one was available for LIG (Otto-Bliesner et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Future climatic conditions were explored using the same models but using MPI-ESM-LR instead of MPI-ESM-P, each for representative concentration pathways (RCPs) 2.6, 4.5, and 8.5. To enhance the data's applicability, climatic heterogeneity for annual mean temperature (bio1) and annual precipitation (bio12) were created using the focal function with a 3x3 moving window in the terra package (version 1.7\u0026ndash;74) in R (version 4.2.3) (Hijmans et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). We excluded certain variables (bio8, bio9, bio18, and bio19) because they include spatial inconsistencies among adjacent pixels (Escobar et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThree additional sets of bioclimatic layers were created for analysis by reducing inclusion of climatic dimensions under pairwise, layer-to-layer correlation thresholds of 0.9, 0.8, and 0.6, using the vifcor function in the usdm package (version 2.1-7) in R (version 4.2.3) (Naimi et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In the 0.6 threshold dataset, heterogeneity layers were retained. These datasets included 13, 10, 7, and 7 variables respectively, allowing for varied degrees of data complexity and specificity in ENM.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eM Simulations\u003c/h3\u003e\n\u003cp\u003eSimulating biologically realistic accessible areas for use as calibration areas in ENM enhances model performance through a biologically informed approach has recently become feasible (Barve et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, Machado-Stredel et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This methodology not only shapes the interpretation and outcomes of models (Barve et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), but also ensures that modeled niche dimensions and model transfers across different environmental contexts are more appropriate biologically. By incorporating key biological dynamics such as dispersal, colonization, and extinction, these simulations approximate the accessible areas for species (Sober\u0026oacute;n and Peterson \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). This process allows for the establishment of biologically relevant contrasts in model calibration, thereby minimizing extrapolation errors. Adoption of a simulation-based methodology enables quantitative estimates of a species\u0026rsquo; accessible area while accommodating its dispersal capabilities and environmental adaptability. We used the \"grinnell\" package (version 0.0.21) in R (version 4.2.3) to develop these simulations using default settings except for setting kernel density to 0.5, and dispersal events to 20 (Machado-Stredel et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Results of simulations were used as calibration areas in ENM and later to remove areas of overprediction.\u003c/p\u003e\n\u003ch3\u003eEcological Niche Modeling\u003c/h3\u003e\n\u003cp\u003eENM was performed using the Maxent software and the kuenm package in R, which are established tools for such modeling (Cobos et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Phillips and Dud\u0026iacute;k, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Occurrence data were partitioned into training (75%) and testing (25%) datasets to facilitate development and evaluation of models. A comprehensive, multi-criterion approach was employed to select the most robust models, prioritizing those that were (1) predicting independent data subsets with statistical significance (partial ROC test), (2) predicting independent data subsets \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ewith \u0026lt;\u003c/span\u003e\u0026thinsp;5% omission at a 10% training presence omission threshold, and (3) relatively simple according to the corrected Akaike information criterion (AICc) (Hurvich and Tsai, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Peterson et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This selection process was applied across a broad array of 900 candidate models generated by using 4 environmental data sets x 15 regularization multiplier values (ranging from 0.1 to 10), and 15 combinations feature classes (including linear, quadratic, product, and hinge features).\u003c/p\u003e \u003cp\u003eModels with the lowest AICc scores were selected, indicating they provide the most concise representation of the influence of sets of bioclimatic variables on species\u0026rsquo; distributions (G\u0026uuml;r et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Instead of relying on a single model, the median of suitable areas from the best-performing models (i.e., all models within 2 AICc units of the minimum among significant, low-omission candidate models) was used to derive final predictions, enhancing the robustness of the results. This method employed 10 replicates and specified no model extrapolation (Owens et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), ensuring the reliability of the findings.\u003c/p\u003e \u003cp\u003eFor model transfers to historical and projected future climate scenarios, these median-based predictions were rendered onto each temporal scenario and transformed into binary maps (suitable/unsuitable) employing a 10% training presence logistic threshold. The use of binary outputs in ecological niche modeling serves to delineate suitable areas clearly for the species under study. This approach sets clear ecological thresholds that are aligned with conservation-focused research objectives, facilitating straightforward interpretation and aiding in precise identification of areas suitable for potential conservation measures (Escobar et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). For all 36 amphibian species studied, binary maps were compiled for the Last Interglacial, Last Glacial Maximum, Mid-Holocene periods, the present, and future scenarios under RCPs 2.6, 4.5, and 8.5 for 2050 and 2070.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eFollowing removal of erroneous data, remaining records were reduced to minimize sampling bias. Counts of records before and after this reduction process are detailed in Supplementary Tables S75. These curated records were subsequently used in ENM. Accessible areas delineated for each amphibian species, derived from binarized results of the ecological niche models, are illustrated in the supplementary figures. Environmental variables incorporated into the models varied by set, reflecting specific bioclimatic conditions and spatial heterogeneities considered critical for each scenario (see Supplementary table S76)\u003c/p\u003e \u003cp\u003eFrom among the 900 candidate models for each species, best-performing models were selected based on their ecological validity and statistical robustness; a detailed summary of their statistics and the percent contribution of each variable presented in Supplementary Tables S1-S74. Model predictive ability assessed using the AUC metric for all species can also be seen in Supplementary Tables S1-S74. While contributions of individual variables varied among models, common trends took the form of the significant influence of bio12 (annual precipitation), bio15 (precipitation seasonality), and the spatial heterogeneity of bio12. These findings underscore the dependency of amphibian distributions on water availability, reflecting their ecological preferences and susceptibilities.\u003c/p\u003e \u003cp\u003eOverlay of ENM results for the 36 amphibian species identified species-rich areas corresponding to current Mediterranean biodiversity hotspots (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For the Last Interglacial (LIG) (Fig.\u0026nbsp;2a), models suggest a considerable westward-shifted distribution for amphibians, particularly in Portugal and France. Last Glacial Maximum (LGM) model outputs (Fig.\u0026nbsp;2b) match well with the expansion-contraction model expectations. Suitability in the Mid-Holocene period for the 36 amphibian species (Fig.\u0026nbsp;2c) exhibited a distribution highly similar to present-day conditions. In terms of future potential distributions (2050 and 2070), model transfers indicated significant shifts in concentrations of suitable areas for amphibians in the Mediterranean Basin (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study combines ENMs for various amphibian species in the Mediterranean with a broader examination of the region's biodiversity to project and explore amphibian diversity patterns under past, present, and future climate scenarios. The Mediterranean Basin, widely recognized as a biodiversity hotspot, plays a critical role in harboring endemic and threatened species across various taxa (Maiorano et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Numa et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). ENM, a method considered highly useful for interpreting species' ecological and historical biogeography (Perktaş et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2015a\u003c/span\u003e), was chosen for its potential to deliver meaningful, geographically explicit conservation outcomes for this region, which is under significant threat from climate change and human activities.\u003c/p\u003e \u003cp\u003eThe Mediterranean Basin\u0026rsquo;s status as a global biodiversity focus is further emphasized by its qualification as one of the original 36 Global Biodiversity Hotspots, a distinction it earns by hosting\u0026thinsp;\u0026gt;\u0026thinsp;1500 endemic species vascular plants and experiencing\u0026thinsp;\u0026gt;\u0026thinsp;30% loss of its original natural vegetation (Myers et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Hrdina and Romportl, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This study focuses on endemic amphibian species, the significant number of which underscores the critical nature of the region in terms of its unique and threatened biodiversity.\u003c/p\u003e \u003cp\u003eThe geographic distributions of species in the Mediterranean have been influenced by alternating glacial and interglacial periods, as evidenced by historical climate dynamics. The expansion-contraction model, especially relevant during colder periods, is supported by the findings from Hewitt (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and Schmitt (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This model suggests species sought refuge in southern, warmer climates during glaciations (Stojak and Jędrzejewska, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Analyses across various taxa, including mammals, plants, and invertebrates, underline the genetic impacts of these climatic shifts on historical biogeography (G\u0026uuml;r, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Taberlet et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Notably, the LIG models show a westward distribution shift in amphibians, specifically in Portugal and France, attributed to regional climatic stability (Rioual et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), which is congruent with individual species' suitabilities across various taxa (Perktaş et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; \u0026Uuml;lker et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These patterns confirm the relevance of historical climate refugia suggested by M\u0026eacute;dail and Diadema (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), although our LGM outputs suggest a slight misalignment, they still match current species suitability. The similarity of Mid-Holocene distributions to contemporary conditions reflects the findings by Badis et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), Wu et al. (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and Segatto et al. (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), highlighting the ongoing influence of historical climates on present biodiversity patterns and emphasizing the need for targeted conservation strategies.\u003c/p\u003e \u003cp\u003eBiodiversity hotspots have been instrumental in informing global conservation priorities, and have been used to focus conservation actions on particular regions with exceptional concentrations of endemic species undergoing significant habitat loss (Myers et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). As a contrasting concept, biodiversity coldspots are limited-diversity regions often explained by harsh ecological conditions (Schr\u0026ouml;ter et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Biodiversity hotspots have received significant attention and conservation efforts, yet coldspots remain relatively overlooked and poorly understood (Procheş, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), even though the scarce biodiversity in coldspots can be sensitive to environmental changes and human activities (Liu et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These two concepts are relevant, given that current suitable areas may transition between the two states over time (REF), as has also been illustrated in this study. For example, the southern part of the Iberian Peninsula and central Anatolia appear to lose their significance, whereas northern Europe and Caucasia will have increasing significance under future climate scenarios.\u003c/p\u003e \u003cp\u003eIn the Mediterranean Basin, invasive species such as the African clawed frog (\u003cem\u003eXenopus laevis\u003c/em\u003e) and various invasive crayfish species (e.g., \u003cem\u003eProcambarus clarkii\u003c/em\u003e and \u003cem\u003ePacifastacus leniusculus\u003c/em\u003e) pose significant ecological threats. These invaders are particularly problematic because of their adaptability to Mediterranean climates and their aggressive competition with native amphibians for critical resources and habitats (Lillo et al., 2010; Mota-Ferreira \u0026amp; Beja, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The presence of invasive species has been linked to reductions in the reproductive success of native species, fundamentally altering ecological interactions, and potentially leading to local extinctions even without direct habitat destruction (Clavero et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Shifting distributions of species, driven by present climate change processes, is emerging as a threat to biodiversity, especially for amphibians in the Mediterranean.\u003c/p\u003e \u003cp\u003eMoreover, the phenomenon of introgression through hybridization can present a further challenge to conserving genetic diversity in the region. Introgressive hybridization, particularly observed between native European tree frogs (\u003cem\u003eHyla arborea\u003c/em\u003e) and introduced species like \u003cem\u003eH. intermedia\u003c/em\u003e, can significantly diminish the viability and fertility of hybrid individuals, potentially reducing the overall fitness of local amphibian populations (Dufresnes et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Such genetic intermixing may lead to homogenization and eventual replacement of native gene pools, further complicating conservation efforts and threatening the unique biodiversity of the Mediterranean Basin (Dufresnes et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs illustrated by M\u0026eacute;dail and Diadema (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), the Mediterranean biodiversity hotspot is home to 52 putative or possible refugia based on studies of plant distributions. Our ENM-based analyses align these refugia with the current distributions of amphibians. Notably, influences of climate change suggest significant temporal transitions for these refugial areas, with several changing from hotspots to coldspots for our target species. These transitions are expected to affect climatic suitability of these areas by the 2050 and 2070 time horizons. Implications of different RCP scenarios are profound, with the best-case scenario RCP 2.6 showing less-dramatic shifts compared to the worst-case scenario RCP 8.5. This result indicates that some conservation priorities may need to shift towards areas that are currently regarded as coldspots, which have not traditionally been considered as areas of conservation focus (Cox and Underwood, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). For instance, whereas the Iberian Peninsula and Central Anatolia are projected to lose significant diversity, regions in central and western France are expected to gain diversity, suggesting a need to reevaluate conservation priorities and resource allocation in these emerging priority areas, especially considering the high human population density. In line with other studies, our findings confirm that the Mediterranean Basin is exceedingly vulnerable to climate change, which poses significant risks to biodiversity conservation (Almeida et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ben\u0026iacute;tez-Ben\u0026iacute;tez et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Guiot and Cramer, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA notable limitation of this study lies in its focus solely on climatic variables to explore distributional shifts of amphibians in the Mediterranean Basin. While this approach is critical for understanding the impacts of climate change, it inherently overlooks other significant ecological factors that can also profoundly influence amphibian populations (Costa et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Dvorsky et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Youngquist and Boone, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Non-climatic threats such as vegetation distributions, habitat destruction, urbanization, pollution, and introduction of invasive species, are also at least potentially important in shaping present and future distributions of these species but are not directly accounted for in our models (Harper et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Underwood et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Veron et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In this sense, this study should be interpreted as exploring climate-based potential geographic distributions of species.\u003c/p\u003e \u003cp\u003eEmerging threats from diseases such as chytridiomycosis, caused by \u003cem\u003eBatrachochytrium dendrobatidis\u003c/em\u003e, and other coinfections further exemplify the challenges that need to be integrated into full conservation planning applications of such studies (Pereira et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Wuerthner et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Such pathogenic factors are known to cause rapid declines in amphibian populations and could drastically alter the landscape of biodiversity in the Mediterranean, independent of or in conjunction with climate change. This study also not incorporate effects of multiple stressors beyond climatic factors, such as interactions between disease pathogens and environmental contaminants. For instance, effects of trematode infections are exacerbated by pesticide exposure, highlighting the complex interplay between biotic and abiotic factors which can influence amphibian health and survival (Kiesecker, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). These factors could significantly alter the outcomes of climate change impact predictions by either mitigating or intensifying the effects perceived solely through the lens of climatic variables.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eThis study leverages the potential of ENM, evaluating effects of past and future climate variation to illuminate how climate change might reshape distributions of amphibian species across the Mediterranean Basin, a key biodiversity hotspot. Our findings indicate significant shifts in climatic suitability under various climate scenarios from the past to the future, predicting a transformation in regional biodiversity significance from current hotspots to potential new conservation areas. These changes are particularly manifested in regions such as central and western France, which could become crucial future refugia for amphibian species. These insights are crucial for guiding future conservation efforts, ensuring that strategies are dynamically aligned with projected changes in habitat conditions. Although the analysis focused primarily on climate change, the implications of our findings necessitate further and future consideration of human impacts, such as urbanization and habitat alteration, particularly in densely populated Mediterranean areas.\u003c/p\u003e \u003cp\u003eAcknowledging limitations of a study such as this one is essential for refining future research approaches. It emphasizes the need for integrated models that not only consider a broader range of environmental variables but also incorporate dynamic interactions between multiple stressors. This holistic view is crucial for developing more robust and effective conservation strategies that can address the multifaceted challenges facing amphibian populations in the Mediterranean Basin. By providing a predictive framework, this research supports proactive conservation planning, helping to safeguard Mediterranean amphibian biodiversity against the impending challenges of climate change.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFUNDING\u003c/h2\u003e \u003cp\u003eCE received support from the Scientific and Technological Research Council of Turkey through the 2214-A International Research Fellowship Programme for PhD Students, under project number 1059B142200286.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. C.E. acquired the data and created visuals. C.E. contributed in the analysis. C.E. created the original manuscript. A.T.P. thoroughly reviewed and edited the manuscript. U.P. contributed as Supervisor. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eSpecial thanks are extended to Dr. Utku Perktaş for his guidance and insights throughout the development of this project. His expertise and feedback were invaluable in shaping the research.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eRaw occurrence data was obtained from Global Biodiversity Information Facility.GBIF.org (11 April 2023) GBIF Occurrence Download https://doi.org/10.15468/dl.g8e3sz\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkın \u0026Ccedil;, Bilgin CC, Beerli P, Westaway R, Ohst T, Litvinchuk SN, Uzzell T, Bilgin M, Hotz H, Guex G, Pl\u0026ouml;tner J (2010) Phylogeographic patterns of genetic diversity in eastern Mediterranean water frogs were determined by geological processes and climate change in the Late Cenozoic. 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PLOS ONE 16, e0255058. https://doi.org/10.1371/journal.pone.0255058\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biodiversity-and-conservation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bioc","sideBox":"Learn more about [Biodiversity and Conservation](https://www.springer.com/journal/10531)","snPcode":"10531","submissionUrl":"https://submission.nature.com/new-submission/10531/3","title":"Biodiversity and Conservation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Mediterranean Basin, biodiversity hotspots, amphibians, ecological niche modeling, climate change","lastPublishedDoi":"10.21203/rs.3.rs-4361804/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4361804/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Mediterranean Basin, a region renowned for its biodiversity, is experiencing unprecedented ecological changes owing to shifting climate patterns. This study employs ecological niche modeling to assess impacts of historical, current, and future climate scenarios on climatic suitability patterns for 36 endemic amphibian species. The study incorporates a diverse set of environmental variables to project species\u0026rsquo; potential geographic distributions across significant climatic events, including the Last Interglacial, Last Glacial Maximum, and Mid-Holocene, as well as future projections for 2050 and 2070 under various Representative Concentration Pathways (RCPs). The resulting models underscore the congruence of predicted species-rich areas with established biodiversity hotspots, and highlight the influence of precipitation on amphibian distribution. Notably, the study reveals potential shifts in biodiversity importance of different areas across the Mediterranean landscape, with certain regions projected to transition from hotspots to coldspots and \u003cem\u003evice versa\u003c/em\u003e, in response to future climatic changes. These insights contribute to a broader discourse on conservation priorities, emphasizing the need for adaptive strategies that can accommodate the dynamic nature of biodiversity in response to climate change. The findings of this study serve as a call to action for preserving Mediterranean biodiversity, providing a data-driven foundation for informed conservation planning in this critical hotspot.\u003c/p\u003e","manuscriptTitle":"Hotspots in Transition: Mediterranean Amphibian Diversity Under Different Climate Scenarios","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-09 17:36:30","doi":"10.21203/rs.3.rs-4361804/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2024-05-06T14:55:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-04T01:45:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biodiversity and Conservation","date":"2024-05-03T03:59:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biodiversity-and-conservation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bioc","sideBox":"Learn more about [Biodiversity and Conservation](https://www.springer.com/journal/10531)","snPcode":"10531","submissionUrl":"https://submission.nature.com/new-submission/10531/3","title":"Biodiversity and Conservation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d03e5122-055e-46a3-a513-b7768b7f8cc9","owner":[],"postedDate":"May 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-09T16:06:30+00:00","versionOfRecord":{"articleIdentity":"rs-4361804","link":"https://doi.org/10.1007/s10531-024-02988-6","journal":{"identity":"biodiversity-and-conservation","isVorOnly":false,"title":"Biodiversity and Conservation"},"publishedOn":"2024-12-06 15:58:02","publishedOnDateReadable":"December 6th, 2024"},"versionCreatedAt":"2024-05-09 17:36:30","video":"","vorDoi":"10.1007/s10531-024-02988-6","vorDoiUrl":"https://doi.org/10.1007/s10531-024-02988-6","workflowStages":[]},"version":"v1","identity":"rs-4361804","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4361804","identity":"rs-4361804","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}