Brazil nut journey under future climate change in Amazon

RESEARCH ARTICLE Brazil nut journey under future climate change in Amazon Luciano J. S. AnjosID1,2☯*, Gabriela S. R. Gonc¸alves3☯, Vı´tor A. B. DutraID2☯, Amanda G. RosaID2‡, Lucyana B. Santos4‡, Ma´rcia N. R. Barros2‡, Everaldo B. de SouzaID1,2‡, Peter M. de Toledo5‡ 1 Faculdade de Meteorologia, Instituto de Geociências, Universidade Federal do Para´ —UFPA, Bele´ m, Para´, Brazil, 2 Programa de Po´s-Graduac¸ão em Ciências Ambientais, Instituto de Geociências, Universidade Federal do Para´ —UFPA, Bele´ m, Para´ , Brazil, 3 Laborato´rio de Biogeografia da Conservac¸ão e Macroecologia, Instituto de Ciências Biolo´ gicas, Universidade Federal do Para´ —UFPA, Bele´m, Para´ , Brazil, 4 Programa de Po´ s-Graduac¸ão em Ciências Ambientais, Universidade do Estado do Para´—UEPA, Bele´ m, Para´ , Brazil, 5 Divisão de Impactos, Adaptac¸ão e Vulnerabilidade, Instituto Nacional de Pesquisas Espaciais —INPE, São Jose´ dos Campos, São Paulo, Brazil ☯ These authors contributed equally to this work. ‡ AGR, LBS, MNRB, EBS and PMT also contributed equally to this work. * ljsanjos@gmail.com Abstract Climate change is among the principal threats to global terrestrial biodiversity, especially to megadiverse ecosystems such as the Amazon rainforest. In this study, we investigate how it could affect an iconic forest species—Bertholletia excelsa—(the Brazil nut) which has val- ues in multiple dimensions in an Amazonian context. We used an ensemble from various distribution modeling methods designed for four different climate scenarios from CMIP6 by

Brazil nut journey under future climate change in Amazon. PLoS ONE 19(11): e0312308. https://doi. org/10.1371/journal.pone.0312308 Editor: Marcela Pagano, Universidade Federal de Minas Gerais, BRAZIL Received: February 29, 2024 Accepted: October 3, 2024 Published: November 13, 2024 Copyright: © 2024 Anjos et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: The work in question received two types of public funding resources from Brazilian agencies for scientific research, as detailed below. LJSA - Postdoctoral grant Specific grant numbers: 88887.461811/2019-00 Coordenac¸ão de Aperfeic¸oamento de Pessoal de Nı´vel Superior https://www.gov.br/capes/pt-br LJSA – Payment of fee publication Specific grant numbers: EDITAL 01/ 2023 – PROPESP Pro´-Reitoria de Pesquisa e Po´s-

traits, as well as the network of interactions of communities, impacting on interspecific rela- tionships and their structure [3]. In response to the changes, species move into geographic space, seeking adequate climatic conditions for their survival, growth, and reproduction [2, 4], changing their distribution pat- terns over generations [5, 6]. In this way, it can lead to population declines, or even species extinction [7, 8]. As consequence of these cascading events, changes in the climate pattern can promote the loss of biodiversity and ecosystem functions, such as seed dispersal, the germina- tive success of these seeds, and therefore the process of forest regeneration [9], affecting the integrity of biomes on a wide scale [10]. In the Amazon, the consequences of climate change can range from extreme weather events such as droughts and floods, changes in rainfall regime, increased fire risk associated with impacts on climate, health, and biodiversity [11, 12]. Furthermore, extreme droughts and floods cause additional stress on Amazonian forests, increasing the risk of tree mortality [13]. Thus, if changes reach a critical threshold because of increases in temperature, generating lon- ger drought periods in the near future, major changes would be triggered in Amazonia, such as large-scale "savannization" events [11, 12, 14]. According to [15], continuous deforestation in the Amazon severely affected about 36 to 57% of all common and rare tree species. Inasmuch, some species are the merger of losing

over 30% of their original population. This is the case of the Brazilian Nut tree (Bertholletia excelsa), an iconic species of the Amazon region that is among the vulnerable species, under the criteria of the International Union for Conservation of Nature (IUCN) Red List [16]. The Brazil nut tree is a long-lived species that is demanding in terms of favorable light for its survival and ascent in the canopy. In the seedling stage it is demanding for light, especially in open areas such as clearings and grazing, favoring its vertical growth, besides having a high capacity for regrowth and performance recovery after traumatic episodes of physiological nature, being considered indicators of past disturbances. Therefore, its life cycle is associated with natural events and disturbances such as extreme floods, droughts, tree fall gaps and fires [17–20]. B. excelsa is one of the most important non-timber products producing trees in the Amazon bioeconomy. Its fruits are predominantly harvested from natural forests. The species is an emergent tree, reaching heights up to 50 m, and is a long-lived and pioneer. It usually grows in areas above sea level (> 400 m) with an annual mean temperature of 23.5 to 27.6˚C and annual rainfall ranging from 1,445 to 3,399 mm [21]. In this study, to analyze suitability conditions for the Brazil nut distribution by the end of the current century, we used species distribution modeling under future climatic conditions not analogous to the current ones. We also quantify over continuous geographical space and

time in the Amazon landscape, under different climatic scenarios, the extinction patterns, per- sistence places, and colonization of potential distribution areas. Since the species at hand has a strong dependence on human consumption and traditional cultivation activities, this historical distribution pattern must be an issue to be addressed in the conservation strategies. Material and methods Area of study The area of study comprises the Amazon biome in its biogeographic domains defined by the Amazon Network of Georeferenced Socio-Environmental Information (RAISG) polygon (http://raisg.socioambiental.org/ - accessed on the November 2023). The study area covers approximately 7 million km2. It is the world’s largest watershed, encompassing tropical PLOS ONE Effects of climate change on Brazil nut PLOS ONE | https://doi.org/10.1371/journal.pone.0312308 November 13, 2024 2 / 13 Graduac¸ão, Universidade Federal do Para´ https:// www.propesp.ufpa.br/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.

rainforest and other types of vegetation [22]. The Amazon biome has been altered by defores- tation and forest degradation, affecting 38% of the area [23]. Current and future climate variables datasets We used the bioclimatic variables of WorldClim 2.0 [24] (https://worldclim.org - accessed in 09/19/2023) as predictors with a spatial resolution of 0.0833˚ (~10 km). We selected the follow- ing variables: bio1—Average Annual Temperature, bio12—Annual cumulative precipitation; bio7—Annual temperature amplitude; and bio15—Seasonality of Precipitation. These predic- tors are often used for distribution models because of their relationship to species physiology and water/energy sources. Regarding the simulated climate for the future, the bioclimatic variables mentioned above were downloaded from WorldClim 2.0 from the most recent simulation generated by CMIP6 (Coupled Model Intercomparison Project Phase 6). We used four distinct time periods until the end of the century: 2021–2040; 2041–2060; 2061–2080 and 2081–2100. To minimize the effect of uncertainty associated with the different Global Circulation Models (GCMs) [25], we used an average ensemble of five GCMs (BCC-CSM2-MR, CNRM-CM6-1, CNRM-ESM2-1, MIROC6, MIROC-ES2L). Such GCMs were selected considering the values of the Equilibrium Climate Sensibility (ECS) and Transition Climate Response (TCR) parameters [26]. Anthropogenic Greenhouse Gases (GHG) emissions are mainly driven by population size, economic activity, lifestyle, energy use, land use patterns, technology, and climate policy. In

this sense, the Intergovernmental Panel for Climate Change (IPCC) conceptualized the SSPs— Shared Socioeconomic Pathways (SSPs) based on CMIP6 climate simulations [27]. We have selected four (04) simulated climate scenarios available on the WorldClim 2.0 (https:// worldclim.org/data/) [28]. Among the scenarios used in this study, the most optimistic is SSP1-2.6, which points to a sustainable future where there are low challenges to mitigating and adapting to climate change [29]. We also use a scenario called Middle of the Road (SSP2-4.5), where the challenges of adapting to and mitigating climate change can be considered intermediate. Finally, we use two pessimistic scenarios: SSP3-7.0 (Regional Rivalry) and SSP5-8.5 (Fossil-fueled Development). The difference between them concerns the great challenges for adapting to climate change, where SSP3-7.0 points to high challenges in promoting adaptation. In other hand, SSP5-8.5, despite the economy and use of natural resources being based on the intensive use of fossil fuels, there would be more conditions for the generation and sharing of new adaptive technologies. Occurrence database To prospect the species distribution of Bertholletia excelsa Bonpl., in the Amazon biome, we used geographical occurrences from the Global Biodiversity Information Facility (GBIF) (https://www.gbif.org/species/3083180; accessed in 16/05/2024), which is an international net- work and research infrastructure funded by the world’s governments and aimed at providing open access to data about much life on Earth. To download the occurrences, we used the

’dismo’ package [30]. After downloading the occurrences, we performed coordinate accuracy testing and duplicate exclusion with the ’biogeo’ package [31]. We compiled 255 unique occur- rence records for Bertholletia excelsa, covering the entire area of study. Distribution model for B. excelsa To build the species distribution model for B. excelsa, we used the package ’biomod2’ [32] implemented in the R software [33]. We built a consensus model based on an ensemble of PLOS ONE Effects of climate change on Brazil nut PLOS ONE | https://doi.org/10.1371/journal.pone.0312308 November 13, 2024 3 / 13

seven different distribution modeling algorithms, which are: Artificial Neural Networks (ANN) [34]; Classification Tree Analysis (CTA) [35]; Function Discriminant Analysis (FDA) [34]; Generalized Additive Models (GAM) [36]; Generalized Boosted Regression Models (GBM) [37]; Generalized Linear Models (GLM) [38]; Random Forest (RF) [39]. For each modeling method, we ran 10 replicate models with 75–25% training-test propor- tion samples, respectively, re-sampled randomly by bootstrap. The 500 pseudo-absence sam- ples were selected using the ’disk’ function, considering the limit of a radius of 1˚ (111.11 km) in the surroundings of each geographical occurrence for selection. To evaluate the quality of the generated models, we used two metrics: True Skill Statistics (TSS) [40] and Receiving Operating Characteristic (ROC) [41] (S1 Table). For each model gen- erated, a measure of the importance of climatic variables for the construction of the models was also computed (S2 Table). Finally, for ensemble composition, we selected only models with TSS values equal to or greater than 0.6. Our consensual distribution model, represented by the average model among the best rotated models, was then designed under present and future climatic conditions for the different scenarios and periods. The result comprises a mea- sure of climate adequacy, ranging from inadequate (0) to the most appropriate (1000) climati- cally between the different periods and climate scenarios evaluated. Calculation of trend of gain or loss of climatic suitability

To assess the trend of changes in climate suitability for Bertholletia excelsa by the end of the century, we used the VoCC package [42] in R [33]. We use the ’tempTrend’ function that esti- mates coefficients of a linear regression and projects them over the geographic space, showing loss (negative values) or gain (positive values) of suitability for the species over the periods and climatic scenarios evaluated. Definition of the critical threshold of suitability for extinction The distribution models have in their representation in a continuous form of suitability for the species. Here, ranging between zero (0) and 1000. One of the key points of the post-modeling steps is to define from which value along the gradient the species will be present (persistence or potential colonization) or absent (local extinction). As a critical threshold parameter for the extinction of the species in a pixel, we used the minimum training presence (MTP) observed among all records of occurrence of the species, which is represented by the value equal to 550. In other words, if a pixel, in any period or future scenario assessed, has a value of less than 550 in terms of climatic suitability, it is declared that the species would be locally extinct. This strat- egy is widely adopted to define critical thresholds because it has a strong biological support [43]. Simulation of future spatial dynamics with MigClim Unlike static models, which are used to evaluate the effects of step-by-step environmental changes, here we use the MigClim package [44] in R [33]. The main function of this package is

to incorporate spatially explicitly the dispersion (movement) of the species over the study area as a function of events of changes in suitability for the time interval evaluated. In this sense, it was possible to quantify three fundamental results about the geographical distribution of a spe- cies under pressure of environmental changes (here climatic): [1] Persistence—when a particu- lar pixel maintains, throughout the evaluated period, minimally satisfactory values of suitability that support the maintenance of the species; [2] Extinction—occurs when an evalu- ated pixel loses suitability for a critical climate threshold; & [3] Colonization—occurs when there is an increase in suitability, because of ongoing changes, in unoccupied pixels next to PLOS ONE Effects of climate change on Brazil nut PLOS ONE | https://doi.org/10.1371/journal.pone.0312308 November 13, 2024 4 / 13

those that the species already occurred, causing the species to disperse to these neighboring pixels. We used four environmental change events, (one for each period up to the end of the cen- tury) with two (2) dispersal events, equivalent to one event every 10 years. The scattering func- tion for colonization of neighboring cells follows the following probabilistic values from the contiguous pixels: 1.0, 0.4, 0.16, 0.06, 0.03. This means that as the geographic departure of a particular pixel occurs, the likelihood of scattering events from that pixel decreases. The main result of this spatial population dynamics simulation is a map where it is possible to map all the events described above (persistence, extinction, and colonization) and in which period such an event occurred. In addition, a special class of pixels is created where it can occur, until the end of the evaluation period, the resumption to a previous level of suitability. This class can be interpreted as those pixels that initially lost suitability for the critical level of extinction, but that eventually became favorable by the end of the simulation. Influence of altitude on the future spatial dynamics of B. excelsa With the results of the spatialized simulations with MigClim for the different scenarios (extinc- tion, colonization, and persistence), we tested the hypothesis that the colonization events for new areas could be correlated with altitude, given a visual pattern detected in the analyzes. In this sense, we extracted the altitude values for each cell of the map of the study area and tested

the response of the simulations from a Pearson correlation analysis. Such analyzes were per- formed in R [33]. Results The maps in Fig 1 show the trend of loss/gain of suitability from the present until the year 2100. The positive values (blue tones) show gain in suitability and the negative ones (yellow and red tones) show loss. We observed a loss of suitability for Bertholletia excelsa in most of the Amazon basin. This pattern is persistent among the different future scenarios evaluated. Some areas would be affected by a greater loss of climate suitability than others. For example, in the Southwest Amazon moist forests, in the region of the northern trough of the Amazon River—Uatuma-Trombetas moist forests—and a portion of the southeast—Tapajo´s-Xingu moist forests (areas in red). On the other hand, it was possible to observe that to the west and north of the Amazon basin, around the region of Japura´-Solimoes-Negro moist forests, there would be a gain in suitability, as well as those areas with higher altitude (Peruvian Yungas, Gui- anan moist forests, Xingu-Tocantins-Araguaia moist forests). There are differences between future climatic scenarios that need to be highlighted. Although there is a tendency to reduce the generalized suitability for the Amazon basin, losing suitability would be more severe in the most pessimistic climate scenarios. This result is clear when the percentage lost via extinction in the different scenarios over time is evaluated (Table 1). All scenarios point to losses of more than 50% of the species’ distribution area due to

climate change by the end of the century. In the SSP3-7.0 scenario, the reduction of the avail- able area of the species could reach 94% of what is now the current distribution of Bertholletia excelsa. SSP2-4.5 would be the least severe among the future scenarios evaluated, with a loss of the original distribution area reaching 53.53% by the end of the century. Oppositely, the mod- els predict that the gain in suitability tends to be more pronounced also toward the most pessi- mistic scenarios. The graph in Fig 2 shows the relationship between the temporal trend of suitability and alti- tude. The results show that the colonization of the species to new areas may be related to a search for environments of higher elevation. This is evidenced by the positive values of the PLOS ONE Effects of climate change on Brazil nut PLOS ONE | https://doi.org/10.1371/journal.pone.0312308 November 13, 2024 5 / 13

correlation between the tendency to increase suitability associated with the increase in altitude. It is also possible to observe that there are differences between the different climate scenarios. Apparently, the more severe the scenario (e.g., SSP5-8.5), the greater the effect of colonization to new areas of high elevation. The maps in Fig 3 evaluate the spatial dynamics of the species in the different climatic sce- narios. In the most optimistic scenario (Fig 3A), the local extinction of the species would occur in a large area in the first 20 years, being more severe than the scenario in Fig 3B (SSP2-4.5) B. The most dramatic situation would be in the SSP3-7.0 scenario (Fig 3C), in which the area where the species could persist is restricted to a narrow strip in the central Amazon towards the southwestern Amazon. In the most pessimistic scenario (Fig 3D), there would be a signifi- cant loss of habitat with virtual local extinction, mainly in the last period evaluated (areas in red). Fig 1. Gain or loss of climatic suitability for Bertholletia excelsa by the end of the century in the different climate scenarios evaluated. (A) SSP1-2.6; (B) SSP2-4.5; (C) SSP3-7.0; (D) SSP5-8.5. Made with Natural Earth. Free vector and raster map data @naturalearthdata.com. https://doi.org/10.1371/journal.pone.0312308.g001 Table 1. Percentual of the potential distribution lost cumulatively via predicted extinction for each period (col- umns) and climate scenario (rows) analyzed in relation to the current distribution. Period/Scenario 2021–2040 2041–2060 2061–2080 2081–2100

SSP1-2.6 41.11 55.68 59.92 62.29 SSP2-4.5 33.62 43.74 49.23 53.53 SSP3-7.0 44.51 73.27 88.39 94.37 SSP5-8.5 36.74 47.33 60.15 71.60 https://doi.org/10.1371/journal.pone.0312308.t001 PLOS ONE Effects of climate change on Brazil nut PLOS ONE | https://doi.org/10.1371/journal.pone.0312308 November 13, 2024 6 / 13

Another relevant result observed concerns the possibility of reversing habitats that would become climatically unsuitable in the near future. Our results suggest that some areas in Fig 3 (in yellow) would become climatically suitable in the last 20 years of the century, specifically between 2080 and 2100. However, Bertholletia excelsa could not access them due to the lack of landscape connectivity, defined based on the parameters of the migration model for the spe- cies. They would be areas suitable climatically, but inaccessible to the species via natural dis- persal. These would be areas that humans could manage the species, considering recovery from active ecological restoration. This pattern is most pronounced in the most pessimistic scenarios (SSP3-7.0 and SSP5-8.5). Discussion The biogeographic distributions of trees in the Amazon are shaped by a combination of fac- tors, such as drought tolerance, biological interactions, edaphic conditions, shade tolerance, and dispersal. Moreover, drought acts more strongly as an environmental filter for adult trees [45, 46]. Plants subjected to higher atmospheric concentrations of CO2 and increased air tem- perature show changes in photosynthetic production, resulting in changes in their ecophysiol- ogy [47, 48]. Thus, the risk of extinction of the Brazil nut may increase due to its sensitivity to environmental variations [17, 49]. Esquivel-Muelbert et al. investigated whether the floristic and functional composition of intact lowland Amazonian forests has been changing by evaluating records from 106 long-term inven-

tory plots spanning 30 years [50]. One of their results indicated that there had been notable Fig 2. Pearson’s correlation between the trend of changes in suitability and altitude with the data of the simulated colonization events for new areas in the different scenarios. The dashed red line marks the division between the values of loss of suitability (left) and gain (right). https://doi.org/10.1371/journal.pone.0312308.g002 PLOS ONE Effects of climate change on Brazil nut PLOS ONE | https://doi.org/10.1371/journal.pone.0312308 November 13, 2024 7 / 13

increases in the relative abundance of the dry-affiliated genera Bertholletia. One of the aggravating factors also for the effective success of the chestnut tree is its reproduction dependent on bee- mediated fertilization and the loss of these pollinators affects the long-term viability of chestnut populations [20]. In addition, Brazil nuts are also dependent on agouti for seed dispersal [51]. Inasmuch, climate change alters the geographic distribution of species and the response of each species depends on its individual intrinsic tolerance [52]. This displacement may lead to the loss of key relationships between species, contributing to the extinction of these biotic interactions [53]. Seed dispersal and pollination are closely dependent on animal-plant inter- actions for reproduction [53]. According to Sales et al. [54] found that the resilience of the biotic interactions between the Brazil nut tree and its community of dispersers may suffer a decoupling due to the niche mismatch for the year 2090. This mismatch was more frequent in the scenario more realistic scenario of climate change (SSP3-7.0). In our results, we verified that the colonization regions are concentrated in areas of higher altitudes. These results are comparable with other works. For example, [55] found that 20% of the epiphyte species found in the Atlantic Forest will have their climatic niche shifted to higher altitudes. The same was observed by [56], who, working with ferns and lycophytes in Hondu- ras, found that 28–53% of these will have altitudinal displacement by the year 2100 for both

RCP 2.6 and RCP 8.5, respectively. [57] found that 47% of the fern and lycophyte species found along the mountain of the Celaque National Park, the highest in Honduras, will have to Fig 3. Spatial dynamics, considering extinction, colonization, and persistence, for Bertholletia excelsa in the different future climate scenarios evaluated in the study. Made with Natural Earth. Free vector and raster map data @naturalearthdata.com. https://doi.org/10.1371/journal.pone.0312308.g003 PLOS ONE Effects of climate change on Brazil nut PLOS ONE | https://doi.org/10.1371/journal.pone.0312308 November 13, 2024 8 / 13

shift their distribution above the maximum altitude of the mountain under the scenario from RCP2.6 to the year 2050. This displacement to areas of higher altitudes is also being recorded for animal species. Stream fish species of the genera Barbus and Leuciscus, it is predicted to colonize newly suit- able areas in stretches of higher elevation or to extend their ranges towards the poles [58–60]. [61] studying birds endemic to the mountains of eastern Brazil predicted that all species stud- ied in all scenarios (2050 and 2070) will experience a shift in their distributions to higher areas. A similar finding was also found for birds from high mountains in temperate and tropical regions, such as the Andes [62–64]. In many parts of its distribution range, B. excelsa occurs in an aggregated pattern, forming clusters known as ’manchales’, ’castanhais’ or ’reboleiras’, which are interspersed with vast areas of forest with very few or no trees. The scale of these clusters varies, and at the local level, the dispersion of B. excelsa is usually attributed to Dasyprocta species. At a regional and conti- nental level, it is attributed to humans acting as dispersal agents, with evidence of human activ- ity ranging from 12,000 to 20,000 years Before Present (BP) [21]. In a more recent scenario, it is known that the B. excelsa distribution across Central Amazo- nia changed drastically not only with regional climatic variability but also with major political and socioeconomic activities during post-colonial era (over 400 years ago)–the collapse of pre-

Columbian indigenous (e.g., Mura populations) led to the interruption of management prac- tices, affecting the B. excelsa as well [17]. In a future scenario where there is a reduction and/or absence of Dasyprocta species, B. excelsa will rely on human dispersion to colonize new areas suitable for its growth, as seen in the yellow areas in Fig 3. Moreover, future projections of climate change show that pollinators’ range may reduce drastically in the future, which might cause a spatial mismatch between B. excelsa and its community of pollinators [54]. In this sense, our finding aligns well with [21] results, especially for our SSP5-8.5 scenario result (Fig 3D), where the western portion of the Amazon might be suitable for B. excelsa colonization if there is human intervention. It is difficult to predict how B. excelsa will fare in the future climate along with human inter- vention. However, because of its importance for the bioeconomy, it is possible to infer that the species might be planted in more areas towards the Brazilian Western Amazon in the future. Brazil is the leading exporter of Brazil nuts with shells, holding a 47% share of its global market between 2017 and 2019. The global market for this product is relatively small (US$24 million/ year), and the main destinations for Brazil nuts with shells are Peru (38%) and Bolivia (16%). Both countries purchase Brazil nuts with shells as raw materials and use their superior indus- trial and commercial capacities to process and export them as Brazil nuts without shells, a

product with a unit price four times higher (US$9.1/kg without shell against US$2.2/kg with shell) and a total market almost 15 times larger (US$364 million) [65]. Brazil nuts not only play a key role in the ecology and nutrient cycling of the Amazon for- ests, but also have their importance for human subsistence since the settlement of the Amazon [66, 67]. In addition, Brazil nuts play an important role in carbon sequestration [68]. In this way, information on the best areas for human management practices, restoration potential, contributes to more efficient conservation efforts, maintenance of Brazil nut trees and the design of management strategies, given that the species is currently considered threatened by the Ministry of the Environment (Law No. 443/2014 MMA, 2014). Conclusions Our results indicate that there is a high risk of the extinction of the iconic species Bertholletia excelsa because of the effects of climate change by the end of the century. This risk can be PLOS ONE Effects of climate change on Brazil nut PLOS ONE | https://doi.org/10.1371/journal.pone.0312308 November 13, 2024 9 / 13

reduced if the species can access areas of elevation via migration, as well as have an active recovery plan based on effective management of the species, especially in the most pessimistic climate scenarios. Supporting information S1 Table. Averaged (Mean) and Standard Deviation (SD) values for evaluation metrics (TSS and ROC) by different methods for specie distribution model. Average values were calculated utilizing 10 replicates. (DOCX) S2 Table. Importance metrics of the predictors by different methods to build the specie distribution model. (DOCX) Author Contributions Conceptualization: Luciano J. S. Anjos, Vı´tor A. B. Dutra, Amanda G. Rosa, Lucyana B. San- tos, Ma´rcia N. R. Barros, Everaldo B. de Souza, Peter M. de Toledo. Data curation: Luciano J. S. Anjos, Vı´tor A. B. Dutra, Amanda G. Rosa, Ma´rcia N. R. Barros. Formal analysis: Luciano J. S. Anjos, Gabriela S. R. Gonc¸alves, Vı´tor A. B. Dutra, Amanda G. Rosa, Lucyana B. Santos, Ma´rcia N. R. Barros. Funding acquisition: Luciano J. S. Anjos, Everaldo B. de Souza, Peter M. de Toledo. Investigation: Peter M. de Toledo. Methodology: Gabriela S. R. Gonc¸alves, Vı´tor A. B. Dutra, Amanda G. Rosa, Lucyana B. San- tos, Ma´rcia N. R. Barros, Everaldo B. de Souza, Peter M. de Toledo. Project administration: Luciano J. S. Anjos. Software: Gabriela S. R. Gonc¸alves. Validation: Luciano J. S. Anjos. Visualization: Luciano J. S. Anjos. Writing – original draft: Luciano J. S. Anjos, Gabriela S. R. Gonc¸alves, Vı´tor A. B. Dutra, Amanda G. Rosa, Lucyana B. Santos, Ma´rcia N. R. Barros, Everaldo B. de Souza, Peter M. de Toledo.

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