Projections of suitable habitat loss and its implications in conservation for endemic non-pseudantial Euphorbioideae (Euphorbiaceae) species in Northeastern Brazil under climate change scenarios

Projections of suitable habitat loss and its implications in conservation for endemic non-pseudantial Euphorbioideae (Euphorbiaceae) species in Northeastern Brazil under climate change 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 Projections of suitable habitat loss and its implications in conservation for endemic non-pseudantial Euphorbioideae (Euphorbiaceae) species in Northeastern Brazil under climate change scenarios Tiago Oliveira, Yeison Jaroc Lombo-Sanchez, Karen Yuliana Suarez-Contento, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7781649/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Climate change has intensified negative impacts on biodiversity through changes in precipitation patterns and rising global average temperatures. Semi-arid regions, such as parts of Northeastern Brazil, are particularly susceptible to these changes, with projections indicating that they will become hotter and drier, reducing the climatic suitability of several plant species. In this context, endemic and restricted-range species may be highly vulnerable. In this study, we used distribution modeling to estimate potential changes in the geographic distribution and conservation of 12 endemic Euphorbiaceae species from Northeastern Brazil, to inform conservation strategies. We found that climate change will have distinctly different impacts on the suitable habitat areas for the analyzed taxa. Projections indicate that in the optimistic scenario (SSP126), Sapium sceleratum could expand its suitable range by approximately 80%, while Microstachys uleana and Actinostemon appendiculatus will experience limited gains (< 14%), and other species will experience losses exceeding 40%. In the pessimistic scenario (SSP585), five taxa lose areas of suitability above 40%, but Sapium sceleratum and Algernonia bahiensis could expand by 76% and 100%, respectively. We also documented a reduction in species richness in all future climate scenarios analyzed. Furthermore, in both climate scenarios, a general trend toward increasing extinction risk is observed for most species. Thus, this study clearly demonstrates that most endemic species in the family are highly vulnerable to various future climate change scenarios and that conservation measures such as the creation of protected areas within the species' climatically suitable concentrations should be established. Spatial analysis Biogeography Ecological Niche Modeling Hippomaneae Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Climate change significantly influences species population dynamics (Zhao 2021) and may modify climate suitability and precipitation patterns in natural ecosystems (MMA 2018 ). This, in turn, may increase the risk of large-scale extinction events (Pillet et al. 2022 ), as has been recorded several times throughout the geological period (Elewa and Abdelhady 2020 ). Currently, the possibility of a new extinction event caused by the increase in Earth's temperature, driven by the intensification of anthropogenic activities, is being discussed (Schmidt 2021 ; IPCC 2023 ). These environmental changes can accelerate the decline in plant health in both natural environments and agricultural systems (Pautasso et al. 2012 ), negatively impact the distribution of endemic species (Manes et al. 2021 ) and increase vulnerability to extinction (Qian and Qian 2024 ). The subfamily Euphorbioideae (Euphorbiaceae) comprises representatives of the tribes Euphorbieae, Hippomaneae, Hureae, Pachystromateae, and Stomatocalyceae (Wurdack et al. 2005 ). The group referred to as non-pseudantial Euphorbioideae includes the tribes that lack pseudantial inflorescences of the cyathium type (Hippomaneae, Hureae, Pachystromateae, and Stomatocalyceae), and is characterized by more conventional flowers, usually arranged in racemes, thyrsus or panicles. The subfamily is predominantly composed of species producing toxic latex and defensive chemical compounds (García-Saldaña 2024), with recognized potential for cancer treatment (Souza et al. 2025a ), biological control (Vaz et al. 2010 ), rubber production (Guerra et al. 2021 ), traditional medicine (Agra et al. 2008 ; Ramos et al. 2024 ), and pharmaceutical applications (Silva et al. 2024). In Brazil, the Euphorbioideae subfamily is represented by 219 species, of which 100 are endemic and 26 are restricted to the Northeastern region, including 15 belonging to the non-pseudantial group (Flora e Funga do Brasil 2025). These species occur mainly in the Atlantic Forest and Caatinga (Flora e Funga do Brasil 2025), many of them with extremely restricted geographic distributions (Oliveira 2010 ; Esser 2012 ; Athiê-Souza et al. 2015 ). Approximately one third are classified in some category of threat (Athiê-Souza et al. 2015 ; Fernandez and Rosa 2018 ; Fernandez and Moraes 2020 ; Amorim and Fernandez 2021 ). The Northeastern region is home to more than 11,900 species of angiosperms, making it the third most diverse region in the country in terms of flora (Flora e Funga do Brasil 2024). In contrast, it is also one of the most vulnerable to current climate change, subject to changes in the distribution of extreme temperature and rainfall events (Araujo and Willians 2000; Suarez-Contento et al. 2024 ). According to the Brazilian Panel on Climate Change (PBMC 2013 ), a reduction of up to 20% in precipitation and an increase of approximately 1°C in average air temperature are projected by 2040, with these trends progressively worsening by the end of the century, which could accelerate processes such as the desertification of the Caatinga. Furthermore, in recent decades this region has suffered a high degree of deforestation associated with the loss of habitats for agricultural activities (Araújo et al. 2023), resulting in a high proportion of locally threatened species, including endemic ones (Leal et al. 2005 ). In this context, studies that associate climate change and its future projections with the population dynamics of plant species are essential, especially for developing conservation strategies and contributing to elucidating the impacts of environmental changes on the biodiversity of semiarid regions (Cavalcante et al. 2020 ). Furthermore, investigating the potential distribution of species is an essential tool for identifying priority areas for conservation, helping to direct management efforts and reduce the limitations associated with the creation of new conservation units (Diniz-Filho et al. 2009 ). Applying spatial analyses with a research approach, such as those based on diversity metrics (Bullong et al. 2024 ), can deepen the understanding of the population dynamics of endemic species, especially those with restricted and regionalized geographic distributions (Echternacht et al. 2011 ; Costa et al. 2024 ). The use of species distribution models (ENM) has also proven effective in elucidating spatial patterns in specific regions and ecosystems (Siqueira and Durigan 2007 ), such as Northeastern Brazil. The potential effects of climate change on the distribution of species have been widely investigated in regions such as Asia and Europe (Qazi et al. 2022 ). In contrast, in Neotropical countries, particularly Brazil, which harbors one of the largest portions of global biodiversity, including a high number of endemic species, such studies remain relatively scarce. In Brazil, most research has been concentrated in the Southeastern and Southern regions (Duarte et al. 2019 ), while other areas that are highly vulnerable to climate change, such as the Northeastern, have received less attention. This gap is particularly evident in arid and semi-arid regions, where ecological niche modeling studies face additional challenges due to the scarcity of occurrence data (Vasconcelos et al. 2024 ). Nevertheless, recent studies have indicated severe habitat losses for many animal and plant species, especially within the Caatinga biome (Rodrigues et al. 2015 ; Simões et al. 2019 ; Moura et al. 2023 a; Suarez-Contento et al. 2024 ), with the most critical impacts predicted for endemic species (Simões et al. 2019 ; Almeida et al. 2024 ; Suarez-Contento et al. 2024 ). In this study, we analyzed the impacts of climate change on the distribution of endemic non-pseudantial Euphorbioideae species in Northeastern Brazil, projecting their potential distribution under different climate scenarios until the year 2100. Furthermore, we identified the areas of greatest species richness and estimated the extinction risk of these taxa in the face of predicted environmental changes. Materials and Methods Study area The Northeastern region is in Brazil's tropical belt (1°02' N, 18°20' S, 34°47' W, 48°45' W) and comprises the states of Maranhão, Piauí, Ceará, Rio Grande do Norte, Paraíba, Pernambuco, Alagoas, Sergipe, and Bahia. It is the third-largest region in the country in terms of territorial extension, with 1,561,177.80 km², corresponding to approximately 18.26% of the national territory (IBGE 2006). Its vast spatial dimension is reflected in significant physical, cultural, and climatic variations, which led to its subdivision into four subregions: the Mid-North, characterized as a transition zone between the Semiarid and the Amazon; the Sertão, located in the interior of the region; the Agreste, a transition zone between the Sertão and the Zona da Mata; and the Zona da Mata, located in the coastal strip that extends approximately 200 km inland (IBGE 2006). Due to the region's remarkable environmental heterogeneity, areas of high rainfall are found along the coast, where annual precipitation can exceed 2,000 mm, in contrast to the semiarid Sertão, where annual rainfall is often less than 400 mm and droughts are recurrent. Temperatures also vary: while the coast has annual averages between 24°C and 28°C, the Sertão experiences high daytime temperatures, often above 30°C. In terms of vegetation cover, the Northeast is home to formations belonging to four major domains: the Atlantic Forest, restricted to small areas near the coast; the Cerrado, present in western Bahia and southern Maranhão; the Caatinga, predominant in the semiarid interior; and the Amazon, represented by the Mata dos Cocais in portions of Maranhão, Piauí, Rio Grande do Norte, and Ceará (Rizzini 1963 ). Each of these domains presents distinct biological, hydrographic, climatic, and topographic characteristics, offering a wide range of ecological niches and environmental conditions that contribute to the region's high biodiversity. Database – species occurrences The occurrence data of the endemic species of non-pseudantial Euphorbioideae of Northeastern Brazil were compiled from specific literature (e.g., Wurdack et al. 2005 ; Oliveira 2010 ; Athiê-Souza et al. 2015 ; Pscheidt 2015 ; Cordeiro 2018), where 15 taxa were identified (14 spp. and 1 subspecies), of which 12 were evaluated in this study (Table 1 ). Subsequently, collection occurrence records were extracted from 46 indexed herbaria (ALCB, ASE, CEN, CEPEC, CEPLAC, CESJ, CSTR, EAC, ESA, F, FUEL, FURB, G, HDELTA, HFC, HPL, HRCB, HTSA, HUEFS, HUESB, HURB, HVASF, IAN, IBt, IPA, JPB, MAC, MBM, MCCA, MCMG, MN, MO, MOSS, NY, PEUFR, MNHN, SORO, SP, SPF, UB, UEC, UEFS, UFBA, UFP, US, USP -- acronyms follow Thiers 2025 , continuously updated) and HST herbarium (not indexed) through the virtual platforms SpeciesLink ( https://specieslink.net/ ) and Reflora ( https://reflora.jbrj.gov.br/reflora/herbarioVirtual/ ), totaling 1077 specimens. The data were then screened to eliminate duplicate specimens, those with non-georeferenceable information, and/or uncertain identification. Specimens identified by experts in the Euphorbiaceae family were used to validate identification. After screening, the database totaled 421 records sampled here. Table 1 Minimum and maximum elevation of the sampled species endemic to Northeastern Brazil Species Minimum elevation (m) Maximum elevation (m) Ac_appendiculatus 12 350 Al_bahiensis 13 225 Gr_franciscana 119 120 Ma_f_bahiensis 372 770 Mi_heterodoxa 4 1206 Mi_revoluta 888 1269 Mi_uleana 777 1531 Op_parviflorum 360 360 Op_pedunculare 16 474 Se_jacobinensis 50 860 Se_macrocarpa 18 853 Se_trinervia 607 607 Sa_sceleratum 153 887 St_loranthacea 839 1074 St_trapezoidea 170 1129 Table 2 Extent of Occurrence (EOO) and Area of Occupancy (AOO) based on the current distribution of endemic species of Northeastern Brazil Species EOO (km²) AOO (km²) Ac_appendiculatus 169,959.304 114 Al_bahiensis 8,230.618 28 Gr_franciscana 00 6 Ma_f_bahiensis 35,387.887 28 Mi_heterodoxa 226,.694.344 356 Mi_revoluta 146.963 24 Mi_uleana 31,357.204 132 Op_parviflorum 0 4 Op_pedunculare 4,363.019 24 Se_jacobinensis 328,437.8540 116 Se_macrocarpa 442,805.7598 336 Se_trinervia 0 4 Sa_sceleratum 212,176.014 32 St_loranthacea 634.365 52 St_trapezoidea 599,044.629 232 Environmental Variables and Distribution Modeling A set of 19 bioclimatic variables for the different scenarios were obtained from WorldClim 2.0 (Fick and Hijmans 2017 ), with a 30-second resolution (using the boundaries of the Northeastern region of Brazil). To avoid multicollinearity problems and improve model robustness, a 70% correlation threshold was applied to the selection of environmental variables (Booth et al. 2014 ). After this analysis, the variables were: bio2, bio3, bio4, bio8, bio14, bio16, bio18, and bio19. Modeling of the potential distribution of species was performed using the Maxent algorithm (Phillips et al. 2017 ), implemented through the modleR package (Sánchez-Tapia et al. 2020 ) in R software (v. 4.4.0, R Core Team 2023). Of the 15 taxa initially considered, only 12 were modeled, as three of them have only the type locality. Maxent is a maximum entropy method that models species distribution based on presence data and environmental variables. It is particularly advantageous for species with few occurrence records—a minimum of 5 to 10 unique occurrence points is recommended for robust analyses (Phillips et al. 2006 ). Its effectiveness with small sample sizes is due to the exclusive use of presence data and the incorporation of regularization techniques that prevent overfitting (Wisz et al. 2008 ; Phillips et al. 2006 ; Hernandez et al. 2006 ). The accuracy and robustness of the models were assessed using cross-validation techniques, with performance measured by the Area Under the ROC Curve (AUC) (Boria et al. 2014 , 2016 ; Cobos et al. 2019 ). The calibration area for each species was defined by a minimum convex polygon encompassing 100% of the occurrence points, expanded by a 1.5° buffer. The model projection area corresponded to the geographic limits of Northeastern Brazil, as this is the region where the study species are present. Future projections (2080–2100) were performed using four General Circulation Models (GCMs) representing the full range of climate sensitivity (ECS 2.9–5.5°C): BCC-CSM2-MR, CMCC-ESM2, HadGEM3-GC31-LL, and IPSL-CM6A-LR (Boucher et al. 2020 ; Cherchi et al. 2019 ; Williams et al. 2018 ; Wu et al. 2021 ; Zelinka et al. 2020 ). These GCMs were selected based on their robust historical performance in South America (Eyring et al. 2016 ; Hodnebrog et al. 2022 ; Scafetta 2023 ; Zelinka et al. 2020 ), allowing for contrast between the Shared Socioeconomic Pathway scenarios: SSP126 (optimistic) and SSP585 (pessimistic). The area of environmental suitability was calculated from the distribution models using the cellStats() function of the raster package (Hijmans 2012 ) in R software (v. 4.4.0, R Core Team 2023). A suitability threshold of 0.6 was applied to generate binary maps, considering cells with values above the threshold as suitable. Based on the suitability area indicated in the ecological niche modeling, the extent of the protected territory (km²) was calculated using the mask_thr_projs_mscn_b function from the ENMwizard package (Heming et al. 2019 ). Data on protected areas were obtained from the UNEP-WCMC and IUCN databases (UNEP-WCMC and ShareAction 2024 & IUCN 2023). All analyses were conducted in R software (v. 4.4.0, R Core Team 2023). To assess the taxonomic diversity of endemic species under different climate scenarios, we used distribution models for each species. The metric was calculated using a tree-based approach and raster data (Mota et al. 2023 ). Alpha diversity was obtained using the spat.alpha() function from the divraster package (Mota et al. 2023 ). This function is suitable for raster data and optimizes calculations for large datasets. Taxonomic diversity was defined as the species richness in each raster cell, where each species is connected to the tree root by an edge of unit length (Mota et al. 2023 ). All these analyses were performed in R software (v. 4.4.0, R Core Team 2023). Risk of species extinction For the current conservation status, the area of occupancy (AOO) of the species was used as follows: CR < 100 km², EN < 5,000 km², VU < 20,000 km², NT 30,000 km². Conversely, for future scenarios, the conservation status analysis was performed based on the potential distribution and projections for future scenarios, using the values of the extent of the areas of suitable occurrence and area of occupancy, according to criterion A3(c) (IUCN 2024). Criterion A3 considers the "projected or estimated future population reduction," and subcriterion (c) considers the decline in area of occupancy (AOO), extent of occurrence (EOO), and/or habitat quality. Therefore, we classified species according to the percentage of habitat loss as follows: Extinct (EX) – 100%; Critically Endangered (CR) – above 80%; Endangered (EN) between 50% and 80%; Vulnerable (VU) – between 30% and 50%; Near Threatened (NT) – slightly below 30% (Pomoim et al. 2022 ). All analyses were performed using R software (v. 4.4.0, R Core Team 2023). Results All taxa exhibited changes in their areas of climatic suitability in both projected scenarios (Figs. 1 and 2 ). Although the optimistic scenario (SSP126) indicates more significant reductions in the loss of climatic suitability for a greater number of species (over 25%), the pessimistic scenario (SSP585) proves more critical, as the reductions occur primarily in species with already restricted areas of suitability, resulting in greater susceptibility to inclusion in threatened categories. In SSP126, Sapium sceleratum could expand its area of ​​suitability by approximately 80%, while Microstachys uleana and Actinostemon appendiculatus will experience gains of no more than 14%. The opposite trend was observed for other taxa, such as Mabea fistulifera subsp. bahiensis , which experienced a 75% loss in area, followed by Ophthalmoblapton pedunculare , Microstachys heterodoxa , and Sebastiania jacobinensis , which had the most critical losses above 40% (Fig. 3 A). Regarding the SSP585 scenario, a 40% loss was observed for Mabea fistulifera subsp. bahiensis , Ophthalmoplapton pedunculare , Microstachys heterodoxa , and Stillingia loranthacea . On the other hand, Sapium sceleratum could gain 76% in area, and Algernonia bahiensis could double its area of ​​suitability (Fig. 3 B). The environmental suitability analysis revealed significant differences among species regarding the proportion of their potential habitats protected by conservation units, considering the current scenarios, SSP126, and SSP585. Overall, most species have a low level of protection. Less than 20% of the suitable area for these species overlaps with protected areas. Species such as O . pedunculare , M. revoluta , and M. uleana stand out for having high percentages of protection in some scenarios, but have relatively small potential areas of occurrence. This suggests that, despite their limited distribution, much of their projected habitats are within conservation units, which may benefit their conservation in the future. On the other hand, widely distributed species such as Sp . sceleratum and Se . macrocarpa maintain large areas of environmental suitability, but with low relative protection, representing a potential risk in the face of climate change, especially in the most pessimistic scenario (SSP585) (Fig. 4 ). In general, the analyzed taxa exhibit higher richness values ​​in southern Bahia, Chapada Diamantina, and the Atlantic Forest areas on the east coast of the Northeast. These regions, although experiencing reductions in both future scenarios, still concentrate the greatest richness (Fig. 5 ). In the current scenario, the regions with the highest species richness are concentrated primarily in southern Bahia and northern Minas Gerais, reaching values ​​of up to five species per pixel. Cores/secondary areas of species richness were also identified in elevated areas of Pernambuco, Alagoas, and Paraíba. Under the SSP126 scenario, a general reduction in species richness is observed. Although some higher elevation areas in Bahia and Pernambuco maintain some suitability, the extent of zones with high richness (values ​​≥4) decreases. In the pessimistic scenario (SSP585), the effects of climate change are more pronounced. Species richness declines drastically, and areas that previously had high suitability now show low or intermediate values ​​(1–3 species per pixel). Only small regions in southern Bahia and Pernambuco retain moderate levels of richness. These results indicate a trend toward a loss of climatic suitability for the studied species, with potential consequences for regional biodiversity conservation, especially in the most extreme scenarios. The conservation status of the 12 endemic taxa of the Northeastern shows a predominantly increasing trend without risk of extinction (Fig. 6 ). Our results indicate that in the current scenario, 10 species (83%) are classified as Least Concern (LC) and two (16.66%) are classified as Near Threatened (NT). In both future scenarios, A. pendiculatus maintains its Least Concern (LC) status, demonstrating some resilience of its potential habitats. In the optimistic scenario (SSP126), 75% of the species migrated to higher risk categories, with specific species classified as Near Threatened (NT), Endangered (EN), and Vulnerable (VU). Similarly, in the pessimistic scenario (SSP585), the majority of species (75%) were found in some threat category. The increase in risk is most pronounced for O. pedunculare , which changes from Least Concern (LC) to Near Threatened (NT) in SSP126 and subsequently to Endangered (EN) in SSP585; and for St. loranthacea , which jumps from Least Concern (LC) to Endangered (EN) in SSP126. The most critical case is that of Mabea fistulifera subsp. bahiensis , which changes from Least Concern (LC) to Endangered (EN) in SSP126 and, in the worst-case scenario, reaches Critically Endangered (CR) status. In contrast, A. bahiensis exhibits an atypical pattern, worsening from Least Concern (LC) to Near Threatened (NT) in SSP126 but returning to Least Concern (LC) in SSP585. Discussion Our results highlight complex and worrying patterns in the potential distribution and conservation status of non- pseudantial endemic Euphorbioideae species in Northeastern Brazil under climate change scenarios. A generalized contraction of areas of climatic suitability was observed for most taxa (75%) under both scenarios, resulting in a significant increase in extinction risk. Furthermore, we observed that the effects of climate change can vary distinctly across areas of suitability, thus being species-specific. These results corroborate recent evidence that many endemic plant species are sensitive to climate change, primarily because they often have restricted distributions and fragmented habitats, which represent barriers to the colonization of new climatically suitable areas in the future (Suarez-Contento et al. 2024 ). Furthermore, seasonally dry tropical forests, such as the Caatinga, are highly sensitive to climate change, as they are already close to their tolerance limits in terms of temperature and water availability (Allen et al. 2017 ). Thus, rising temperatures and reduced engineering standards can significantly reduce suitable habitats for many species (Marengo et al. 2011; Andrade et al. 2017 ). Moura et al. ( 2023 ) used ENMs to assess potential changes in the distribution of non-volant mammals in the Caatinga and observed that 85% of mammal species will lose suitable habitats, with a quarter of species projected to completely lose their suitable habitats by 2060. A similar result was found in the study by Silva et al. ( 2019 ), which demonstrated that habitats in the Caatinga with a high probability of occurrence (> 80%) of endemic species will be reduced (up to ~ 10% for trees, ~ 13% for non-trees, 10–28% for species with any pollination/breeding system), with the largest reductions recorded for species with specialized reproductive traits. In this study, expansions into suitable areas were observed in both scenarios only for S. sceleratum and A. appendiculatus , indicating that some species can withstand extreme climate events, as they possess morphophysiological adaptations capable of withstanding prolonged droughts (Bongers et al. 2017 ). According to Cordeiro et al. ( 2018 ), S. sceleratum is commonly found on rocky outcrops and in environments subject to seasonal water deficit in the Caatinga. According to Souza et al. ( 2025b ), the areas surrounding inselbergs in the Caatinga serve as ecological microrefugia and create exceptional wetlands within these dry forests, as runoff is largely directed down the inselberg slopes. Therefore, these environments are potentially important for the persistence of many species under increasing aridity. Additionally, the presence of abundant laticifers, common in Euphorbiaceae and confirmed for species of the genus Sapium , may contribute to the rapid sealing of injured tissues, reducing water loss through transpiration in wounds and offering a physical barrier in hot and dry environments (Demarco et al. 2013 ). Actinostemon appendiculatus is widely distributed in the Atlantic Forest, occurring from the state of Bahia to Paraíba in both dense and open seasonal and ombrophilous forests. This range of occurrence may explain the species' tendency toward greater resilience to climate change, given that, as discussed by Leão et al. ( 2021 ), widespread species tend to be less vulnerable, as they encounter favorable climatic conditions in different regions. On the other hand, A. bahiensis showed a different pattern. Despite its distribution restricted to the Atlantic Forest of Bahia and its preferential occurrence in open and dense ombrophilous forests, as well as in deciduous and semideciduous seasonal forests (Sátiro and Sales 2014 ), the species showed projections of significant expansion of suitable areas only under the most pessimistic climate scenario. This seemingly contradictory result may be related to changes in the availability of phytophysiognomies, since, according to the MMA ( 2018 ), most forest types in the Atlantic Forest are likely to lose climatic suitability in future scenarios, except for open ombrophilous forest and transition areas, which have potential for expansion. Therefore, the projected increase in areas of suitability for A. bahiensis should be interpreted with caution, as it is associated with specific habitat changes and not necessarily with greater safety for the species. Several studies have shown that, in certain cases, climate change can favor some plant species, expanding the areas considered environmentally suitable for their occurrence. One example of this is the study by Gülçin et al. ( 2021 ), which highlighted the likely expansion of potential areas for Carpinus betulus in Northern Europe under the new climate conditions. Meanwhile, in China, modeling for Magnolia officinalis indicated a significant increase in areas of high and medium suitability by the end of the 21st century, with projected increases of more than 300,000 km² under moderate and pessimistic scenarios (Ren et al. 2025 ). A similar trend was observed for species of the genus Epipactis (Orchidaceae) in Europe, where future suitability increased in more than half of the species studied, in addition to showing northward latitudinal shifts, accompanying changes in temperature regimes (Evans and Jacquemyn 2022 ). A similar trend was recorded for three specialist tree species associated with seasonally dry tropical forests (SDTFs) in Brazil, where modeling indicated an increase of approximately 18% in suitable areas by 2080, especially in the Midwestern and Northern regions of the country (Rodrigues et al. 2015 ). Meanwhile, the remaining taxa studied, that is, more than half of them, could be impacted in both scenarios. However, more intense and negative impacts on suitable habitats are expected for M. fistulifera subsp. bahiensis , O. pendunculare , M. heterodoxa , and S. jacobinensis , whose habitats will shrink by more than 45%. Similarly, Suarez-Contento et al. ( 2024 ) predicted a decrease in ranges for approximately half of the endemic species of the genus Manihot (Euphorbiaceae) in Northeastern Brazil. The authors also observed that most species are found in regions that are extremely fragmented and degraded by human action. Furthermore, most of these species occur in Chapada Diamantina, Bahia, an area predominantly characterized by rocky fields and Caatinga vegetation. For example, Microstachys revoluta is exclusive to the Sincorá mountain range (Esser 1998 ), and Stillingia loranthacea is restricted to the municipality of Morro do Chapéu (Athiê-Souza et al. 2014 ), while Microstachys uleana , in turn, grows from the south to the central portion of the Chapada (Pscheidt 2015 ). The rocky fields of Chapada Diamantina are high-altitude ecosystems with high endemism and a small continuous area, making them extremely vulnerable to climate change (Bugado et al. 2025 ). According to Bitencourt et al. ( 2016 ), this area will nearly disappear, losing more than 98% of its habitat due to climate change. Furthermore, it is currently highly threatened by deforestation for agricultural activities (Funch et al. 2005 , 2008 ), and between 2019 and 2021 it suffered the loss of more than 100,000 hectares of natural territory (Silva et al. 2023 ). According to Evans and Jacquemyn ( 2022 ), species with broader niche ranges (generalists) experience greater changes in habitat range in response to climate change than specialists. Similar studies have demonstrated a recurring pattern of reduced areas of climatic suitability for many Brazilian plant species. In the Brazilian semiarid region, Ceiba glaziovii , an endemic species of the Caatinga, showed significant losses of climatically suitable range in all scenarios analyzed, with the disappearance of areas of high suitability in more pessimistic scenarios (Almeida et al. 2024 ). Furthermore, in the Caatinga biome, other endemic cactus species, such as Brasilicereus phaeacanthus and Pereskia aureiflora , showed significant losses of climatically suitable range, and in future scenarios, these species face considerable challenges in maintaining their current distributions (Simões et al. 2019 ). Furthermore, in other specific biomes, such as the Cerrado, the genus Lessingianthus (Asteraceae), which comprises numerous threatened species, also showed significant reductions in its future distribution ranges in both optimistic and pessimistic scenarios for 2050 and 2070 (Angulo et al. 2021 ). Thus, these studies highlight both the intrinsic vulnerability of endemic and restricted species and the urgent need for robust conservation strategies, including the expansion of protected areas and the identification of climate refugia, to ensure the maintenance of plant biodiversity in the face of future climate change. Furthermore, these findings indicate the need to reassess the representativeness of protected areas, prioritizing both species with widespread distributions that are poorly protected and those with restricted distributions, even when currently well protected. Despite the identification of areas of high biodiversity value in the current scenario, future projections point to a significant reduction in these biodiversity hotspots. Furthermore, analysis of overlap with protected areas also reveals that, although some species may find partial refuge in already protected areas, current coverage is insufficient to ensure the maintenance of most potential habitats in the face of predicted severe climate change. Similar patterns are observed in other regions, indicating that, even with the expansion of protected areas, their capacity to guarantee suitable habitats may prove limited in the face of future climate conditions (Lombo-Sanchez et al. 2025 ). In this study, we found that nine taxa are considered within some threat category in both future scenarios, notably Stillingia loranthacea , which is restricted to a single municipality and in the projections showed a decline in its area of ​​suitability in both scenarios, in addition to going from the category of Least Concern (LC) to Vulnerable (VU). For the conservation of these taxa to be effective, it is necessary to create new Conservation Units in the areas of greatest richness and diversity, with emphasis on Chapada Diamantina and Sul Baiano, which presented the highest diversity indices, as well as in regions with extremely restricted species, such as Gradyana franciscana , as well as areas that are suitable refuges for wider species, such as the fragments of the East Northeast, which present a refuge for Actinostemon appendicullatus . A recent survey of biodiversity protection in Brazil's protected areas, covering vertebrates, arthropods, and angiosperms, indicates that, despite the country's exceptional biological wealth and its status as a global conservation priority, these areas still offer insufficient protection. Many endemic species and lineages remain unprotected, highlighting significant gaps in the coverage and effectiveness of currently established areas (Lopes, 2010). Although restricted species known only from type material ( Ophthalmoblapton parviflorum , Sebastiania trinervia , and Gradyana franciscana ) were not included in the distribution modeling, they are likely at high risk of threat due to their microendemism and extremely small populations (Qian & Qian, 2024 ). Furthermore, they are highly vulnerable to human impact. A striking example is Gradyana franciscana , recorded on the banks of the Lower São Francisco River, an area heavily impacted by human activity and subject to intense modifications of the riverside landscape, with consequent alterations to associated ecosystems (Araújo, 2015 ). Conclusion The study of endemic Euphorbioideae taxa in Northeastern Brazil highlights the importance of assessing their potential distribution, vulnerability, and adaptation in the face of climate change. The results, which indicate both gains and losses in suitable areas, reveal the complexity of climate impacts and the need to expand collections and population studies, especially for rare species underrepresented in scientific collections. Furthermore, the current configuration of Protected Areas (PAs) in Northeastern Brazil does not guarantee the conservation of the studied species against future climate change. Therefore, we emphasize the need for conservation strategies to protect biodiversity in Northeastern Brazil's ecosystems. Declarations Competing Interests The authors have no relevant financial or non-financial interests to disclose. Funding This work was supported by Fundação de Amparo à Ciência e Tecnologia de Pernambuco (BFP-0238-2.03/24) and (APQ-0995-2.03/21) and by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (405265/2021-2). Author Contribution All authors contributed to the concept and design of the article. Database compilation and preparation were carried out by J.C.R.M. & T.O. All analyses developed in the study were performed by T.O., K.Y.S.C., Y.J.L.S., and V.R.S.L. with supervision by S.M.A.S. Graphical production of the maps in QGIS was performed by T.O. The scope of this manuscript was written by T.O., A.M.T., and S.M.A.S., and the other authors contributed comments and suggestions throughout the writing process. All authors read and approved the result. Acknowledgments The authors would like to thank the Fundação de Amparo à Ciência e Tecnologia de Pernambuco (FACEPE) for awarding the first author a master's degree scholarship and the second author a postdoctoral scholarship (BFP-0238-2.03/24), and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (405265/2021-2), and FACEPE (APQ-0995-2.03/21) for financial support during herbarium visits. The authors would also like to thank the herbarium curators and technicians for their logistical support during the material analyses. References Agra MDF, Silva KN, Basílio IJLD, Freitas PFD, Barbosa-Filho JM (2008) Survey of medicinal plants used in the region Northeast of Brazil. Rev Bras Farmacogn 18:472–508. https://doi.org/10.1590/S0102-695X2008000300023 Allen K, Dupuy JM, Gei MG, Hulshof C, Medvigy D, Pizano C, Salgado-Negret B, Smith CM, Trierweiler A, Bloem SJV, Waring B, Xu X, Powers JS (2017) Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes? Environ Res Let 12(2):023001. https://doi.org/10.1088/1748-9326/aa5968 Almeida DM, Nogueira SS, Silva EA, Souza JMF, Gurchel ALC, Sousa AN (2024) Climate change is expected to reduce the potential distribution of Ceiba glaziovii in Caatinga, the largest area of dry tropical forest in South America. J Biosci 40:e40051. https://doi.org/10.14393/BJ-v40n0a2024-72663 Angulo MB, Via Do Pico G, Dematteis M (2021) Impact of climate change on the current and future distribution of threatened species of the genus Lessingianthus (Vernonieae: Asteraceae) from the Brazilian Cerrado. Acad Bras Cienc 93:e20190796. https://doi.org/10.1590/00013765202120190796 Amorim E, Fernandez E (2021) Algernonia bahiensis (Euphorbiaceae). Lista Vermelha da Flora Brasileira: Centro Nacional de Conservação da Flora/ Instituto de Pesquisas Jardim Botânico do Rio de Janeiro. https://proflora.jbrj.gov.br/html/Algernonia%20bahiensis_2021.htmlh (accessed September 2024) Andrade EM, Aquino DN, Chaves LCG, Lopes FB (2017) Water as capital and its uses in the Caatinga. In: Silva JMC, Leal IR, Tabarelli M (eds) Caatinga - The largest tropical dry forest region in South America. Springer, Cham, pp 281–302 Araújo MB, Williams PH (2000) Selecting areas for species persistence using occurrence data. Biol Conserv 96:331–345. https://doi.org/10.1016/S0006-3207(00)00074-4 Araújo SS (2015) Apropriação dos recursos naturais e conflitos socioambientais no Baixo São Francisco em Sergipe e Alagoas. Thesis, Universidade Federal de Sergipe. https://ri.ufs.br/jspui/handle/123456789/4041 Araujo HFP (2023) Human disturbance is the major driver of vegetation changes in the Caatinga dry forest region. Sci Rep 13:18440 Athiê-Souza SM, Melo AL, Silva MJ, Sales MF (2014) Reinstatement and Lectotypification of Stillingia loranthacea (Euphorbiaceae), a Vulnerable Species from Chapada Diamantina, Bahia (Brazil), and a New Circumscription of Stillingia saxatilis. Syst Bot. 39:510–516. https://doi.org/10.1600/036364414X680915 Athiê-Souza SM, Melo AL, Silva MJ, Oliveira LSD, Sales MF (2015) Gradyana (Euphorbiaceae): A New Genus from Northeastern Brazil. Syst Bot 40:527–533. https://doi.org/10.1600/036364415X688781 Bitencourt C, Rapini A, Damascena LS, Junior PDM (2016) The worrying future of the endemic flora of a tropical mountain range under climate change. Flora: Morphol Distrib Funct Ecol Plants 218:1–10. https://doi.org/10.1016/j.flora.2015.11.001 Bongers FJ, Olmo M, Lopez-Iglesias B, Anten NPR, Villar RJPB (2017) Drought responses, phenotypic plasticity and survival of Mediterranean species in two different microclimatic sites. Plant Biol 19:386–395 Booth TH, Nix HA, Busby JR, Hutchinson MF (2014) BIOCLIM: the first species distribution modelling package, its early applications and relevance to most current MAXENT studies. Divers distrib 20:1–9 Boria RA, Olson LE, Goodman SM, Anderson RP (2014) Spatial filtering to reduce sampling bias can improve the performance of ecological niche models. Ecol Model 275:73–77. https://doi.org/10.1016/j. ecolmodel.2013.12.012 Boria RA, Olson LE, Goodman SM, Anderson RP (2016) A single-algorithm ensemble approach to estimating suitability and uncertainty: cross-time projections for four Malagasy tenrecs. Divers distrib 23:196–208. https://doi.org/10.1111/ddi.12510 Boucher O, Servonnat J, Albright AL, Aumont O, Balkanski Y, Bastrikov V, Bekki S, Bonnet R, Bony S, Bopp L, Braconnot P, Brockmann P, Cadule P, Caubel A, Cheruy F, Codron F, Cozic A, Cugnet D, D’Andrea F, Davini P, de Lavergne C, Denvil S, Deshayes J, Devilliers M, Ducharne A, Dufresne JL, Dupont E, Éthé C, Fairhead L, Falletti L (2020) Presentation and Evaluation of the IPSL-CM6A-LR Climate Model. J Adv Model Earth Syst 12(7): e2019MS002010. https://doi.org/10.1029/2019MS002010 Bugado RE, Shrestha N, Magri RA, Prado J, Lopes JC (2025) Vanishing ecosystems: The looming threat of climate change on an iconic genus Vellozia in the Brazilian campos rupestres. Glob Ecol Conserv 58:e03439. https://doi.org/10.1016/j.gecco.2025.e03439 Bullong JRT, Silverio JP, Alafag JI et al (2024) Development of endemicity and conservation importance indices for tropical forests and the floral diversity assessment of Mt. Natoo Benguet Philippines JMS 21:786–804. https://doi.org/10.1007/s11629-023-8387-9 Cavalcante AMB, Fernandes PHC, Silva EM (2020) Opuntia ficus-indica (L.) Mill. e as Mudanças Climáticas: Uma Análise a Luz da Modelagem de Distribuição de Espécies no Bioma Caatinga. Rev bras meteorol 35: 375–385. https://doi.org/10.1590/0102-7786353001 Cherchi A, Fogli PG, Lovato T, Peano D, Iovino D, Gualdi S, Masina S, Scoccimarro E, Materia S, Belluci A, Navarra A (2019) Global Mean Climate and Main Patterns of Variability in the CMCC-CM2 Coupled Model. J Adv Model Earth Syst 11:185–209. https://doi.org/10.1029/2018MS001369 Cobos ME, Peterson AT, Barve N, Osorio-Olvera L (2019) Kuenm: An R package for detailed development of ecological niche models using Maxent. PeerJ 7:e6281. https://doi.org/10.7717/peerj.6281 Cordeiro WDS, Melo AD, Athiê-Souza SM, Esser HJ, Sales MD (2018) Reinstatement of Sapium sceleratum (Euphorbiaceae), an endemic species from Northeast Brazil, and new circumscription of Sapium argutum . Phytotaxa, 348: 23–31 Costa SL, Louzada RB, Nepomuceno SC, Alves JV, Buril MT (2024) Distribution pattern in the rupiculous genus Orthophytum (Bromelioideae/Bromeliaceae) reveals high microendemicity in different types of rocky outcrops. Braz Acad Sci 96(2). https://doi.org/10.1590/0001-3765202420230007 Diniz-Filho JAF, Bini LM, Rangel TF, Loyola RD, Hof C, Nogués-Bravo D, Araújo MB (2009) Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change. Ecography. 32:897–906. https://doi.org/10.1111/j.1600-0587.2009.06196.x Demarco D, de Moraes Castro M, Ascensão L (2013) Two laticifer systems in Sapium haematospermum —new records for Euphorbiaceae. Botany 91:545–554. https://doi.org/10.1139/cjb-2012-0277 Duarte LDS et al (2019) Species distribution models for Atlantic Forest plants: advances and challenges. Perspect Ecol Conserv 17:1–10 Echternacht L, Trovó M, Oliveira CT, Pirani JR (2011) Areas of endemism in the Espinhaço Range in Minas Gerais, Brazil. Flora 206:782–791. https://doi.org/10.1016/j.flora.2011.04.003 Elewa AMT, Abdelhady AA (2020) Past, present, and future mass extinctions. J Afr Earth Sci 162:1–16. https://doi.org/10.1016/j.jafrearsci.2019.103678 Esser HJ (1998) New combinations in Microstachys (Euphorbiaceae). Kew Bull 955–960 Esser HJ (2012) The tribe Hippomaneae (Euphorbiaceae) in Brazil. Rodriguésia 63:209–225. https://doi.org/10.1590/S2175-78602012000100013 Evans A, Jacquemyn H (2022) Range size and niche breadth as predictors of climate-induced habitat change in Epipactis (Orchidaceae). Front Ecol Evol 10:894616 Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE (2016) Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci Model Dev 9:1937–1958. https://doi.org/10.5194/gmd-9-1937-2016 Fernandez E, Moraes M (2020) Stillingia loranthacea (Euphorbiaceae). Lista Vermelha da Flora Brasileira: Centro Nacional de Conservação da Flora/ Instituto de Pesquisas Jardim Botânico do Rio de Janeiro. https://proflora.jbrj.gov.br/html/Stillingia%20loranthacea_2020.htmlax (accessed September 2024) Fernandez E, Rosa P (2018) ) Ophthalmoblapton pedunculare (Euphorbiaceae). Lista Vermelha da Flora Brasileira: Centro Nacional de Conservação da Flora/ Instituto de Pesquisas Jardim Botânico do Rio de Janeiro. https://proflora.jbrj.gov.br/html/Ophthalmoblapton%20pedunculare_2018.html (accessed September 2024) Fick SE, Hijmans RJ (2017) WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol 37:4302–4315. https://doi.org/10.1002/joc.5086 Funch LS, Funch RR, Harley R, Giulietti AM, Queiroz LP, França F, Melo E, Gonçalves CN, Santos T (2005) Florestas estacionais semideciduais. In: Juncá FA, Funch L, Rocha W (eds) Biodiversidade e conservação da Chapada Diamantina. Ministério do Meio Ambiente, Brasília, pp 181–193 Funch LS, Rodal MJN, Funch RR (2008) Floristic aspects of the forests of the Chapada Diamantina, Bahia, Brazil. In: Thomas W, Briton EG (ed) The Atlantic Coastal Forest of Northeastern Brazil. Mem. of the New York Botanical Garden Press 100: 193–220 García-Saldaña EA, Cerqueda-García D, Ibarra-Laclette E, Aluja M (2024) Insights into the differences related to the resistance mechanisms to the highly toxic fruit Hippomane mancinella (Malpighiales: Euphorbiaceae) between the larvae of the sister species Anastrepha acris and Anastrepha ludens (Diptera: Tephritidae) through comparative transcriptomics. Front Physiol 15:1263475 Guerra NB, Sant’Ana Pegorin G, Boratto MH, de Barros NR, de Oliveira Graeff CF, Herculano RD (2021) Biomedical applications of natural rubber latex from the rubber tree Hevea brasiliensis . Mater Sci Eng C 126:112126. https://doi.org/10.1016/j.msec.2021.112126 Gülçin D, Arslan ES, Örücü, Öme K (2021) Effects of climate change on the ecological niche of common hornbeam ( Carpinus betulus L). Ecol Inf 66:101478. https://doi.org/10.1016/j.ecoinf.2021.101478 Harley RM (1995) Introdução. In: Stannard BL (ed) Flora of the Pico das Almas, Chapada Diamantina, Bahia, Brasil. Royal Botanic Gardens, Kew, pp 43–78 Heming N, Dambros C, Gutiérrez E (2019) NM/ENMwizard: Advanced Techniques for Ecological Niche Modeling Made Easy . Available from https://github.com/HemingNM/ENMwizard Hernandez PA, Graham CH, Master LL, Albert DL (2006) The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 29:773–785. https://doi.org/10.1111/j.0906-7590.2006.04700.x Hijmans RJ (2012) Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model. Ecology 93:679–688. https://doi.org/10.1890/11-0826.1 Hodnebrog Ø, Steensen BM, Marelle L, Alterskjær K, Dalsøren SB, Myhre G (2022) Understanding model diversity in future precipitation projections for South America. Clim Dyn 58:1329–1347. https://doi.org/10.1007/s00382-021-05964-w INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA (IBGE) (2006) Regiões, mesorregiões geográficas do Brasil. 34, Brasília, 62p IPCC (2023) Summary for Policymakers. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds)] IPCC, Geneva, Switzerland, pp. 1–34. https://doi.org/10.59327/IPCC/AR6-9789291691647.001 IUCN Standards and Petitions Committee (2024) Guidelines for Using the IUCN Red List Categories and Criteria. Version 16. Prepared by the Standards and Petitions Committee. https://www.iucnredlist.org/documents/RedListGuidelines.pdf Leão TCC, Reinhardt JR, Nic Lughadha E, Reich PB (2021) Projected impacts of climate and land use changes on the habitat of Atlantic Forest plants in Brazil. Glob Ecol Biogeogr 30:2016–2028. https://doi.org/10.1111/geb.13365 Leal IR, Da-Silva JMC, Tabarelli M, Lacher TE (2005) Changing the course of biodiversity conservation in the Caatinga of northeastern Brazil. Biol Conserv 19:701–706. https://doi.org/10.1111/j.1523-1739.2005.00703.x Lopes RV (2010) As espécies ameaçadas da Flora brasileira e o Sistema Nacional de Unidades de Conservação (SNUC): uma abordagem preliminar do caso do bioma Cerrado. In: Diniz R et al (eds) Cerrado-Conhecimento científico quantitativo como subsídio para ações de conservação. Brazil; Conservação International, pp 35–88 Lombo-Sanchez YJ, Suarez-Contento KY, Silva MPP, Pôrto KC (2025) Liverworts in a changing world: Vulnerability and extinction risk of specialist species under climate change in a tropical country (Colombia). Nat Conserv Res 10(3):34–53. https://dx.doi.org/10.24189/ncr.2025.016 Manes S et al (2021) Endemism increases species’ climate change risk in areas of global biodiversity importance. Biol Conserv 257:109070. https://doi.org/10.1016/j.biocon.2021.109070 MMA (2018) Impacto das mudanças do clima na Mata Atlântica. Brasília. Available at: https://www.gov.br/mma/pt-br/assuntos/ecossistemas/biomas/arquivos-biomas/impactos-da-mudanca-do-clima-na-mata-atlantica.pdf . (accessed December 2024) Marengo JA, Torres RR, Alves LM (2017) Drought in Northeast Brazil – past, present and future. Theor Appl Climatol 129:1189–1200. https://doi.org/10.1007/s00704-016-1840-8 Moura MR, Oliveira GA, Paglia AP, Pires MM, Santos BA (2023) Climate change should drive mammal defaunation in tropical dry forests. Glob Chang Biol 29:6931–6944. https://doi.org/10.1111/gcb.16979 Mota FMM, Alves-Ferreira G, Talora DC, Heming NM (2023) divraster: an R package to calculate taxonomic, functional and phylogenetic diversity from rasters. Ecography, 2023(12), e06905 Oliveira LSD (2010) Considerações filogenéticas e taxonômicas na tribo Hureae Dumort. (Euphorbioideae - Euphorbiaceae). Thesis, Universidade Federal Rural de Pernambuco. https://bdtd.ibict.br/vufind/Record/URPE_2cdcc75c11631d7526f1d99e4e5b226e Pautasso M, Döring TF, Garbelotto M, Pellis L, Jeger MJ (2012) Impacts of climate change on plant diseases—opinions and trends. Eur J Plant Pathol 133:295–313. https://doi.org/10.1007/s10658-012-9936-1 PBMC (2013) Sumário Executivo do Volume 1 – Base Científica das Mudanças Climáticas. Contribuição do Grupo de Trabalho 1 para o 1° Relatório de Avaliação Nacional do Painel Brasileiro de Mudanças Climáticas. COPPE/UFRJ, Rio de Janeiro Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259 Phillips SJ, Anderson RP, Dudík M, Schapire RE, Blair ME (2017) Opening the black box: an open-source release of Maxent. Ecography 40:887–893. https://doi.org/10.1111/ecog.03049 Pillet et al (2022) Elevated extinction risk of cacti under climate change. Nat Plants 8:366–372. https://doi.org/10.1038/s41477-022-01130-0 Pomoim N, Hughes AC, Trisurat Y, Corlett RT (2022) Vulnerability to climate change of species in protected areas in Thailand. Sci Rep 12:5705. https://doi.org/10.1038/s41598-022-09767-9 Pscheidt AC (2015) O gênero Microstachys A. Juss. e a tribo Hippomaneae (Euphorbiaceae). Thesis, Universidade de São Paulo, 258p. smastr16.blob.core.windows.net/pgibt/2018/05/pscheidt_2015.pdf Qazi AW, Saqib Z, Zaman-ul-Haq M (2022) Trends in species distribution modelling in context of rare and endemic plants: a systematic review. Ecol Process 11:40. https://doi.org/10.1186/s13717-022-00384-y Qian H, Qian S (2024) Global patterns of taxonomic and phylogenetic endemism in liverwort assemblages. Plant Divers 47:82–88. https://doi.org/10.1016/j.pld.2024.08.004 Ramos LFS, de Sousa AG, de Siqueira Amorim R, de Araújo Roque A, Carvalho ILD, de Carvalho ALV, Santos ME, Marques MB, Lima LRA, Costa MJF, Sette-de-Souza PH (2024) Ethnobotanical surveys of plants used by Quilombola communities in Brazil: A scoping review. Life 14(10):1215 Ren J, Li S, Zhang Y, Yang Q, Liu J, Fan J, Xiang Y (2025) MaxEnt-based evaluation of climate change effects on the habitat suitability of Magnolia officinalis in China. Front Plant Sci 16:1601585 Rizzini CT (1963) Nota prévia sobre a divisão fitogeográfica (florístico-sociológica) do Brasil. RBG 25:3–64 Rodrigues PMS, Silva JO, Eisenlohr PV, Schaefer CEGR (2015) Climate change effects on the geographic distribution of specialist tree species of the Brazilian tropical dry forests. Braz J Biol 75:679–684 Sátiro LR, Sales MF (2014) Algernonia bahiensis (Euphorbiaceae), a new species from Bahia, Brazil. Phytotaxa 156:285–290 Sánchez-Tapia A, Mortara SR, Bezerra Rocha DS, Mendes Barros FS, Gall G, de Siqueira MF (2020) modleR: a modular workflow to perform ecological niche modeling in R. BioRxiv, 2020-04. https://doi.org/10.1101/2020.04.01.021105 Scafetta N (2023) CMIP6 GCM ensemble members versus global surface temperatures. Clim Dyns 60:3091–3120. https://doi.org/10.1007/s00382-022-06493-w Schmidt JJ (2021) Glacial Deaths, Geologic Extinction. Environ Humanit 13:2. https://doi.org/10.1215/22011919-9320156 Silva EM, Rocha WJSF, Souza DTM, Costa DP, Duverger SG (2023) O processo de desmatamento do bioma Caatinga na Chapada Diamantina-BA (2019–2021) In: Anais do XX Simpósio Brasileiro de Sensoriamento Remoto. IMPE, Florianópolis, pp 3040–3043 Silva JLS, Cruz-Neto O, Peres CA, Tabarelli M, Lopes AV (2019) Climate change will reduce suitable Caatinga dry forest habitat for endemic plants with disproportionate impacts on specialized reproductive strategies. PLoS ONE 14(5):e0217028. https://doi.org/10.1371/journal.pone.0217028 Silva LMB, Loureiro B (2024) Properties and medical applications of the Euphorbiaceae family and their bioproducts: a patent review. Naunyn-schmiedeberg's Arch Pharmacol Simões SS, Zappi D, Costa GM, Oliveira G, Aona LYS (2019) Spatial niche modelling of five endemic cacti from the Brazilian Caatinga: Past, present and future. Austral Ecol 45:35–47. https://doi.org/10.1111/aec.12825 Siqueira MF, Durigan G (2007) Modeling geographic distribution of Cerrado woddy species in São Paulo State. Rev Brasil Bot 30:233–243. https://doi.org/10.1590/S0100-84042007000200008 Souza BM, Tonini TRT, Rocha EA (2018) Environmental characterization of rural properties in Serra Bonita Particular Reserve of the Natural Heritage. Camacan Bahia SODEBRAS 13:93–97. https://doi.org/10.29367/issn.1809-3957.2018.151 Souza TAD, Alves AF, Lira ND, Cibulski SP, Pereira LH, Abreu LS, Tavares JF, Scotti MT, Silva MSD (2025a) Chemotaxonomic Analysis of Diterpenes in Four Euphorbiaceae Genera: A Path to New Cytotoxic Agents. J Braz Chem Soc 36(7):e–20250061 Souza BID, Lunguinho RL, Xavier RA, Queiroz RTD, Medeiros JRD, Cardoso ECM, Maciel MGR, Neto IOB, Santos LJC, Souza JJLLS, Cordeiro JMP (2025b) Rainwater runoff, soil, and vegetation interactions in inselbergs provide microrefugia in Brazil’s Caatinga drylands. Environ Monit Assess 197:772 Suarez-Contento KY, Teles CB, Alves-Ferreira G, Martins MLL, Athiê-Souza SM (2024) Projected effects of climate change on the potential distribution range of Manihot species endemic to Northeast Brazil Annals of Brazilian Academy of Science 96. 1. https://doi.org/10.1590/0001-3765202420231211 Thiers B (2025) [continuously updated]) Index Herbariorum: A global directory of public herbaria and associated staff. New York Botanical Garden’s Virtual Herbarium, New York. Available from: http://sweetgum.nybg.org/ih/ (accessed March 2025) UNEP-WCMC and ShareAction (2024) Risk Management in Protected Areas. UN Environment Programme World Conservation Monitoring Centre, Cambridge, UK Vasconcelos RN, Cantillo-Pérez T, Franca Rocha WJ, Aguiar WM, Mendes DT, de Jesus Santana CO, Santana MM, Oliveira RP (2024) Advances and Challenges in Species Ecological Niche Modeling: A Mixed Review. Earth 5:963–989 Vaz AF, Costa RM, Melo AM, Oliva ML, Santana LA, Silva-Lucca RA, Coelho LCBB, Correia MT (2010) Biocontrol of Fusarium species by a novel lectin with low ecotoxicity isolated from Sebastiania jacobinensis . Food Chem 119:1507–1513 Zhao et al (2021) Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study. Lancet Planet Health 2021; 5: e415–25. https://doi.org/10.1016/S2542-5196(21)00081-4 Williams KD, Copsey D, Blockley EW, Bodas-Salcedo A, Calvert D, Comer R, Davis P, Graham T, Hewitt HT, Hill R, Hyder P, Ineson S, Johns TC, Keen AB, Lee RW, Megann A, Milton SF, Rae JGL, Roberts MJ, Scaife AA, Schiemann R, Storkey D, Thorpe, Watterson IG, Walters DN, West A, Wood RA, Woollings T, Xavier PK (2018) The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations. J Adv Model Earth Syst 10:357–380. https://doi.org/10.1002/2017MS001115 Wisz MS, Hijmans RJ, Li J, Peterson AT, Graham CH, Guisan A, Elith J, Dudík M, Ferrier S, Huettmann F, Leathwick JR, Lehmann A, Lohmann L, Loiselle BA, Manion G, Moritz C, Nakamura M, Nakazawa Y, Overton JMC, Phillips SJ, Richardson KS, Scachetti-Pereira R, Schapire RE, Soberón J, Williams SE, Zimmermann NE (2008) Effects of sample size on the performance of species distribution models. Divers distrib 14:763–773. https://doi.org/10.1111/j.1472-4642.2008.00482.x Wu T, Yu R, Lu Y, Jie W, Fang Y, Zhang J, Zhang L, Xin X, Li L, Wang Z, Liu Y, Zhang F, Wu F, Chu M, Li J, Li W, Zhang Y, Shi X, Zhou W, Yao J, Liu X, Zhao H, Yan J, Wei M, Xue W, Huang A, Shu Q, Hu A (2021) BCC-CSM2-HR: A high-resolution version of the Beijing Climate Center Climate System Model. Geosci Model Dev 14:2977–3006. https://doi.org/10.5194/gmd-14-2977-2021 Wurdack KJ, Hoffmann P, Chase MW (2005) Molecular phylogenetic analysis of uniovulate Euphorbiaceae (Euphorbiaceae sensu stricto) using plastid rbcL and trnL-F DNA sequences. Am J Bot 92:1397–1420. https://doi.org/10.3732/ajb.92.8.1397 Zelinka MD, Myers TA, McCoy DT, Po-Chedley S, Caldwell PM, Ceppi P, Klein SA, Taylor KE (2020) Causes of higher climate sensitivity in CMIP6 models. Geophys Res Lett 47(1): e2019GL085782. https://doi.org/10.1029/2019GL085782 Additional Declarations No competing interests reported. Supplementary Files Supplementarydata.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 01 Apr, 2026 Reviews received at journal 28 Jan, 2026 Reviewers agreed at journal 19 Jan, 2026 Reviews received at journal 13 Jan, 2026 Reviewers agreed at journal 12 Jan, 2026 Reviews received at journal 18 Dec, 2025 Reviewers agreed at journal 01 Dec, 2025 Reviewers agreed at journal 01 Dec, 2025 Reviewers invited by journal 01 Dec, 2025 Editor assigned by journal 23 Oct, 2025 Submission checks completed at journal 10 Oct, 2025 First submitted to journal 04 Oct, 2025 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7781649","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":554177680,"identity":"d834ca8d-3cfb-4490-971f-87b0896e9fa0","order_by":0,"name":"Tiago Oliveira","email":"","orcid":"","institution":"Universidade Federal Rural de Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Tiago","middleName":"","lastName":"Oliveira","suffix":""},{"id":554177681,"identity":"ab345f9f-a275-4331-bd42-402ec7f32a58","order_by":1,"name":"Yeison Jaroc Lombo-Sanchez","email":"","orcid":"","institution":"Universidade Federal de Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Yeison","middleName":"Jaroc","lastName":"Lombo-Sanchez","suffix":""},{"id":554177682,"identity":"b8757f30-bfc5-41cd-9bcb-a0f8c1e9613d","order_by":2,"name":"Karen Yuliana Suarez-Contento","email":"","orcid":"","institution":"Universidade Federal Rural de Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Karen","middleName":"Yuliana","lastName":"Suarez-Contento","suffix":""},{"id":554177683,"identity":"692e9a7d-07d6-478f-adc9-ab35d7a74d9c","order_by":3,"name":"Alícia Marques Torres","email":"","orcid":"","institution":"Universidade Federal Rural de Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Alícia","middleName":"Marques","lastName":"Torres","suffix":""},{"id":554177684,"identity":"8245e766-35e4-46bf-b501-db7010865ae7","order_by":4,"name":"Jone Clebson Ribeiro Mendes","email":"","orcid":"","institution":"Universidade Federal Rural de Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Jone","middleName":"Clebson Ribeiro","lastName":"Mendes","suffix":""},{"id":554177685,"identity":"741446cc-27dc-48aa-bfed-f66877581a7a","order_by":5,"name":"Vitória Raquel Silva Lima","email":"","orcid":"","institution":"Universidade Federal Rural de Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Vitória","middleName":"Raquel Silva","lastName":"Lima","suffix":""},{"id":554177686,"identity":"d8684769-46d1-4a2b-85f8-933fe01cdb04","order_by":6,"name":"Sarah Maria Athiê-Souza","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYJACZijN+IDBBkTzEK+F2YAhjUQtbBJEaZFvP/vwcwFDnZzB+cPPqnkS7uXxM/Ae+4BPi8GZdGPpGQyHjQ0OHDO7zZNQXCzZwJc8A68WoFukeRgOJG442GB2m/dHQuKGAzzG+B3W/4z5Nw9DXeKGw+zfinkSEhL3E9LCcCONDWgLc+KGYzxmzCAtGxgIaDG48YzNmsfgsLHkGZ5iyTkJCcUSh/mSCTgsjfk2T0WdHN/54xs/vElIyONv7z2M32EQuxDMBHg0EQ0SSNUwCkbBKBgFwx8AALZGQOtTwQj5AAAAAElFTkSuQmCC","orcid":"","institution":"Universidade Federal Rural de Pernambuco","correspondingAuthor":true,"prefix":"","firstName":"Sarah","middleName":"Maria","lastName":"Athiê-Souza","suffix":""}],"badges":[],"createdAt":"2025-10-04 19:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7781649/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7781649/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97473502,"identity":"e62ab27f-49f1-42e2-9f22-7b92e6da8330","added_by":"auto","created_at":"2025-12-04 18:16:43","extension":"tiff","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":34789730,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/59d332044aa7540bb28dddc6.tiff"},{"id":97670398,"identity":"0037ece5-e336-4ed8-aa48-43854d089540","added_by":"auto","created_at":"2025-12-08 09:30:32","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4247790,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA03OCT25MANUSCRIPT.docx","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/b92fdd605c7796d7c5f7caf8.docx"},{"id":97473504,"identity":"540c925d-c655-4aef-a857-fc4d677b5239","added_by":"auto","created_at":"2025-12-04 18:16:43","extension":"tiff","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":34789730,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.2.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/802f4ecb9c19db94a45543b2.tiff"},{"id":97669540,"identity":"5dee695e-70ab-405b-b7ae-b8ee9a893143","added_by":"auto","created_at":"2025-12-08 09:28:09","extension":"tiff","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":7996234,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.3.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/aa118385266dc6d5325885a3.tiff"},{"id":97669927,"identity":"c8fd9ba0-fe33-4795-b995-5a4881a6bb94","added_by":"auto","created_at":"2025-12-08 09:29:24","extension":"tiff","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11994242,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.4.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/b36f2d7438d7575631453dd3.tiff"},{"id":97473496,"identity":"ac209f1c-ca7d-4360-a57e-ed0a4ef50888","added_by":"auto","created_at":"2025-12-04 18:16:42","extension":"tiff","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5997234,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.5.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/1966c5bc1f310f87ac6dc392.tiff"},{"id":97670418,"identity":"983f39c3-d300-4530-ae55-b3f96858f9d3","added_by":"auto","created_at":"2025-12-08 09:30:36","extension":"tiff","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2782442,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.6.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/8dad3f42ac73c9f1ff110ea1.tiff"},{"id":97670284,"identity":"9a1d79c2-5e3b-40be-90f1-4dc1e36f2258","added_by":"auto","created_at":"2025-12-08 09:30:10","extension":"json","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8624,"visible":true,"origin":"","legend":"","description":"","filename":"4dc30529341f43d28f750e33cf7a8e41.json","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/863c6bae1ff932e9c63031c6.json"},{"id":97473492,"identity":"d95f83fc-6240-4d79-b26e-9b65409b7b76","added_by":"auto","created_at":"2025-12-04 18:16:42","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":17085,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydata.docx","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/fa1329a7aca1243a7034edf2.docx"},{"id":97669043,"identity":"0eb878ab-a6b9-4cdd-9ff8-0c8fdcb6f680","added_by":"auto","created_at":"2025-12-08 09:27:08","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":211448,"visible":true,"origin":"","legend":"","description":"","filename":"4dc30529341f43d28f750e33cf7a8e411enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/68a00fa2a08e8a9810e97e0a.xml"},{"id":97473511,"identity":"e2ae6f34-6ed2-45b1-8ab4-ae9e67f2b4ae","added_by":"auto","created_at":"2025-12-04 18:16:43","extension":"tiff","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":34789730,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/1ff208512771b4399df74a99.tiff"},{"id":97670596,"identity":"d0378e06-ed8f-4cd4-b36a-ffc1b015fb55","added_by":"auto","created_at":"2025-12-08 09:31:00","extension":"tiff","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":34789730,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.2.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/3ebc656735e66124ecb3d3e3.tiff"},{"id":97669352,"identity":"9eab0b21-bd2c-4dcd-9353-05fa57e9acb5","added_by":"auto","created_at":"2025-12-08 09:27:50","extension":"tiff","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":7996234,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.3.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/e7f1c64f1f2404b3e43db99e.tiff"},{"id":97473507,"identity":"1c513624-cc73-45b8-af7c-70087bb21269","added_by":"auto","created_at":"2025-12-04 18:16:43","extension":"tiff","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11994242,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.4.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/3e25a9efc24d11806d0deefc.tiff"},{"id":97670209,"identity":"d892ff12-0659-4fef-aec8-f3a80ccfc568","added_by":"auto","created_at":"2025-12-08 09:29:54","extension":"tiff","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5997234,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.5.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/e78ed56ea9e4a86c445aedf5.tiff"},{"id":97473509,"identity":"907f271c-6c10-41fc-a8a4-04ee7c43fc75","added_by":"auto","created_at":"2025-12-04 18:16:43","extension":"tiff","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2782442,"visible":true,"origin":"","legend":"","description":"","filename":"OLIVEIRA01OCT25Fig.6.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/a33c46045fc7d716b3f69c91.tiff"},{"id":97473490,"identity":"622b1e4c-41a7-48ab-b994-e787b54ea4d8","added_by":"auto","created_at":"2025-12-04 18:16:42","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":465052,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineOLIVEIRA01OCT25Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/50a9a2ad2d9f7aaad3179dd4.png"},{"id":97669767,"identity":"d4f435c3-8ac8-498a-bdf3-02ce0eb59c06","added_by":"auto","created_at":"2025-12-08 09:28:51","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":536702,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineOLIVEIRA01OCT25Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/aa874ab21db87a4b414c4f0e.png"},{"id":97669240,"identity":"94d4c1b8-5a00-4a7d-b538-c427d70b5f07","added_by":"auto","created_at":"2025-12-08 09:27:39","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":72339,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineOLIVEIRA01OCT25Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/1c6d80aa4e982fa2cb4ea089.png"},{"id":97473500,"identity":"3809a3ee-38fd-48e1-b64f-f6512d84c7f3","added_by":"auto","created_at":"2025-12-04 18:16:43","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":67991,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineOLIVEIRA01OCT25Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/7828b5cd1102f87b6f6b0ef7.png"},{"id":97473499,"identity":"49a1238d-1260-4e39-ac8c-4590413447d0","added_by":"auto","created_at":"2025-12-04 18:16:43","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":163904,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineOLIVEIRA01OCT25Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/590c7d8fa3ad783022749644.png"},{"id":97473493,"identity":"dd50f5af-9e08-4270-8157-5a4a07879829","added_by":"auto","created_at":"2025-12-04 18:16:42","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":23784,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineOLIVEIRA01OCT25Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/4606e3bfe948caeb98940530.png"},{"id":97669121,"identity":"ddd8d435-2668-484f-ae3c-d3fd860aadf9","added_by":"auto","created_at":"2025-12-08 09:27:17","extension":"xml","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":209586,"visible":true,"origin":"","legend":"","description":"","filename":"4dc30529341f43d28f750e33cf7a8e411structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/3ea6712d33ff26fe0405badd.xml"},{"id":97668951,"identity":"12af5974-5646-4962-a199-9df3c77e9fc7","added_by":"auto","created_at":"2025-12-08 09:26:47","extension":"html","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":219944,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/54f7477e92d4296a8edcd8ef.html"},{"id":97669230,"identity":"4ad1b956-d81c-4513-8a56-9f9a892ac0af","added_by":"auto","created_at":"2025-12-08 09:27:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":203240,"visible":true,"origin":"","legend":"\u003cp\u003eConsensus models of potential distribution for \u003cem\u003eActinostemon appendiculatus, Algernonia bahiensis, Mabea fistulifera \u003c/em\u003esubsp.\u003cem\u003ebahiensis, Microstachys heterodoxa, Microstachys revoluta \u003c/em\u003eand \u003cem\u003eMicrostachys uleana \u003c/em\u003eprojected for Northeastern Brazil under three climate scenarios: current (Current), optimistic (SSP126), and pessimistic (SSP585). The color scale represents the climate suitability per pixel, ranging from 0 (light green) to ≥ 0.9 (dark red)\u003c/p\u003e","description":"","filename":"OLIVEIRA01OCT25Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/e8e5dbab09181d5100d05156.png"},{"id":97473513,"identity":"2e20cd76-73df-405e-9261-3a693dbd2b38","added_by":"auto","created_at":"2025-12-04 18:16:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":672200,"visible":true,"origin":"","legend":"\u003cp\u003eConsensus models of potential distribution of \u003cem\u003eOphthalmoblapton pedunculare, Sapium sceleratum, Sebastiania jacobinensis, Sebastiania macrocarpa, Stillingia loranthacea \u003c/em\u003eand \u003cem\u003eStillingia trapezoidea \u003c/em\u003eprojected for Northeastern Brazil under three climate scenarios: current (Current), optimistic (SSP126), and pessimistic (SSP585). The color scale represents the climate suitability per pixel, ranging from 0 (light green) to ≥ 0.9 (dark red)\u003c/p\u003e","description":"","filename":"OLIVEIRA01OCT25Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/8914282e2eafcc74d74aab23.png"},{"id":97473485,"identity":"102b27e6-db61-426a-a215-368b87bc5401","added_by":"auto","created_at":"2025-12-04 18:16:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1513864,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of loss and gain of environmental suitability area for endemic species under different climate scenarios: A = optimistic (SSP126); B = pessimistic (SSP585)\u003c/p\u003e","description":"","filename":"OLIVEIRA01OCT25Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/a632e530bb49d9407846ede8.png"},{"id":97473483,"identity":"4aea91d5-ce38-4eb5-80b1-31810d91f1b7","added_by":"auto","created_at":"2025-12-04 18:16:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2286166,"visible":true,"origin":"","legend":"\u003cp\u003eTotal area of ​​environmental suitability (represented by the size of the circles) and percentage of overlap with protected areas (color scale) for 12 species under three climate scenarios: current, SSP126 (optimistic), and SSP585 (pessimistic). Red and orange circles indicate a high proportion of protected habitat (above 30%), while green shades represent low protection (less than 20%)\u003c/p\u003e","description":"","filename":"OLIVEIRA01OCT25Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/7adbc3d6d29979f3f2ff88e1.png"},{"id":97473488,"identity":"5fcafeb8-1c57-49b7-baa0-cd7893ad95c0","added_by":"auto","created_at":"2025-12-04 18:16:42","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5574706,"visible":true,"origin":"","legend":"\u003cp\u003eProjected species richness distribution for Northeastern Brazil under three climate scenarios: current (Current), optimistic (SSP126), and pessimistic (SSP585). The color scale represents the number of species (SR) with climatic suitability per pixel, ranging from 0 (light green) to ≥5 (dark red). Blue contours indicate protected areas\u003c/p\u003e","description":"","filename":"OLIVEIRA01OCT25Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/e0c393eb6c36328a95a6117f.png"},{"id":97473487,"identity":"0a00014b-f36d-4d59-86e9-6c2027c9c940","added_by":"auto","created_at":"2025-12-04 18:16:42","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":931562,"visible":true,"origin":"","legend":"\u003cp\u003eConservation status projections of 12 endemic species of Northeastern Brazil under the current, optimistic (SSP126) and pessimistic (SSP585) climate scenarios\u003c/p\u003e","description":"","filename":"OLIVEIRA01OCT25Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/37e2543626a3c3580c5e403e.png"},{"id":97677827,"identity":"f854bde6-0d77-4d8f-b5ff-4f310b8d22ad","added_by":"auto","created_at":"2025-12-08 09:54:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11256228,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/eec7f25a-8c27-4bbc-8f1c-7bfdece7d8a7.pdf"},{"id":97669130,"identity":"8d36f2f7-3391-4fb9-b451-244d947734fc","added_by":"auto","created_at":"2025-12-08 09:27:21","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":17085,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydata.docx","url":"https://assets-eu.researchsquare.com/files/rs-7781649/v1/6da45109e68ea233e263a634.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Projections of suitable habitat loss and its implications in conservation for endemic non-pseudantial Euphorbioideae (Euphorbiaceae) species in Northeastern Brazil under climate change scenarios","fulltext":[{"header":"Introduction","content":"\u003cp\u003eClimate change significantly influences species population dynamics (Zhao 2021) and may modify climate suitability and precipitation patterns in natural ecosystems (MMA \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This, in turn, may increase the risk of large-scale extinction events (Pillet et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), as has been recorded several times throughout the geological period (Elewa and Abdelhady \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Currently, the possibility of a new extinction event caused by the increase in Earth's temperature, driven by the intensification of anthropogenic activities, is being discussed (Schmidt \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; IPCC \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These environmental changes can accelerate the decline in plant health in both natural environments and agricultural systems (Pautasso et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), negatively impact the distribution of endemic species (Manes et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and increase vulnerability to extinction (Qian and Qian \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe subfamily Euphorbioideae (Euphorbiaceae) comprises representatives of the tribes Euphorbieae, Hippomaneae, Hureae, Pachystromateae, and Stomatocalyceae (Wurdack et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The group referred to as non-pseudantial Euphorbioideae includes the tribes that lack pseudantial inflorescences of the cyathium type (Hippomaneae, Hureae, Pachystromateae, and Stomatocalyceae), and is characterized by more conventional flowers, usually arranged in racemes, thyrsus or panicles. The subfamily is predominantly composed of species producing toxic latex and defensive chemical compounds (Garc\u0026iacute;a-Salda\u0026ntilde;a 2024), with recognized potential for cancer treatment (Souza et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e), biological control (Vaz et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), rubber production (Guerra et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), traditional medicine (Agra et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Ramos et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and pharmaceutical applications (Silva et al. 2024). In Brazil, the Euphorbioideae subfamily is represented by 219 species, of which 100 are endemic and 26 are restricted to the Northeastern region, including 15 belonging to the non-pseudantial group (Flora e Funga do Brasil 2025). These species occur mainly in the Atlantic Forest and Caatinga (Flora e Funga do Brasil 2025), many of them with extremely restricted geographic distributions (Oliveira \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Esser \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Athi\u0026ecirc;-Souza et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Approximately one third are classified in some category of threat (Athi\u0026ecirc;-Souza et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Fernandez and Rosa \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fernandez and Moraes \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Amorim and Fernandez \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Northeastern region is home to more than 11,900 species of angiosperms, making it the third most diverse region in the country in terms of flora (Flora e Funga do Brasil 2024). In contrast, it is also one of the most vulnerable to current climate change, subject to changes in the distribution of extreme temperature and rainfall events (Araujo and Willians 2000; Suarez-Contento et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). According to the Brazilian Panel on Climate Change (PBMC \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), a reduction of up to 20% in precipitation and an increase of approximately 1\u0026deg;C in average air temperature are projected by 2040, with these trends progressively worsening by the end of the century, which could accelerate processes such as the desertification of the Caatinga. Furthermore, in recent decades this region has suffered a high degree of deforestation associated with the loss of habitats for agricultural activities (Ara\u0026uacute;jo et al. 2023), resulting in a high proportion of locally threatened species, including endemic ones (Leal et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this context, studies that associate climate change and its future projections with the population dynamics of plant species are essential, especially for developing conservation strategies and contributing to elucidating the impacts of environmental changes on the biodiversity of semiarid regions (Cavalcante et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, investigating the potential distribution of species is an essential tool for identifying priority areas for conservation, helping to direct management efforts and reduce the limitations associated with the creation of new conservation units (Diniz-Filho et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Applying spatial analyses with a research approach, such as those based on diversity metrics (Bullong et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), can deepen the understanding of the population dynamics of endemic species, especially those with restricted and regionalized geographic distributions (Echternacht et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Costa et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The use of species distribution models (ENM) has also proven effective in elucidating spatial patterns in specific regions and ecosystems (Siqueira and Durigan \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), such as Northeastern Brazil.\u003c/p\u003e\u003cp\u003eThe potential effects of climate change on the distribution of species have been widely investigated in regions such as Asia and Europe (Qazi et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In contrast, in Neotropical countries, particularly Brazil, which harbors one of the largest portions of global biodiversity, including a high number of endemic species, such studies remain relatively scarce. In Brazil, most research has been concentrated in the Southeastern and Southern regions (Duarte et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), while other areas that are highly vulnerable to climate change, such as the Northeastern, have received less attention. This gap is particularly evident in arid and semi-arid regions, where ecological niche modeling studies face additional challenges due to the scarcity of occurrence data (Vasconcelos et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Nevertheless, recent studies have indicated severe habitat losses for many animal and plant species, especially within the Caatinga biome (Rodrigues et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sim\u0026otilde;es et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Moura et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea; Suarez-Contento et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), with the most critical impacts predicted for endemic species (Sim\u0026otilde;es et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Almeida et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Suarez-Contento et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this study, we analyzed the impacts of climate change on the distribution of endemic non-pseudantial Euphorbioideae species in Northeastern Brazil, projecting their potential distribution under different climate scenarios until the year 2100. Furthermore, we identified the areas of greatest species richness and estimated the extinction risk of these taxa in the face of predicted environmental changes.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy area\u003c/h2\u003e\n \u003cp\u003eThe Northeastern region is in Brazil\u0026apos;s tropical belt (1\u0026deg;02\u0026apos; N, 18\u0026deg;20\u0026apos; S, 34\u0026deg;47\u0026apos; W, 48\u0026deg;45\u0026apos; W) and comprises the states of Maranh\u0026atilde;o, Piau\u0026iacute;, Cear\u0026aacute;, Rio Grande do Norte, Para\u0026iacute;ba, Pernambuco, Alagoas, Sergipe, and Bahia. It is the third-largest region in the country in terms of territorial extension, with 1,561,177.80 km\u0026sup2;, corresponding to approximately 18.26% of the national territory (IBGE 2006). Its vast spatial dimension is reflected in significant physical, cultural, and climatic variations, which led to its subdivision into four subregions: the Mid-North, characterized as a transition zone between the Semiarid and the Amazon; the Sert\u0026atilde;o, located in the interior of the region; the Agreste, a transition zone between the Sert\u0026atilde;o and the Zona da Mata; and the Zona da Mata, located in the coastal strip that extends approximately 200 km inland (IBGE 2006). Due to the region\u0026apos;s remarkable environmental heterogeneity, areas of high rainfall are found along the coast, where annual precipitation can exceed 2,000 mm, in contrast to the semiarid Sert\u0026atilde;o, where annual rainfall is often less than 400 mm and droughts are recurrent. Temperatures also vary: while the coast has annual averages between 24\u0026deg;C and 28\u0026deg;C, the Sert\u0026atilde;o experiences high daytime temperatures, often above 30\u0026deg;C.\u003c/p\u003e\n \u003cp\u003eIn terms of vegetation cover, the Northeast is home to formations belonging to four major domains: the Atlantic Forest, restricted to small areas near the coast; the Cerrado, present in western Bahia and southern Maranh\u0026atilde;o; the Caatinga, predominant in the semiarid interior; and the Amazon, represented by the Mata dos Cocais in portions of Maranh\u0026atilde;o, Piau\u0026iacute;, Rio Grande do Norte, and Cear\u0026aacute; (Rizzini \u003cspan class=\"CitationRef\"\u003e1963\u003c/span\u003e). Each of these domains presents distinct biological, hydrographic, climatic, and topographic characteristics, offering a wide range of ecological niches and environmental conditions that contribute to the region\u0026apos;s high biodiversity.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eDatabase \u0026ndash; species occurrences\u003c/h3\u003e\n\u003cp\u003eThe occurrence data of the endemic species of non-pseudantial Euphorbioideae of Northeastern Brazil were compiled from specific literature (e.g., Wurdack et al. \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e; Oliveira \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e; Athi\u0026ecirc;-Souza et al. \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Pscheidt \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Cordeiro 2018), where 15 taxa were identified (14 spp. and 1 subspecies), of which 12 were evaluated in this study (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Subsequently, collection occurrence records were extracted from 46 indexed herbaria (ALCB, ASE, CEN, CEPEC, CEPLAC, CESJ, CSTR, EAC, ESA, F, FUEL, FURB, G, HDELTA, HFC, HPL, HRCB, HTSA, HUEFS, HUESB, HURB, HVASF, IAN, IBt, IPA, JPB, MAC, MBM, MCCA, MCMG, MN, MO, MOSS, NY, PEUFR, MNHN, SORO, SP, SPF, UB, UEC, UEFS, UFBA, UFP, US, USP -- acronyms follow Thiers \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e, continuously updated) and HST herbarium (not indexed) through the virtual platforms SpeciesLink (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://specieslink.net/\u003c/span\u003e\u003c/span\u003e) and Reflora (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://reflora.jbrj.gov.br/reflora/herbarioVirtual/\u003c/span\u003e\u003c/span\u003e), totaling 1077 specimens. The data were then screened to eliminate duplicate specimens, those with non-georeferenceable information, and/or uncertain identification. Specimens identified by experts in the Euphorbiaceae family were used to validate identification. After screening, the database totaled 421 records sampled here.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMinimum and maximum elevation of the sampled species endemic to Northeastern Brazil\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMinimum elevation (m)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMaximum elevation (m)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAc_appendiculatus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e350\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAl_bahiensis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGr_franciscana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMa_f_bahiensis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e770\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMi_heterodoxa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1206\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMi_revoluta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1269\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMi_uleana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1531\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOp_parviflorum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOp_pedunculare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e474\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSe_jacobinensis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e860\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSe_macrocarpa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e853\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSe_trinervia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e607\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSa_sceleratum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e887\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSt_loranthacea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSt_trapezoidea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eExtent of Occurrence (EOO) and Area of Occupancy (AOO) based on the current distribution of endemic species of Northeastern Brazil\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEOO (km\u0026sup2;)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAOO (km\u0026sup2;)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAc_appendiculatus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e169,959.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAl_bahiensis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,230.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGr_franciscana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMa_f_bahiensis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35,387.887\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMi_heterodoxa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e226,.694.344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e356\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMi_revoluta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146.963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMi_uleana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31,357.204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOp_parviflorum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOp_pedunculare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,363.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSe_jacobinensis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e328,437.8540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSe_macrocarpa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e442,805.7598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e336\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSe_trinervia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSa_sceleratum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e212,176.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSt_loranthacea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e634.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSt_trapezoidea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e599,044.629\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e232\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch3\u003eEnvironmental Variables and Distribution Modeling\u003c/h3\u003e\n\u003cp\u003eA set of 19 bioclimatic variables for the different scenarios were obtained from WorldClim 2.0 (Fick and Hijmans \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), with a 30-second resolution (using the boundaries of the Northeastern region of Brazil). To avoid multicollinearity problems and improve model robustness, a 70% correlation threshold was applied to the selection of environmental variables (Booth et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). After this analysis, the variables were: bio2, bio3, bio4, bio8, bio14, bio16, bio18, and bio19.\u003c/p\u003e\n\u003cp\u003eModeling of the potential distribution of species was performed using the Maxent algorithm (Phillips et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), implemented through the modleR package (S\u0026aacute;nchez-Tapia et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) in R software (v. 4.4.0, R Core Team 2023). Of the 15 taxa initially considered, only 12 were modeled, as three of them have only the type locality. Maxent is a maximum entropy method that models species distribution based on presence data and environmental variables. It is particularly advantageous for species with few occurrence records\u0026mdash;a minimum of 5 to 10 unique occurrence points is recommended for robust analyses (Phillips et al. \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). Its effectiveness with small sample sizes is due to the exclusive use of presence data and the incorporation of regularization techniques that prevent overfitting (Wisz et al. \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e; Phillips et al. \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e; Hernandez et al. \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). The accuracy and robustness of the models were assessed using cross-validation techniques, with performance measured by the Area Under the ROC Curve (AUC) (Boria et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e; Cobos et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). The calibration area for each species was defined by a minimum convex polygon encompassing 100% of the occurrence points, expanded by a 1.5\u0026deg; buffer. The model projection area corresponded to the geographic limits of Northeastern Brazil, as this is the region where the study species are present.\u003c/p\u003e\n\u003cp\u003eFuture projections (2080\u0026ndash;2100) were performed using four General Circulation Models (GCMs) representing the full range of climate sensitivity (ECS 2.9\u0026ndash;5.5\u0026deg;C): BCC-CSM2-MR, CMCC-ESM2, HadGEM3-GC31-LL, and IPSL-CM6A-LR (Boucher et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Cherchi et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Williams et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wu et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zelinka et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). These GCMs were selected based on their robust historical performance in South America (Eyring et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e; Hodnebrog et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Scafetta \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zelinka et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), allowing for contrast between the Shared Socioeconomic Pathway scenarios: SSP126 (optimistic) and SSP585 (pessimistic).\u003c/p\u003e\n\u003cp\u003eThe area of environmental suitability was calculated from the distribution models using the cellStats() function of the raster package (Hijmans \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e) in R software (v. 4.4.0, R Core Team 2023). A suitability threshold of 0.6 was applied to generate binary maps, considering cells with values above the threshold as suitable. Based on the suitability area indicated in the ecological niche modeling, the extent of the protected territory (km\u0026sup2;) was calculated using the mask_thr_projs_mscn_b function from the ENMwizard package (Heming et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Data on protected areas were obtained from the UNEP-WCMC and IUCN databases (UNEP-WCMC and ShareAction \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e \u0026amp; IUCN 2023). All analyses were conducted in R software (v. 4.4.0, R Core Team 2023).\u003c/p\u003e\n\u003cp\u003eTo assess the taxonomic diversity of endemic species under different climate scenarios, we used distribution models for each species. The metric was calculated using a tree-based approach and raster data (Mota et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Alpha diversity was obtained using the spat.alpha() function from the divraster package (Mota et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). This function is suitable for raster data and optimizes calculations for large datasets. Taxonomic diversity was defined as the species richness in each raster cell, where each species is connected to the tree root by an edge of unit length (Mota et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). All these analyses were performed in R software (v. 4.4.0, R Core Team 2023).\u003c/p\u003e\n\u003ch3\u003eRisk of species extinction\u003c/h3\u003e\n\u003cp\u003eFor the current conservation status, the area of occupancy (AOO) of the species was used as follows: CR\u0026thinsp;\u0026lt;\u0026thinsp;100 km\u0026sup2;, EN\u0026thinsp;\u0026lt;\u0026thinsp;5,000 km\u0026sup2;, VU\u0026thinsp;\u0026lt;\u0026thinsp;20,000 km\u0026sup2;, NT\u0026thinsp;\u0026lt;\u0026thinsp;30,000 km\u0026sup2;, and LC\u0026thinsp;\u0026gt;\u0026thinsp;30,000 km\u0026sup2;. Conversely, for future scenarios, the conservation status analysis was performed based on the potential distribution and projections for future scenarios, using the values of the extent of the areas of suitable occurrence and area of occupancy, according to criterion A3(c) (IUCN 2024). Criterion A3 considers the \u0026quot;projected or estimated future population reduction,\u0026quot; and subcriterion (c) considers the decline in area of occupancy (AOO), extent of occurrence (EOO), and/or habitat quality. Therefore, we classified species according to the percentage of habitat loss as follows: Extinct (EX) \u0026ndash; 100%; Critically Endangered (CR) \u0026ndash; above 80%; Endangered (EN) between 50% and 80%; Vulnerable (VU) \u0026ndash; between 30% and 50%; Near Threatened (NT) \u0026ndash; slightly below 30% (Pomoim et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). All analyses were performed using R software (v. 4.4.0, R Core Team 2023).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAll taxa exhibited changes in their areas of climatic suitability in both projected scenarios (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although the optimistic scenario (SSP126) indicates more significant reductions in the loss of climatic suitability for a greater number of species (over 25%), the pessimistic scenario (SSP585) proves more critical, as the reductions occur primarily in species with already restricted areas of suitability, resulting in greater susceptibility to inclusion in threatened categories.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn SSP126, \u003cem\u003eSapium sceleratum\u003c/em\u003e could expand its area of ​​suitability by approximately 80%, while \u003cem\u003eMicrostachys uleana\u003c/em\u003e and \u003cem\u003eActinostemon appendiculatus\u003c/em\u003e will experience gains of no more than 14%. The opposite trend was observed for other taxa, such as \u003cem\u003eMabea fistulifera\u003c/em\u003e subsp. \u003cem\u003ebahiensis\u003c/em\u003e, which experienced a 75% loss in area, followed by \u003cem\u003eOphthalmoblapton pedunculare\u003c/em\u003e, \u003cem\u003eMicrostachys heterodoxa\u003c/em\u003e, and \u003cem\u003eSebastiania jacobinensis\u003c/em\u003e, which had the most critical losses above 40% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Regarding the SSP585 scenario, a 40% loss was observed for \u003cem\u003eMabea fistulifera\u003c/em\u003e subsp. \u003cem\u003ebahiensis\u003c/em\u003e, \u003cem\u003eOphthalmoplapton pedunculare\u003c/em\u003e, \u003cem\u003eMicrostachys heterodoxa\u003c/em\u003e, and \u003cem\u003eStillingia loranthacea\u003c/em\u003e. On the other hand, \u003cem\u003eSapium sceleratum\u003c/em\u003e could gain 76% in area, and \u003cem\u003eAlgernonia bahiensis\u003c/em\u003e could double its area of ​​suitability (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe environmental suitability analysis revealed significant differences among species regarding the proportion of their potential habitats protected by conservation units, considering the current scenarios, SSP126, and SSP585. Overall, most species have a low level of protection. Less than 20% of the suitable area for these species overlaps with protected areas. Species such as \u003cem\u003eO\u003c/em\u003e. \u003cem\u003epedunculare\u003c/em\u003e, \u003cem\u003eM. revoluta\u003c/em\u003e, and \u003cem\u003eM. uleana\u003c/em\u003e stand out for having high percentages of protection in some scenarios, but have relatively small potential areas of occurrence. This suggests that, despite their limited distribution, much of their projected habitats are within conservation units, which may benefit their conservation in the future. On the other hand, widely distributed species such as \u003cem\u003eSp\u003c/em\u003e. \u003cem\u003esceleratum\u003c/em\u003e and \u003cem\u003eSe\u003c/em\u003e. \u003cem\u003emacrocarpa\u003c/em\u003e maintain large areas of environmental suitability, but with low relative protection, representing a potential risk in the face of climate change, especially in the most pessimistic scenario (SSP585) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn general, the analyzed taxa exhibit higher richness values ​​in southern Bahia, Chapada Diamantina, and the Atlantic Forest areas on the east coast of the Northeast. These regions, although experiencing reductions in both future scenarios, still concentrate the greatest richness (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In the current scenario, the regions with the highest species richness are concentrated primarily in southern Bahia and northern Minas Gerais, reaching values ​​of up to five species per pixel. Cores/secondary areas of species richness were also identified in elevated areas of Pernambuco, Alagoas, and Para\u0026iacute;ba. Under the SSP126 scenario, a general reduction in species richness is observed. Although some higher elevation areas in Bahia and Pernambuco maintain some suitability, the extent of zones with high richness (values ​​\u0026ge;4) decreases. In the pessimistic scenario (SSP585), the effects of climate change are more pronounced. Species richness declines drastically, and areas that previously had high suitability now show low or intermediate values ​​(1\u0026ndash;3 species per pixel). Only small regions in southern Bahia and Pernambuco retain moderate levels of richness. These results indicate a trend toward a loss of climatic suitability for the studied species, with potential consequences for regional biodiversity conservation, especially in the most extreme scenarios.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe conservation status of the 12 endemic taxa of the Northeastern shows a predominantly increasing trend without risk of extinction (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Our results indicate that in the current scenario, 10 species (83%) are classified as Least Concern (LC) and two (16.66%) are classified as Near Threatened (NT). In both future scenarios, \u003cem\u003eA. pendiculatus\u003c/em\u003e maintains its Least Concern (LC) status, demonstrating some resilience of its potential habitats. In the optimistic scenario (SSP126), 75% of the species migrated to higher risk categories, with specific species classified as Near Threatened (NT), Endangered (EN), and Vulnerable (VU). Similarly, in the pessimistic scenario (SSP585), the majority of species (75%) were found in some threat category. The increase in risk is most pronounced for \u003cem\u003eO. pedunculare\u003c/em\u003e, which changes from Least Concern (LC) to Near Threatened (NT) in SSP126 and subsequently to Endangered (EN) in SSP585; and for \u003cem\u003eSt. loranthacea\u003c/em\u003e, which jumps from Least Concern (LC) to Endangered (EN) in SSP126. The most critical case is that of \u003cem\u003eMabea fistulifera\u003c/em\u003e subsp. \u003cem\u003ebahiensis\u003c/em\u003e, which changes from Least Concern (LC) to Endangered (EN) in SSP126 and, in the worst-case scenario, reaches Critically Endangered (CR) status. In contrast, \u003cem\u003eA. bahiensis\u003c/em\u003e exhibits an atypical pattern, worsening from Least Concern (LC) to Near Threatened (NT) in SSP126 but returning to Least Concern (LC) in SSP585.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur results highlight complex and worrying patterns in the potential distribution and conservation status of non- pseudantial endemic Euphorbioideae species in Northeastern Brazil under climate change scenarios. A generalized contraction of areas of climatic suitability was observed for most taxa (75%) under both scenarios, resulting in a significant increase in extinction risk. Furthermore, we observed that the effects of climate change can vary distinctly across areas of suitability, thus being species-specific. These results corroborate recent evidence that many endemic plant species are sensitive to climate change, primarily because they often have restricted distributions and fragmented habitats, which represent barriers to the colonization of new climatically suitable areas in the future (Suarez-Contento et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, seasonally dry tropical forests, such as the Caatinga, are highly sensitive to climate change, as they are already close to their tolerance limits in terms of temperature and water availability (Allen et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Thus, rising temperatures and reduced engineering standards can significantly reduce suitable habitats for many species (Marengo et al. 2011; Andrade et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMoura et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) used ENMs to assess potential changes in the distribution of non-volant mammals in the Caatinga and observed that 85% of mammal species will lose suitable habitats, with a quarter of species projected to completely lose their suitable habitats by 2060. A similar result was found in the study by Silva et al. (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which demonstrated that habitats in the Caatinga with a high probability of occurrence (\u0026gt;\u0026thinsp;80%) of endemic species will be reduced (up to ~\u0026thinsp;10% for trees, ~\u0026thinsp;13% for non-trees, 10\u0026ndash;28% for species with any pollination/breeding system), with the largest reductions recorded for species with specialized reproductive traits.\u003c/p\u003e\u003cp\u003eIn this study, expansions into suitable areas were observed in both scenarios only for \u003cem\u003eS. sceleratum\u003c/em\u003e and \u003cem\u003eA. appendiculatus\u003c/em\u003e, indicating that some species can withstand extreme climate events, as they possess morphophysiological adaptations capable of withstanding prolonged droughts (Bongers et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). According to Cordeiro et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), S. \u003cem\u003esceleratum\u003c/em\u003e is commonly found on rocky outcrops and in environments subject to seasonal water deficit in the Caatinga. According to Souza et al. (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e), the areas surrounding inselbergs in the Caatinga serve as ecological microrefugia and create exceptional wetlands within these dry forests, as runoff is largely directed down the inselberg slopes. Therefore, these environments are potentially important for the persistence of many species under increasing aridity. Additionally, the presence of abundant laticifers, common in Euphorbiaceae and confirmed for species of the genus \u003cem\u003eSapium\u003c/em\u003e, may contribute to the rapid sealing of injured tissues, reducing water loss through transpiration in wounds and offering a physical barrier in hot and dry environments (Demarco et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eActinostemon appendiculatus\u003c/em\u003e is widely distributed in the Atlantic Forest, occurring from the state of Bahia to Para\u0026iacute;ba in both dense and open seasonal and ombrophilous forests. This range of occurrence may explain the species' tendency toward greater resilience to climate change, given that, as discussed by Le\u0026atilde;o et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), widespread species tend to be less vulnerable, as they encounter favorable climatic conditions in different regions. On the other hand, \u003cem\u003eA. bahiensis\u003c/em\u003e showed a different pattern. Despite its distribution restricted to the Atlantic Forest of Bahia and its preferential occurrence in open and dense ombrophilous forests, as well as in deciduous and semideciduous seasonal forests (S\u0026aacute;tiro and Sales \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), the species showed projections of significant expansion of suitable areas only under the most pessimistic climate scenario. This seemingly contradictory result may be related to changes in the availability of phytophysiognomies, since, according to the MMA (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), most forest types in the Atlantic Forest are likely to lose climatic suitability in future scenarios, except for open ombrophilous forest and transition areas, which have potential for expansion. Therefore, the projected increase in areas of suitability for \u003cem\u003eA. bahiensis\u003c/em\u003e should be interpreted with caution, as it is associated with specific habitat changes and not necessarily with greater safety for the species.\u003c/p\u003e\u003cp\u003eSeveral studies have shown that, in certain cases, climate change can favor some plant species, expanding the areas considered environmentally suitable for their occurrence. One example of this is the study by G\u0026uuml;l\u0026ccedil;in et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which highlighted the likely expansion of potential areas for \u003cem\u003eCarpinus betulus\u003c/em\u003e in Northern Europe under the new climate conditions. Meanwhile, in China, modeling for \u003cem\u003eMagnolia officinalis\u003c/em\u003e indicated a significant increase in areas of high and medium suitability by the end of the 21st century, with projected increases of more than 300,000 km\u0026sup2; under moderate and pessimistic scenarios (Ren et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). A similar trend was observed for species of the genus \u003cem\u003eEpipactis\u003c/em\u003e (Orchidaceae) in Europe, where future suitability increased in more than half of the species studied, in addition to showing northward latitudinal shifts, accompanying changes in temperature regimes (Evans and Jacquemyn \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A similar trend was recorded for three specialist tree species associated with seasonally dry tropical forests (SDTFs) in Brazil, where modeling indicated an increase of approximately 18% in suitable areas by 2080, especially in the Midwestern and Northern regions of the country (Rodrigues et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMeanwhile, the remaining taxa studied, that is, more than half of them, could be impacted in both scenarios. However, more intense and negative impacts on suitable habitats are expected for \u003cem\u003eM. fistulifera\u003c/em\u003e subsp. \u003cem\u003ebahiensis\u003c/em\u003e, \u003cem\u003eO. pendunculare\u003c/em\u003e, \u003cem\u003eM. heterodoxa\u003c/em\u003e, and \u003cem\u003eS. jacobinensis\u003c/em\u003e, whose habitats will shrink by more than 45%. Similarly, Suarez-Contento et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) predicted a decrease in ranges for approximately half of the endemic species of the genus \u003cem\u003eManihot\u003c/em\u003e (Euphorbiaceae) in Northeastern Brazil. The authors also observed that most species are found in regions that are extremely fragmented and degraded by human action.\u003c/p\u003e\u003cp\u003eFurthermore, most of these species occur in Chapada Diamantina, Bahia, an area predominantly characterized by rocky fields and Caatinga vegetation. For example, \u003cem\u003eMicrostachys revoluta\u003c/em\u003e is exclusive to the Sincor\u0026aacute; mountain range (Esser \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), and \u003cem\u003eStillingia loranthacea\u003c/em\u003e is restricted to the municipality of Morro do Chap\u0026eacute;u (Athi\u0026ecirc;-Souza et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), while \u003cem\u003eMicrostachys uleana\u003c/em\u003e, in turn, grows from the south to the central portion of the Chapada (Pscheidt \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The rocky fields of Chapada Diamantina are high-altitude ecosystems with high endemism and a small continuous area, making them extremely vulnerable to climate change (Bugado et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). According to Bitencourt et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), this area will nearly disappear, losing more than 98% of its habitat due to climate change. Furthermore, it is currently highly threatened by deforestation for agricultural activities (Funch et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2005\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and between 2019 and 2021 it suffered the loss of more than 100,000 hectares of natural territory (Silva et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to Evans and Jacquemyn (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), species with broader niche ranges (generalists) experience greater changes in habitat range in response to climate change than specialists. Similar studies have demonstrated a recurring pattern of reduced areas of climatic suitability for many Brazilian plant species. In the Brazilian semiarid region, \u003cem\u003eCeiba glaziovii\u003c/em\u003e, an endemic species of the Caatinga, showed significant losses of climatically suitable range in all scenarios analyzed, with the disappearance of areas of high suitability in more pessimistic scenarios (Almeida et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, in the Caatinga biome, other endemic cactus species, such as \u003cem\u003eBrasilicereus phaeacanthus\u003c/em\u003e and \u003cem\u003ePereskia aureiflora\u003c/em\u003e, showed significant losses of climatically suitable range, and in future scenarios, these species face considerable challenges in maintaining their current distributions (Sim\u0026otilde;es et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, in other specific biomes, such as the Cerrado, the genus \u003cem\u003eLessingianthus\u003c/em\u003e (Asteraceae), which comprises numerous threatened species, also showed significant reductions in its future distribution ranges in both optimistic and pessimistic scenarios for 2050 and 2070 (Angulo et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Thus, these studies highlight both the intrinsic vulnerability of endemic and restricted species and the urgent need for robust conservation strategies, including the expansion of protected areas and the identification of climate refugia, to ensure the maintenance of plant biodiversity in the face of future climate change. Furthermore, these findings indicate the need to reassess the representativeness of protected areas, prioritizing both species with widespread distributions that are poorly protected and those with restricted distributions, even when currently well protected.\u003c/p\u003e\u003cp\u003eDespite the identification of areas of high biodiversity value in the current scenario, future projections point to a significant reduction in these biodiversity hotspots. Furthermore, analysis of overlap with protected areas also reveals that, although some species may find partial refuge in already protected areas, current coverage is insufficient to ensure the maintenance of most potential habitats in the face of predicted severe climate change. Similar patterns are observed in other regions, indicating that, even with the expansion of protected areas, their capacity to guarantee suitable habitats may prove limited in the face of future climate conditions (Lombo-Sanchez et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this study, we found that nine taxa are considered within some threat category in both future scenarios, notably \u003cem\u003eStillingia loranthacea\u003c/em\u003e, which is restricted to a single municipality and in the projections showed a decline in its area of ​​suitability in both scenarios, in addition to going from the category of Least Concern (LC) to Vulnerable (VU). For the conservation of these taxa to be effective, it is necessary to create new Conservation Units in the areas of greatest richness and diversity, with emphasis on Chapada Diamantina and Sul Baiano, which presented the highest diversity indices, as well as in regions with extremely restricted species, such as \u003cem\u003eGradyana franciscana\u003c/em\u003e, as well as areas that are suitable refuges for wider species, such as the fragments of the East Northeast, which present a refuge for \u003cem\u003eActinostemon appendicullatus\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eA recent survey of biodiversity protection in Brazil's protected areas, covering vertebrates, arthropods, and angiosperms, indicates that, despite the country's exceptional biological wealth and its status as a global conservation priority, these areas still offer insufficient protection. Many endemic species and lineages remain unprotected, highlighting significant gaps in the coverage and effectiveness of currently established areas (Lopes, 2010).\u003c/p\u003e\u003cp\u003eAlthough restricted species known only from type material (\u003cem\u003eOphthalmoblapton parviflorum\u003c/em\u003e, \u003cem\u003eSebastiania trinervia\u003c/em\u003e, and \u003cem\u003eGradyana franciscana\u003c/em\u003e) were not included in the distribution modeling, they are likely at high risk of threat due to their microendemism and extremely small populations (Qian \u0026amp; Qian, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, they are highly vulnerable to human impact. A striking example is \u003cem\u003eGradyana franciscana\u003c/em\u003e, recorded on the banks of the Lower S\u0026atilde;o Francisco River, an area heavily impacted by human activity and subject to intense modifications of the riverside landscape, with consequent alterations to associated ecosystems (Ara\u0026uacute;jo, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study of endemic Euphorbioideae taxa in Northeastern Brazil highlights the importance of assessing their potential distribution, vulnerability, and adaptation in the face of climate change. The results, which indicate both gains and losses in suitable areas, reveal the complexity of climate impacts and the need to expand collections and population studies, especially for rare species underrepresented in scientific collections. Furthermore, the current configuration of Protected Areas (PAs) in Northeastern Brazil does not guarantee the conservation of the studied species against future climate change. Therefore, we emphasize the need for conservation strategies to protect biodiversity in Northeastern Brazil's ecosystems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by Funda\u0026ccedil;\u0026atilde;o de Amparo \u0026agrave; Ci\u0026ecirc;ncia e Tecnologia de Pernambuco (BFP-0238-2.03/24) and (APQ-0995-2.03/21) and by Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq) (405265/2021-2).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the concept and design of the article. Database compilation and preparation were carried out by J.C.R.M. \u0026amp; T.O. All analyses developed in the study were performed by T.O., K.Y.S.C., Y.J.L.S., and V.R.S.L. with supervision by S.M.A.S. Graphical production of the maps in QGIS was performed by T.O. The scope of this manuscript was written by T.O., A.M.T., and S.M.A.S., and the other authors contributed comments and suggestions throughout the writing process. All authors read and approved the result.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors would like to thank the Funda\u0026ccedil;\u0026atilde;o de Amparo \u0026agrave; Ci\u0026ecirc;ncia e Tecnologia de Pernambuco (FACEPE) for awarding the first author a master's degree scholarship and the second author a postdoctoral scholarship (BFP-0238-2.03/24), and the Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq) (405265/2021-2), and FACEPE (APQ-0995-2.03/21) for financial support during herbarium visits. The authors would also like to thank the herbarium curators and technicians for their logistical support during the material analyses.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgra MDF, Silva KN, Bas\u0026iacute;lio IJLD, Freitas PFD, Barbosa-Filho JM (2008) Survey of medicinal plants used in the region Northeast of Brazil. Rev Bras Farmacogn 18:472\u0026ndash;508. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S0102-695X2008000300023\u003c/span\u003e\u003cspan address=\"10.1590/S0102-695X2008000300023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAllen K, Dupuy JM, Gei MG, Hulshof C, Medvigy D, Pizano C, Salgado-Negret B, Smith CM, Trierweiler A, Bloem SJV, Waring B, Xu X, Powers JS (2017) Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes? Environ Res Let 12(2):023001. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1088/1748-9326/aa5968\u003c/span\u003e\u003cspan address=\"10.1088/1748-9326/aa5968\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlmeida DM, Nogueira SS, Silva EA, Souza JMF, Gurchel ALC, Sousa AN (2024) Climate change is expected to reduce the potential distribution of \u003cem\u003eCeiba glaziovii\u003c/em\u003e in Caatinga, the largest area of dry tropical forest in South America. J Biosci 40:e40051. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.14393/BJ-v40n0a2024-72663\u003c/span\u003e\u003cspan address=\"10.14393/BJ-v40n0a2024-72663\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAngulo MB, Via Do Pico G, Dematteis M (2021) Impact of climate change on the current and future distribution of threatened species of the genus \u003cem\u003eLessingianthus\u003c/em\u003e (Vernonieae: Asteraceae) from the Brazilian Cerrado. Acad Bras Cienc 93:e20190796. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/00013765202120190796\u003c/span\u003e\u003cspan address=\"10.1590/00013765202120190796\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmorim E, Fernandez E (2021) \u003cem\u003eAlgernonia bahiensis\u003c/em\u003e (Euphorbiaceae). Lista Vermelha da Flora Brasileira: Centro Nacional de Conserva\u0026ccedil;\u0026atilde;o da Flora/ Instituto de Pesquisas Jardim Bot\u0026acirc;nico do Rio de Janeiro. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://proflora.jbrj.gov.br/html/Algernonia%20bahiensis_2021.htmlh\u003c/span\u003e\u003cspan address=\"https://proflora.jbrj.gov.br/html/Algernonia%20bahiensis_2021.htmlh\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed September 2024)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAndrade EM, Aquino DN, Chaves LCG, Lopes FB (2017) Water as capital and its uses in the Caatinga. In: Silva JMC, Leal IR, Tabarelli M (eds) Caatinga - The largest tropical dry forest region in South America. Springer, Cham, pp 281\u0026ndash;302\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAra\u0026uacute;jo MB, Williams PH (2000) Selecting areas for species persistence using occurrence data. Biol Conserv 96:331\u0026ndash;345. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0006-3207(00)00074-4\u003c/span\u003e\u003cspan address=\"10.1016/S0006-3207(00)00074-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAra\u0026uacute;jo SS (2015) Apropria\u0026ccedil;\u0026atilde;o dos recursos naturais e conflitos socioambientais no Baixo S\u0026atilde;o Francisco em Sergipe e Alagoas. Thesis, Universidade Federal de Sergipe. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ri.ufs.br/jspui/handle/123456789/4041\u003c/span\u003e\u003cspan address=\"https://ri.ufs.br/jspui/handle/123456789/4041\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAraujo HFP (2023) Human disturbance is the major driver of vegetation changes in the Caatinga dry forest region. Sci Rep 13:18440\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAthi\u0026ecirc;-Souza SM, Melo AL, Silva MJ, Sales MF (2014) Reinstatement and Lectotypification of \u003cem\u003eStillingia loranthacea\u003c/em\u003e (Euphorbiaceae), a Vulnerable Species from Chapada Diamantina, Bahia (Brazil), and a New Circumscription of \u003cem\u003eStillingia saxatilis.\u003c/em\u003e Syst Bot. 39:510\u0026ndash;516. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1600/036364414X680915\u003c/span\u003e\u003cspan address=\"10.1600/036364414X680915\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAthi\u0026ecirc;-Souza SM, Melo AL, Silva MJ, Oliveira LSD, Sales MF (2015) \u003cem\u003eGradyana\u003c/em\u003e (Euphorbiaceae): A New Genus from Northeastern Brazil. Syst Bot 40:527\u0026ndash;533. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1600/036364415X688781\u003c/span\u003e\u003cspan address=\"10.1600/036364415X688781\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBitencourt C, Rapini A, Damascena LS, Junior PDM (2016) The worrying future of the endemic flora of a tropical mountain range under climate change. Flora: Morphol Distrib Funct Ecol Plants 218:1\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.flora.2015.11.001\u003c/span\u003e\u003cspan address=\"10.1016/j.flora.2015.11.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBongers FJ, Olmo M, Lopez-Iglesias B, Anten NPR, Villar RJPB (2017) Drought responses, phenotypic plasticity and survival of Mediterranean species in two different microclimatic sites. Plant Biol 19:386\u0026ndash;395\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBooth TH, Nix HA, Busby JR, Hutchinson MF (2014) BIOCLIM: the first species distribution modelling package, its early applications and relevance to most current MAXENT studies. Divers distrib 20:1\u0026ndash;9\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoria RA, Olson LE, Goodman SM, Anderson RP (2014) Spatial filtering to reduce sampling bias can improve the performance of ecological niche models. Ecol Model 275:73\u0026ndash;77. https://doi.org/10.1016/j. ecolmodel.2013.12.012\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoria RA, Olson LE, Goodman SM, Anderson RP (2016) A single-algorithm ensemble approach to estimating suitability and uncertainty: cross-time projections for four Malagasy tenrecs. Divers distrib 23:196\u0026ndash;208. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/ddi.12510\u003c/span\u003e\u003cspan address=\"10.1111/ddi.12510\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoucher O, Servonnat J, Albright AL, Aumont O, Balkanski Y, Bastrikov V, Bekki S, Bonnet R, Bony S, Bopp L, Braconnot P, Brockmann P, Cadule P, Caubel A, Cheruy F, Codron F, Cozic A, Cugnet D, D\u0026rsquo;Andrea F, Davini P, de Lavergne C, Denvil S, Deshayes J, Devilliers M, Ducharne A, Dufresne JL, Dupont E, \u0026Eacute;th\u0026eacute; C, Fairhead L, Falletti L (2020) Presentation and Evaluation of the IPSL-CM6A-LR Climate Model. J Adv Model Earth Syst 12(7): e2019MS002010. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1029/2019MS002010\u003c/span\u003e\u003cspan address=\"10.1029/2019MS002010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBugado RE, Shrestha N, Magri RA, Prado J, Lopes JC (2025) Vanishing ecosystems: The looming threat of climate change on an iconic genus \u003cem\u003eVellozia\u003c/em\u003e in the Brazilian campos rupestres. Glob Ecol Conserv 58:e03439. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.gecco.2025.e03439\u003c/span\u003e\u003cspan address=\"10.1016/j.gecco.2025.e03439\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBullong JRT, Silverio JP, Alafag JI et al (2024) Development of endemicity and conservation importance indices for tropical forests and the floral diversity assessment of Mt. Natoo Benguet Philippines JMS 21:786\u0026ndash;804. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11629-023-8387-9\u003c/span\u003e\u003cspan address=\"10.1007/s11629-023-8387-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCavalcante AMB, Fernandes PHC, Silva EM (2020) \u003cem\u003eOpuntia ficus-indica\u003c/em\u003e (L.) Mill. e as Mudan\u0026ccedil;as Clim\u0026aacute;ticas: Uma An\u0026aacute;lise a Luz da Modelagem de Distribui\u0026ccedil;\u0026atilde;o de Esp\u0026eacute;cies no Bioma Caatinga. Rev bras meteorol 35: 375\u0026ndash;385. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/0102-7786353001\u003c/span\u003e\u003cspan address=\"10.1590/0102-7786353001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCherchi A, Fogli PG, Lovato T, Peano D, Iovino D, Gualdi S, Masina S, Scoccimarro E, Materia S, Belluci A, Navarra A (2019) Global Mean Climate and Main Patterns of Variability in the CMCC-CM2 Coupled Model. J Adv Model Earth Syst 11:185\u0026ndash;209. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1029/2018MS001369\u003c/span\u003e\u003cspan address=\"10.1029/2018MS001369\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCobos ME, Peterson AT, Barve N, Osorio-Olvera L (2019) Kuenm: An R package for detailed development of ecological niche models using Maxent. PeerJ 7:e6281. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7717/peerj.6281\u003c/span\u003e\u003cspan address=\"10.7717/peerj.6281\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCordeiro WDS, Melo AD, Athi\u0026ecirc;-Souza SM, Esser HJ, Sales MD (2018) Reinstatement of \u003cem\u003eSapium sceleratum\u003c/em\u003e (Euphorbiaceae), an endemic species from Northeast Brazil, and new circumscription of \u003cem\u003eSapium argutum\u003c/em\u003e. Phytotaxa, 348: 23\u0026ndash;31\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCosta SL, Louzada RB, Nepomuceno SC, Alves JV, Buril MT (2024) Distribution pattern in the rupiculous genus Orthophytum (Bromelioideae/Bromeliaceae) reveals high microendemicity in different types of rocky outcrops. Braz Acad Sci 96(2). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/0001-3765202420230007\u003c/span\u003e\u003cspan address=\"10.1590/0001-3765202420230007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDiniz-Filho JAF, Bini LM, Rangel TF, Loyola RD, Hof C, Nogu\u0026eacute;s-Bravo D, Ara\u0026uacute;jo MB (2009) Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change. Ecography. 32:897\u0026ndash;906. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1600-0587.2009.06196.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1600-0587.2009.06196.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDemarco D, de Moraes Castro M, Ascens\u0026atilde;o L (2013) Two laticifer systems in \u003cem\u003eSapium haematospermum\u003c/em\u003e\u0026mdash;new records for Euphorbiaceae. Botany 91:545\u0026ndash;554. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1139/cjb-2012-0277\u003c/span\u003e\u003cspan address=\"10.1139/cjb-2012-0277\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDuarte LDS et al (2019) Species distribution models for Atlantic Forest plants: advances and challenges. Perspect Ecol Conserv 17:1\u0026ndash;10\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEchternacht L, Trov\u0026oacute; M, Oliveira CT, Pirani JR (2011) Areas of endemism in the Espinha\u0026ccedil;o Range in Minas Gerais, Brazil. Flora 206:782\u0026ndash;791. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.flora.2011.04.003\u003c/span\u003e\u003cspan address=\"10.1016/j.flora.2011.04.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElewa AMT, Abdelhady AA (2020) Past, present, and future mass extinctions. J Afr Earth Sci 162:1\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jafrearsci.2019.103678\u003c/span\u003e\u003cspan address=\"10.1016/j.jafrearsci.2019.103678\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEsser HJ (1998) New combinations in \u003cem\u003eMicrostachys\u003c/em\u003e (Euphorbiaceae). Kew Bull 955\u0026ndash;960\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEsser HJ (2012) The tribe Hippomaneae (Euphorbiaceae) in Brazil. Rodrigu\u0026eacute;sia 63:209\u0026ndash;225. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S2175-78602012000100013\u003c/span\u003e\u003cspan address=\"10.1590/S2175-78602012000100013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEvans A, Jacquemyn H (2022) Range size and niche breadth as predictors of climate-induced habitat change in Epipactis (Orchidaceae). Front Ecol Evol 10:894616\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE (2016) Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci Model Dev 9:1937\u0026ndash;1958. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5194/gmd-9-1937-2016\u003c/span\u003e\u003cspan address=\"10.5194/gmd-9-1937-2016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFernandez E, Moraes M (2020) \u003cem\u003eStillingia loranthacea\u003c/em\u003e (Euphorbiaceae). Lista Vermelha da Flora Brasileira: Centro Nacional de Conserva\u0026ccedil;\u0026atilde;o da Flora/ Instituto de Pesquisas Jardim Bot\u0026acirc;nico do Rio de Janeiro. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://proflora.jbrj.gov.br/html/Stillingia%20loranthacea_2020.htmlax\u003c/span\u003e\u003cspan address=\"https://proflora.jbrj.gov.br/html/Stillingia%20loranthacea_2020.htmlax\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed September 2024)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFernandez E, Rosa P (2018) \u003cem\u003e) Ophthalmoblapton pedunculare\u003c/em\u003e (Euphorbiaceae). Lista Vermelha da Flora Brasileira: Centro Nacional de Conserva\u0026ccedil;\u0026atilde;o da Flora/ Instituto de Pesquisas Jardim Bot\u0026acirc;nico do Rio de Janeiro. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://proflora.jbrj.gov.br/html/Ophthalmoblapton%20pedunculare_2018.html\u003c/span\u003e\u003cspan address=\"https://proflora.jbrj.gov.br/html/Ophthalmoblapton%20pedunculare_2018.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed September 2024)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFick SE, Hijmans RJ (2017) WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol 37:4302\u0026ndash;4315. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/joc.5086\u003c/span\u003e\u003cspan address=\"10.1002/joc.5086\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFunch LS, Funch RR, Harley R, Giulietti AM, Queiroz LP, Fran\u0026ccedil;a F, Melo E, Gon\u0026ccedil;alves CN, Santos T (2005) Florestas estacionais semideciduais. In: Junc\u0026aacute; FA, Funch L, Rocha W (eds) Biodiversidade e conserva\u0026ccedil;\u0026atilde;o da Chapada Diamantina. Minist\u0026eacute;rio do Meio Ambiente, Bras\u0026iacute;lia, pp 181\u0026ndash;193\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFunch LS, Rodal MJN, Funch RR (2008) Floristic aspects of the forests of the Chapada Diamantina, Bahia, Brazil. In: Thomas W, Briton EG (ed) The Atlantic Coastal Forest of Northeastern Brazil. Mem. of the New York Botanical Garden Press 100: 193\u0026ndash;220\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarc\u0026iacute;a-Salda\u0026ntilde;a EA, Cerqueda-Garc\u0026iacute;a D, Ibarra-Laclette E, Aluja M (2024) Insights into the differences related to the resistance mechanisms to the highly toxic fruit \u003cem\u003eHippomane mancinella\u003c/em\u003e (Malpighiales: Euphorbiaceae) between the larvae of the sister species \u003cem\u003eAnastrepha acris\u003c/em\u003e and \u003cem\u003eAnastrepha ludens\u003c/em\u003e (Diptera: Tephritidae) through comparative transcriptomics. Front Physiol 15:1263475\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuerra NB, Sant\u0026rsquo;Ana Pegorin G, Boratto MH, de Barros NR, de Oliveira Graeff CF, Herculano RD (2021) Biomedical applications of natural rubber latex from the rubber tree \u003cem\u003eHevea brasiliensis\u003c/em\u003e. Mater Sci Eng C 126:112126. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.msec.2021.112126\u003c/span\u003e\u003cspan address=\"10.1016/j.msec.2021.112126\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eG\u0026uuml;l\u0026ccedil;in D, Arslan ES, \u0026Ouml;r\u0026uuml;c\u0026uuml;, \u0026Ouml;me K (2021) Effects of climate change on the ecological niche of common hornbeam (\u003cem\u003eCarpinus betulus\u003c/em\u003e L). Ecol Inf 66:101478. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ecoinf.2021.101478\u003c/span\u003e\u003cspan address=\"10.1016/j.ecoinf.2021.101478\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarley RM (1995) Introdu\u0026ccedil;\u0026atilde;o. In: Stannard BL (ed) Flora of the Pico das Almas, Chapada Diamantina, Bahia, Brasil. Royal Botanic Gardens, Kew, pp 43\u0026ndash;78\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHeming N, Dambros C, Guti\u0026eacute;rrez E (2019) \u003cem\u003eNM/ENMwizard: Advanced Techniques for Ecological Niche Modeling Made Easy\u003c/em\u003e. Available from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/HemingNM/ENMwizard\u003c/span\u003e\u003cspan address=\"https://github.com/HemingNM/ENMwizard\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHernandez PA, Graham CH, Master LL, Albert DL (2006) The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 29:773\u0026ndash;785. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.0906-7590.2006.04700.x\u003c/span\u003e\u003cspan address=\"10.1111/j.0906-7590.2006.04700.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHijmans RJ (2012) Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model. Ecology 93:679\u0026ndash;688. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1890/11-0826.1\u003c/span\u003e\u003cspan address=\"10.1890/11-0826.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHodnebrog \u0026Oslash;, Steensen BM, Marelle L, Alterskj\u0026aelig;r K, Dals\u0026oslash;ren SB, Myhre G (2022) Understanding model diversity in future precipitation projections for South America. Clim Dyn 58:1329\u0026ndash;1347. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00382-021-05964-w\u003c/span\u003e\u003cspan address=\"10.1007/s00382-021-05964-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eINSTITUTO BRASILEIRO DE GEOGRAFIA E ESTAT\u0026Iacute;STICA (IBGE) (2006) Regi\u0026otilde;es, mesorregi\u0026otilde;es geogr\u0026aacute;ficas do Brasil. 34, Bras\u0026iacute;lia, 62p\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIPCC (2023) Summary for Policymakers. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds)] IPCC, Geneva, Switzerland, pp. 1\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.59327/IPCC/AR6-9789291691647.001\u003c/span\u003e\u003cspan address=\"10.59327/IPCC/AR6-9789291691647.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIUCN Standards and Petitions Committee (2024) Guidelines for Using the IUCN Red List Categories and Criteria. Version 16. Prepared by the Standards and Petitions Committee. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.iucnredlist.org/documents/RedListGuidelines.pdf\u003c/span\u003e\u003cspan address=\"https://www.iucnredlist.org/documents/RedListGuidelines.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLe\u0026atilde;o TCC, Reinhardt JR, Nic Lughadha E, Reich PB (2021) Projected impacts of climate and land use changes on the habitat of Atlantic Forest plants in Brazil. Glob Ecol Biogeogr 30:2016\u0026ndash;2028. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/geb.13365\u003c/span\u003e\u003cspan address=\"10.1111/geb.13365\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeal IR, Da-Silva JMC, Tabarelli M, Lacher TE (2005) Changing the course of biodiversity conservation in the Caatinga of northeastern Brazil. Biol Conserv 19:701\u0026ndash;706. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1523-1739.2005.00703.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1523-1739.2005.00703.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLopes RV (2010) As esp\u0026eacute;cies amea\u0026ccedil;adas da Flora brasileira e o Sistema Nacional de Unidades de Conserva\u0026ccedil;\u0026atilde;o (SNUC): uma abordagem preliminar do caso do bioma Cerrado. In: Diniz R et al (eds) Cerrado-Conhecimento cient\u0026iacute;fico quantitativo como subs\u0026iacute;dio para a\u0026ccedil;\u0026otilde;es de conserva\u0026ccedil;\u0026atilde;o. Brazil; Conserva\u0026ccedil;\u0026atilde;o International, pp 35\u0026ndash;88\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLombo-Sanchez YJ, Suarez-Contento KY, Silva MPP, P\u0026ocirc;rto KC (2025) Liverworts in a changing world: Vulnerability and extinction risk of specialist species under climate change in a tropical country (Colombia). Nat Conserv Res 10(3):34\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dx.doi.org/10.24189/ncr.2025.016\u003c/span\u003e\u003cspan address=\"10.24189/ncr.2025.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eManes S et al (2021) Endemism increases species\u0026rsquo; climate change risk in areas of global biodiversity importance. Biol Conserv 257:109070. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.biocon.2021.109070\u003c/span\u003e\u003cspan address=\"10.1016/j.biocon.2021.109070\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMMA (2018) Impacto das mudan\u0026ccedil;as do clima na Mata Atl\u0026acirc;ntica. Bras\u0026iacute;lia. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gov.br/mma/pt-br/assuntos/ecossistemas/biomas/arquivos-biomas/impactos-da-mudanca-do-clima-na-mata-atlantica.pdf\u003c/span\u003e\u003cspan address=\"https://www.gov.br/mma/pt-br/assuntos/ecossistemas/biomas/arquivos-biomas/impactos-da-mudanca-do-clima-na-mata-atlantica.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. (accessed December 2024)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarengo JA, Torres RR, Alves LM (2017) Drought in Northeast Brazil \u0026ndash; past, present and future. Theor Appl Climatol 129:1189\u0026ndash;1200. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00704-016-1840-8\u003c/span\u003e\u003cspan address=\"10.1007/s00704-016-1840-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoura MR, Oliveira GA, Paglia AP, Pires MM, Santos BA (2023) Climate change should drive mammal defaunation in tropical dry forests. Glob Chang Biol 29:6931\u0026ndash;6944. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/gcb.16979\u003c/span\u003e\u003cspan address=\"10.1111/gcb.16979\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMota FMM, Alves-Ferreira G, Talora DC, Heming NM (2023) divraster: an R package to calculate taxonomic, functional and phylogenetic diversity from rasters. Ecography, 2023(12), e06905\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOliveira LSD (2010) Considera\u0026ccedil;\u0026otilde;es filogen\u0026eacute;ticas e taxon\u0026ocirc;micas na tribo Hureae Dumort. (Euphorbioideae - Euphorbiaceae). Thesis, Universidade Federal Rural de Pernambuco. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bdtd.ibict.br/vufind/Record/URPE_2cdcc75c11631d7526f1d99e4e5b226e\u003c/span\u003e\u003cspan address=\"https://bdtd.ibict.br/vufind/Record/URPE_2cdcc75c11631d7526f1d99e4e5b226e\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePautasso M, D\u0026ouml;ring TF, Garbelotto M, Pellis L, Jeger MJ (2012) Impacts of climate change on plant diseases\u0026mdash;opinions and trends. Eur J Plant Pathol 133:295\u0026ndash;313. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10658-012-9936-1\u003c/span\u003e\u003cspan address=\"10.1007/s10658-012-9936-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePBMC (2013) Sum\u0026aacute;rio Executivo do Volume 1 \u0026ndash; Base Cient\u0026iacute;fica das Mudan\u0026ccedil;as Clim\u0026aacute;ticas. Contribui\u0026ccedil;\u0026atilde;o do Grupo de Trabalho 1 para o 1\u0026deg; Relat\u0026oacute;rio de Avalia\u0026ccedil;\u0026atilde;o Nacional do Painel Brasileiro de Mudan\u0026ccedil;as Clim\u0026aacute;ticas. COPPE/UFRJ, Rio de Janeiro\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePhillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231\u0026ndash;259\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePhillips SJ, Anderson RP, Dud\u0026iacute;k M, Schapire RE, Blair ME (2017) Opening the black box: an open-source release of Maxent. Ecography 40:887\u0026ndash;893. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/ecog.03049\u003c/span\u003e\u003cspan address=\"10.1111/ecog.03049\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePillet et al (2022) Elevated extinction risk of cacti under climate change. Nat Plants 8:366\u0026ndash;372. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41477-022-01130-0\u003c/span\u003e\u003cspan address=\"10.1038/s41477-022-01130-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePomoim N, Hughes AC, Trisurat Y, Corlett RT (2022) Vulnerability to climate change of species in protected areas in Thailand. Sci Rep 12:5705. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-022-09767-9\u003c/span\u003e\u003cspan address=\"10.1038/s41598-022-09767-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePscheidt AC (2015) O g\u0026ecirc;nero \u003cem\u003eMicrostachys\u003c/em\u003e A. Juss. e a tribo Hippomaneae (Euphorbiaceae). Thesis, Universidade de S\u0026atilde;o Paulo, 258p. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003esmastr16.blob.core.windows.net/pgibt/2018/05/pscheidt_2015.pdf\u003c/span\u003e\u003cspan address=\"http://smastr16.blob.core.windows.net/pgibt/2018/05/pscheidt_2015.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQazi AW, Saqib Z, Zaman-ul-Haq M (2022) Trends in species distribution modelling in context of rare and endemic plants: a systematic review. Ecol Process 11:40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13717-022-00384-y\u003c/span\u003e\u003cspan address=\"10.1186/s13717-022-00384-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQian H, Qian S (2024) Global patterns of taxonomic and phylogenetic endemism in liverwort assemblages. Plant Divers 47:82\u0026ndash;88. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pld.2024.08.004\u003c/span\u003e\u003cspan address=\"10.1016/j.pld.2024.08.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRamos LFS, de Sousa AG, de Siqueira Amorim R, de Ara\u0026uacute;jo Roque A, Carvalho ILD, de Carvalho ALV, Santos ME, Marques MB, Lima LRA, Costa MJF, Sette-de-Souza PH (2024) Ethnobotanical surveys of plants used by Quilombola communities in Brazil: A scoping review. Life 14(10):1215\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRen J, Li S, Zhang Y, Yang Q, Liu J, Fan J, Xiang Y (2025) MaxEnt-based evaluation of climate change effects on the habitat suitability of \u003cem\u003eMagnolia officinalis\u003c/em\u003e in China. Front Plant Sci 16:1601585\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRizzini CT (1963) Nota pr\u0026eacute;via sobre a divis\u0026atilde;o fitogeogr\u0026aacute;fica (flor\u0026iacute;stico-sociol\u0026oacute;gica) do Brasil. RBG 25:3\u0026ndash;64\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRodrigues PMS, Silva JO, Eisenlohr PV, Schaefer CEGR (2015) Climate change effects on the geographic distribution of specialist tree species of the Brazilian tropical dry forests. Braz J Biol 75:679\u0026ndash;684\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eS\u0026aacute;tiro LR, Sales MF (2014) \u003cem\u003eAlgernonia bahiensis\u003c/em\u003e (Euphorbiaceae), a new species from Bahia, Brazil. Phytotaxa 156:285\u0026ndash;290\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eS\u0026aacute;nchez-Tapia A, Mortara SR, Bezerra Rocha DS, Mendes Barros FS, Gall G, de Siqueira MF (2020) modleR: a modular workflow to perform ecological niche modeling in R. BioRxiv, 2020-04. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1101/2020.04.01.021105\u003c/span\u003e\u003cspan address=\"10.1101/2020.04.01.021105\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScafetta N (2023) CMIP6 GCM ensemble members versus global surface temperatures. Clim Dyns 60:3091\u0026ndash;3120. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00382-022-06493-w\u003c/span\u003e\u003cspan address=\"10.1007/s00382-022-06493-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchmidt JJ (2021) Glacial Deaths, Geologic Extinction. Environ Humanit 13:2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1215/22011919-9320156\u003c/span\u003e\u003cspan address=\"10.1215/22011919-9320156\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSilva EM, Rocha WJSF, Souza DTM, Costa DP, Duverger SG (2023) O processo de desmatamento do bioma Caatinga na Chapada Diamantina-BA (2019\u0026ndash;2021) In: Anais do XX Simp\u0026oacute;sio Brasileiro de Sensoriamento Remoto. IMPE, Florian\u0026oacute;polis, pp 3040\u0026ndash;3043\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSilva JLS, Cruz-Neto O, Peres CA, Tabarelli M, Lopes AV (2019) Climate change will reduce suitable Caatinga dry forest habitat for endemic plants with disproportionate impacts on specialized reproductive strategies. PLoS ONE 14(5):e0217028. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0217028\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0217028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSilva LMB, Loureiro B (2024) Properties and medical applications of the Euphorbiaceae family and their bioproducts: a patent review. Naunyn-schmiedeberg's Arch Pharmacol\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSim\u0026otilde;es SS, Zappi D, Costa GM, Oliveira G, Aona LYS (2019) Spatial niche modelling of five endemic cacti from the Brazilian Caatinga: Past, present and future. Austral Ecol 45:35\u0026ndash;47. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/aec.12825\u003c/span\u003e\u003cspan address=\"10.1111/aec.12825\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSiqueira MF, Durigan G (2007) Modeling geographic distribution of Cerrado woddy species in S\u0026atilde;o Paulo State. Rev Brasil Bot 30:233\u0026ndash;243. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S0100-84042007000200008\u003c/span\u003e\u003cspan address=\"10.1590/S0100-84042007000200008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSouza BM, Tonini TRT, Rocha EA (2018) Environmental characterization of rural properties in Serra Bonita Particular Reserve of the Natural Heritage. Camacan Bahia SODEBRAS 13:93\u0026ndash;97. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.29367/issn.1809-3957.2018.151\u003c/span\u003e\u003cspan address=\"10.29367/issn.1809-3957.2018.151\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSouza TAD, Alves AF, Lira ND, Cibulski SP, Pereira LH, Abreu LS, Tavares JF, Scotti MT, Silva MSD (2025a) Chemotaxonomic Analysis of Diterpenes in Four Euphorbiaceae Genera: A Path to New Cytotoxic Agents. J Braz Chem Soc 36(7):e\u0026ndash;20250061\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSouza BID, Lunguinho RL, Xavier RA, Queiroz RTD, Medeiros JRD, Cardoso ECM, Maciel MGR, Neto IOB, Santos LJC, Souza JJLLS, Cordeiro JMP (2025b) Rainwater runoff, soil, and vegetation interactions in inselbergs provide microrefugia in Brazil\u0026rsquo;s Caatinga drylands. Environ Monit Assess 197:772\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSuarez-Contento KY, Teles CB, Alves-Ferreira G, Martins MLL, Athi\u0026ecirc;-Souza SM (2024) Projected effects of climate change on the potential distribution range of \u003cem\u003eManihot\u003c/em\u003e species endemic to Northeast Brazil Annals of Brazilian Academy of Science 96. 1. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/0001-3765202420231211\u003c/span\u003e\u003cspan address=\"10.1590/0001-3765202420231211\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThiers B (2025) [continuously updated]) Index Herbariorum: A global directory of public herbaria and associated staff. New York Botanical Garden\u0026rsquo;s Virtual Herbarium, New York. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://sweetgum.nybg.org/ih/\u003c/span\u003e\u003cspan address=\"http://sweetgum.nybg.org/ih/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed March 2025)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUNEP-WCMC and ShareAction (2024) Risk Management in Protected Areas. UN Environment Programme World Conservation Monitoring Centre, Cambridge, UK\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVasconcelos RN, Cantillo-P\u0026eacute;rez T, Franca Rocha WJ, Aguiar WM, Mendes DT, de Jesus Santana CO, Santana MM, Oliveira RP (2024) Advances and Challenges in Species Ecological Niche Modeling: A Mixed Review. Earth 5:963\u0026ndash;989\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVaz AF, Costa RM, Melo AM, Oliva ML, Santana LA, Silva-Lucca RA, Coelho LCBB, Correia MT (2010) Biocontrol of Fusarium species by a novel lectin with low ecotoxicity isolated from \u003cem\u003eSebastiania jacobinensis\u003c/em\u003e. Food Chem 119:1507\u0026ndash;1513\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao et al (2021) Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study. Lancet Planet Health 2021; 5: e415\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2542-5196(21)00081-4\u003c/span\u003e\u003cspan address=\"10.1016/S2542-5196(21)00081-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilliams KD, Copsey D, Blockley EW, Bodas-Salcedo A, Calvert D, Comer R, Davis P, Graham T, Hewitt HT, Hill R, Hyder P, Ineson S, Johns TC, Keen AB, Lee RW, Megann A, Milton SF, Rae JGL, Roberts MJ, Scaife AA, Schiemann R, Storkey D, Thorpe, Watterson IG, Walters DN, West A, Wood RA, Woollings T, Xavier PK (2018) The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations. J Adv Model Earth Syst 10:357\u0026ndash;380. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/2017MS001115\u003c/span\u003e\u003cspan address=\"10.1002/2017MS001115\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWisz MS, Hijmans RJ, Li J, Peterson AT, Graham CH, Guisan A, Elith J, Dud\u0026iacute;k M, Ferrier S, Huettmann F, Leathwick JR, Lehmann A, Lohmann L, Loiselle BA, Manion G, Moritz C, Nakamura M, Nakazawa Y, Overton JMC, Phillips SJ, Richardson KS, Scachetti-Pereira R, Schapire RE, Sober\u0026oacute;n J, Williams SE, Zimmermann NE (2008) Effects of sample size on the performance of species distribution models. Divers distrib 14:763\u0026ndash;773. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1472-4642.2008.00482.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1472-4642.2008.00482.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu T, Yu R, Lu Y, Jie W, Fang Y, Zhang J, Zhang L, Xin X, Li L, Wang Z, Liu Y, Zhang F, Wu F, Chu M, Li J, Li W, Zhang Y, Shi X, Zhou W, Yao J, Liu X, Zhao H, Yan J, Wei M, Xue W, Huang A, Shu Q, Hu A (2021) BCC-CSM2-HR: A high-resolution version of the Beijing Climate Center Climate System Model. Geosci Model Dev 14:2977\u0026ndash;3006. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5194/gmd-14-2977-2021\u003c/span\u003e\u003cspan address=\"10.5194/gmd-14-2977-2021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWurdack KJ, Hoffmann P, Chase MW (2005) Molecular phylogenetic analysis of uniovulate Euphorbiaceae (Euphorbiaceae sensu stricto) using plastid rbcL and trnL-F DNA sequences. Am J Bot 92:1397\u0026ndash;1420. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3732/ajb.92.8.1397\u003c/span\u003e\u003cspan address=\"10.3732/ajb.92.8.1397\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZelinka MD, Myers TA, McCoy DT, Po-Chedley S, Caldwell PM, Ceppi P, Klein SA, Taylor KE (2020) Causes of higher climate sensitivity in CMIP6 models. Geophys Res Lett 47(1): e2019GL085782. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1029/2019GL085782\u003c/span\u003e\u003cspan address=\"10.1029/2019GL085782\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"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":"Spatial analysis, Biogeography, Ecological Niche Modeling, Hippomaneae","lastPublishedDoi":"10.21203/rs.3.rs-7781649/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7781649/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClimate change has intensified negative impacts on biodiversity through changes in precipitation patterns and rising global average temperatures. Semi-arid regions, such as parts of Northeastern Brazil, are particularly susceptible to these changes, with projections indicating that they will become hotter and drier, reducing the climatic suitability of several plant species. In this context, endemic and restricted-range species may be highly vulnerable. In this study, we used distribution modeling to estimate potential changes in the geographic distribution and conservation of 12 endemic Euphorbiaceae species from Northeastern Brazil, to inform conservation strategies. We found that climate change will have distinctly different impacts on the suitable habitat areas for the analyzed taxa. Projections indicate that in the optimistic scenario (SSP126), \u003cem\u003eSapium sceleratum\u003c/em\u003e could expand its suitable range by approximately 80%, while \u003cem\u003eMicrostachys uleana\u003c/em\u003e and \u003cem\u003eActinostemon appendiculatus\u003c/em\u003e will experience limited gains (\u0026lt;\u0026thinsp;14%), and other species will experience losses exceeding 40%. In the pessimistic scenario (SSP585), five taxa lose areas of suitability above 40%, but \u003cem\u003eSapium sceleratum\u003c/em\u003e and \u003cem\u003eAlgernonia bahiensis\u003c/em\u003e could expand by 76% and 100%, respectively. We also documented a reduction in species richness in all future climate scenarios analyzed. Furthermore, in both climate scenarios, a general trend toward increasing extinction risk is observed for most species. Thus, this study clearly demonstrates that most endemic species in the family are highly vulnerable to various future climate change scenarios and that conservation measures such as the creation of protected areas within the species' climatically suitable concentrations should be established.\u003c/p\u003e","manuscriptTitle":"Projections of suitable habitat loss and its implications in conservation for endemic non-pseudantial Euphorbioideae (Euphorbiaceae) species in Northeastern Brazil under climate change scenarios","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 18:16:31","doi":"10.21203/rs.3.rs-7781649/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-01T15:46:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-28T17:52:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"226770821436591342583657557421389763698","date":"2026-01-19T23:26:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-13T19:17:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"228338662807492149435737389491150941958","date":"2026-01-12T15:12:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-18T18:51:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259912095609133625630325729987468611750","date":"2025-12-01T16:35:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"240309690043651959589117598843658413572","date":"2025-12-01T11:57:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-01T11:50:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-23T13:55:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-10T08:41:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biodiversity and Conservation","date":"2025-10-04T19:19:02+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":"eda9425f-951b-461d-a2ee-84988aa220a3","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-16T18:08:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-04 18:16:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7781649","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7781649","identity":"rs-7781649","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}