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Climate change effects on marginal savannas from central-north Brazil

Abstract

This study estimated the potential effects of climate change on peripheral plant diversity by predicting the distribution of species from Cerrado of Northern Brazil. Ecological niche modeling was used to provide present and future projections of responses in terms of occurrence of ten woody species based on four algorithms and four future climate change scenarios for the year 2050. Potential refuge areas for conservation actions were identified, and evidence of the vulnerability of the flora was demonstrated based on the disparity between potential areas of climate stability amid current protected areas. The results suggested a lack of pattern between the scenarios and an idiosyncratic response of the species, indicating different impacts on plant communities and the existence of unequal stable alternative conditions, which could bring consequences to the ecological relationships and functionality of the floras. Even in the most pessimistic scenarios, most species presented an expansion of potential occurrence areas, suppressing or cohabiting with species of adjacent biomes. Typically marginal plants were the most sensitive. Overlapping adequate habitats are concentrated in the NBC. The analysis of habitats in relation to anthropized areas and PAs demonstrate low future effectiveness in the protection of these savannas.

Key words
biodiversity forecasting modeling; ecological niche modeling; refuge; woody distribution

INTRODUCTION

Changes in climatic conditions are periodic and common in nature in different regions of the planet. They correspond to a natural cyclic process involving warming, cooling and intense geological activities of the earth that promote various phenomena and effects, causing changes in biological systems and ecological interrelations (Oliveira et al. 2017OLIVEIRA MJ, CARNEIRO CDR, VECCHIA FAS & BAPTISTA GMM. 2017. Ciclos climáticos e causas naturais das mudanças do clima. Ter Did 13: 149-184.). However, anthropogenic actions of the last 200 years have contributed to harmful conditions, changing particle/gas concentrations in the atmosphere with the intensification of land use and occupation (Oliveira et al. 2017OLIVEIRA MJ, CARNEIRO CDR, VECCHIA FAS & BAPTISTA GMM. 2017. Ciclos climáticos e causas naturais das mudanças do clima. Ter Did 13: 149-184., IPCC 2018IPCC. 2018. Summary for Policymakers. In: Global warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. In: Masson-Delmotte V et al. (Eds), World Meteorological Organization, Geneva, Switzerland, 32 p. Retrieved from https://report.ipcc.ch/sr15/pdf/sr15_spm_final.pdf.
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), and accelerating the speed of environmental processes to the point of preventing species from adapting or finding more suitable places to live.

The increase in the average global surface temperature is one of the main concerns of the scientific community in view of its immediately noticeable effects and relation with the biosphere in general. During the last century, the increase recorded was of approximately 0.87 °C above pre-industrial levels (IPCC 2018) and if the temperature continues to rise at the current rate, the increase is estimated to reach 1.5 °C between 2030 and 2052 (IPCC 2018). The expected average increase in South America is 4 °C, indicating a higher frequency of extreme events in Brazil, such as floods and heat waves (Marengo 2005MARENGO JA. 2005. Mudanças Climáticas Globais e seus efeitos sobre a biodiversidade, caracterização do clima atual e definição das alterações climáticas para o território brasileiro ao longo do século XXI. Ministério do Meio Ambiente, Brasília, MMA, 212 p.). Regional models indicate that by the end of the 21st century, the most intense effects will occur in the tropical region, specifically in the Amazon and Northeast of Brazil (Nobre et al. 2008NOBRE CA, SAMPAIO G & SALAZAR L. 2008. Cenários de mudança climática para a América do Sul para o final do século 21. Parc Estrat 13: 27-35.).

Climate and geological transformations have triggered adaptive processes in biological communities, leading to their evolution, development, diversification, dispersion and extinction throughout the history of lineages (Costa et al. 2012aCOSTA JLPO, VELOSO FILHO FA, AQUINO CMS & CASTRO AAJF. 2012a. Visão geral da biogeografia e dos sistemas universais de classificação fitogeográfica. Geogr Public Avul 10: 5-22.). It is particularly important to be aware of their effects on biodiversity, because of the associated changes in distribution, phenology, migration calendar, nesting success, and population sizes of species. Thus, the response of biodiversity to climate change has become a very fruitful field for research (Hughes 2000HUGHES L. 2000. Biological consequences of global warming, is the signal already apparent? Trend Ecol Evol 15: 56-61., McCarty 2001MCCARTY JP. 2001. Ecological consequences of recent climate change. Cons.Biol 15: 320-331., Walther et al. 2002WALTHER GR, POST E, CONVEY P, MENZEL A, PARMESAN C, BEEBEE TJC & BAIRLEIN F. 2002. Ecological responses to recent climate change. Nat 416: 389-395., 2005WALTHER GR, BERGER S & SYKES MT. 2005. An ecological ‘footprint’ of climate change. Proceed Royal Soc Lond 272: 1427-1432., De Marco Junior & Siqueira 2009DE MARCO JUNIOR P & SIQUEIRA MF. 2009. Como determinar a distribuição potencial de espécies sob uma abordagem conservacionista? Megadivers 5: 1-2., Bellard et al. 2012BELLARD C, BERTELSMEIER C, LEADLEY P, THUILLER W & COURCHAMP F. 2012. Impacts of climate change on the future of biodiversity. Ecol Lett 15: 365-377.), including studies with animal (Crick 2004CRICK HKP. 2004. The impact of climate change on birds. Ibis 146: 48-56., Ribeiro et al. 2018RIBEIRO BR, SALES LP & LOYOLA R. 2018. Strategies for mammal conservation under climate change in the Amazon. Biod Cons 27: 1943-1955., Miranda et al. 2019MIRANDA LS, IMPERATRIZ-FONSECA VL & GIANNINI TC. 2019. Climate change impact on ecosystem functions provided by birds in southeastern Amazonia. Plos One 11: 1-17.) and plant assemblages (Siqueira & Durigan 2007SIQUEIRA MF & DURIGAN G. 2007. Modelagem da distribuição geográfica de espécies lenhosas de cerrado no Estado de São Paulo. Rev Bras Bot 30: 233-243., Simões et al. 2019SIMÕES 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. Aus Ecol x:1-13.).

Biological interaction with climate is observed in geophysical patterns of vegetation distribution, reflecting different bioclimatic zones (Salazar et al. 2007SALAZAR LF, NOBRE CA & OYAMA MD. 2007. Climate change consequences on the biome distribution in tropical South America. Geo Res Let 34: L09708.). Within the South American climate ranges, Amazônia and Cerrado are the predominant biomes. They are also largely deforested, which has led to worsening climate change because the removal of vegetation cover promotes a warmer and drier regional climate (Nobre et al. 2008NOBRE CA, SAMPAIO G & SALAZAR L. 2008. Cenários de mudança climática para a América do Sul para o final do século 21. Parc Estrat 13: 27-35.). However, although some evidence of current extinctions is correlated with climate change, studies suggest that climate phenomena could outweigh habitat destruction as the greatest global threat to biodiversity in the coming decades (Pereira et al. 2010PEREIRA HM, LEADLEY PW, PROENÇA V, ALKEMADE R, SCHARLEMANN JPW, FERNANDEZ-MANJARRES JF & WALPOLE M. 2010. Scenarios for global biodiversity in the 21st century. Sci 10: 1496-1501., Bellard et al. 2012BELLARD C, BERTELSMEIER C, LEADLEY P, THUILLER W & COURCHAMP F. 2012. Impacts of climate change on the future of biodiversity. Ecol Lett 15: 365-377.).

Studies on Quaternary climate fluctuations and vegetation in Brazil confirm that successive expansions and retractions occurred between forests and savannas (Silva & Bates 2002SILVA JMC & BATES JM. 2002. Biogeographic patterns and conservation in the South American Savanna: a tropical savanna hotspot. BioSci 52: 225-234., Werneck et al. 2012WERNECK FP, NOGUEIRA C, COLLI GR, SITES JW & COSTA GC. 2012. Climatic stability in the Brazilian Savanna: implications for biogeographical connections of South American savannas, species richness and conservation in a biodiversity hotspot. J Biog 39: 1695-1706., Bueno et al. 2016BUENO ML, PENNINGTON RT, DEXTER KG, KAMINO LHY, PONTARA V, NEVES DM, RATTER JA & OLIVEIRA-FILHO AT. 2016. Effects of Quaternary climatic fluctuations on the distribution of Neotropical savanna tree species. Ecogr 40: 403-414.), the main habitat typologies in Brazil. Cerrado is the largest forest savanna in South America, covering 21% of the country’s land area and extending marginally into Paraguay and Bolivia, behind only the Amazon Forest in terms of extension (CI 2019CI. 2019. Conservation Internacional. Biodiversity Hotspots - Savanna. Retrieved from http://www.biodiversityhotspots.org/xp/Hotspots/savanna/Pages/default.aspx.
http://www.biodiversityhotspots.org/xp/H...
). Research in tropical South America has shown Brazil as a region where significant amounts of forests are converted into non-forest areas as a result of global warming (Ledru 2002LEDRU MP. 2002. Late Quaternary history and evolution of the savannas as revealed by palynological records. In: Oliveira PS & Marquis RJ (Eds), The savannas of Brazil - Ecology and natural history of neotropical savanna. Columbia, NY: University of New York Press, p. 33-50., Sanaiotti et al. 2002SANAIOTTI TM, MARTINELLI LA, VICTORIA RL, TRUMBORE SE & CAMARGO PB. 2002. Past vegetation changes in Amazon savannas determined using carbon isotopes of soil organic matter. Biot 34: 2-16., Salazar et al. 2007SALAZAR LF, NOBRE CA & OYAMA MD. 2007. Climate change consequences on the biome distribution in tropical South America. Geo Res Let 34: L09708.). Field observations and numerical models also indicate loss of tropical forest cover (Soares-Filho et al. 2006SOARES-FILHO B, NEPSTAD D, CURRAN L, CERQUEIRA GC, GARCIA RA, RAMOS CA & SCHLESINGER P. 2006. Modelling conservation in the Amazon basin. Nat 440: 520-523., Vale et al. 2008VALE MM, COHN-HAFT M, BERGEN S & PIMM SL. 2008. Effects of future infrastructure development on threat status and occurrence of Amazonian birds. Cons Biol 22: 1006-1015., Rochedo et al. 2018ROCHEDO PRR, SOARES-FILHO B, SCHAEFFER R, VIOLA E, SZKLO A, LUCENA AFP & RATHMANN R. 2018. The threat of political bargaining to climate mitigation in Brazil. Nat Clim Chang 8: 695-698., Gomes et al. 2019GOMES VHF, VIEIRA ICG, SALOMÃO RP & STEEGE H. 2019. Amazonian tree species threatened by deforestation and climate change. Nat Clim Chang 9: 547-553.), replaced by savannas (Salazar et al. 2007SALAZAR LF, NOBRE CA & OYAMA MD. 2007. Climate change consequences on the biome distribution in tropical South America. Geo Res Let 34: L09708.); this potential reorganization of the distribution of biodiversity can affect the structure, dynamics and functioning of ecosystems and their respective contributions (Gallagher et al. 2013GALLAGHER RV, HUGHES L & LEISHMAN MR. 2013. Species loss and gain in communities under future climate change: consequences for functional diversity. Ecogr 36: 531-540.).

Research about spatiotemporal ecological representations of species has increased considerably in recent years with the advancement of geoprocessing and species distribution modeling tools by ecologists and conservation managers, and thus the need to provide efficient assessments of these predictive models (Teles 1996TELES HMS. 1996. Distribuição de Biomphalaria straminea ao Sul da Região Neotropical, Brasil. Rev Saúd Púb 30: 341-349., Allouche et al. 2006ALLOUCHE O, TSOAR A & KADMON R. 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J Appl Ecol 43: 1223-1232.). Species Distribution Models (SDMs) allow spatial extrapolation of known occurrence records at different scales and generate potential distribution maps based on the effects of climate change on species distribution (Teles 1996TELES HMS. 1996. Distribuição de Biomphalaria straminea ao Sul da Região Neotropical, Brasil. Rev Saúd Púb 30: 341-349., Costa et al. 2012bCOSTA TRN, CARNAVAL ACOQ & TOLEDO LF. 2012b. Mudanças climáticas e seus impactos sobre os anfíbios brasileiros. Rev 8: 33-37., Oliveira & Cassemiro 2013OLIVEIRA HR & CASSEMIRO FAS. 2013. Potenciais efeitos das mudanças climáticas futuras sobre a distribuição de um anuro da Caatinga Rhinella granulosa (Anura, Bufonidae). Ihering 103: 272-279.).

Although the assessment of the effects of climate change on Brazilian biodiversity is increasing in all biomes, especially those predominantly forested and with greater species richness and endemism (Amazon and Atlantic Forest) (Aleixo et al. 2010ALEIXO ALP, ALBERNAZ AL, GRELLE CEV, VALE MM & RANGE TF. 2010. Mudanças climáticas e a biodiversidade dos biomas brasileiros: passado, presente e futuro. Natur Conserv 8: 194-196.), there are few attempts to predict the impacts on non-forest areas (Siqueira & Peterson 2003SIQUEIRA MF & PETERSON AT. 2003. Consequences of global climate change for geographic distributions of cerrado tree species. Bio Neotr 3: 1-14., Terribile et al. 2012TERRIBILE LC, LIMA-RIBEIRO MS, ARAÚJO MB, BIZÃO N, COLLEVATTI RG, DOBROVOLSKI R & DINIZ-FILHO JAF. 2012. Areas of Climate Stability of Species Ranges in the Brazilian Savanna: Disentangling Uncertainties Through Time. Natur & Conser 10: 152-159.). High levels of environmental devastation have made Cerrado to be included in the list of biodiversity hotspots (Myers et al. 2000MYERS N, MITTERMEIER RA, MITTERMEIER CG, FONSECA GAB & KENT J. 2000. Biodiversity hotspots for conservation priorities. Nat 403: 853-858., CI 2019CI. 2019. Conservation Internacional. Biodiversity Hotspots - Savanna. Retrieved from http://www.biodiversityhotspots.org/xp/Hotspots/savanna/Pages/default.aspx.
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), and yet minimal (scientific and political-social) attention has been given to the marginal and disjunct patches of the Cerrado of the North and Northeast, called the modern Brazilian agricultural frontier. They refer, in large part, to “MATOPIBA”, a portion of the North and Northeast savannas with more than 73 million hectares (8.5% of the Brazilian territory), recognized as the portion between the states of Maranhão, Tocantins, Piauí and Bahia (Heck & Menezes 2016HECK E & MENEZES L. 2016. MATOPIBA: projeto de destruição do Cerrado. Porantim 37: 8-9.) that accounts for much of Brazil’s grain and fiber production (https://www.embrapa.br/tema-matopiba).

Despite its importance, there is a growing concern with maintaining biodiversity and understanding the ecological relationships among local species, intensified by projections of climate scenarios. In order to support conservation strategies in this ecological transition region in central-north Brazil (from the Amazon to the Brazilian Sertão), this research applied spatial analysis procedures and modeling tools to predict the potential distribution of a representative set of common species considering the entire Cerrado biome (generalists”) and another representative set of species most frequently associated with the marginal and disjunct areas of the biome (“marginals). Our hypothesis is that the “generalists” will be favored by a scenario of increased temperatures, especially in ecotonal areas replacing forest formations, but marginal species may suffer losses from climatically suitable areas.

Based on the physical-environment (thematic maps) and biological (species occurrence) variables of the current times, algorithms were applied in order to model the fundamental niche and the potential area of occurrence of the species. The following questions were investigated in this study: based on the potential current occurrence range of the target species, do the impacts of future climate change on their distribution predict retraction or expansion of the forecasted occurrence of the central-north peripheral Cerrado? Do predictions of future occurrence among species of wide geographical distribution (“generalists”) differ from those most frequent in the northern portion of the Biome “marginals’)? Are environmentally stable areas of future predicted scenarios located inside Protected Areas (PAs) at present? In this context, this study aimed to estimate the impact of climate change on the future extent of occurrence of peripheral Cerrado of central-north Brazil.

MATERIALS AND METHODS

Focal area

The geographic area investigated belongs to the central-north region of Brazil, focusing on marginal and disjunct savannas in relation to the continuous block of the Cerrado biome. The aim was to investigate the effects of climate change on different vegetation types showing the influence of adjacent phytogeographic domains. Projections and analyses are mainly concentrated in the North and Northeast regions (approximate limits 6°N, 19°S, 74°O and 34°O), covering the Amazon, Cerrado, Caatinga and their ecotonal areas, involving natural climatic boundaries between rainforests, savannas and semi-arid steppes (IBGE 2012IBGE. 2012. Instituto Brasileiro de Geografia e Estatística. Manuais técnicos em geociências: manual técnico da vegetação brasileira. Rio de Janeiro.). The studied area is one of the Cerrado’s biodiversity and endemism supercenters, but lacks information on primary biological data, and therefore represents a preferred target for inventories (Vieira et al. 2019VIEIRA LTA, COSTA-COUTINHO JM, CASTRO AAJF & MARTINS FR. 2019. A biogeographic and evolutionary analysis of the flora of the North-eastern savanna, Brazil. Plant Ecol & Divers 12: 475-488.).

Data selection

Species lists were initially obtained from floristic data networks from Cerrado areas (http://savanna.rbge.org.uk, Ratter et al. 2011RATTER JA, BRIDGEWATER S, RIBEIRO JF, FONSÊCA-FILHO J, RODRIGUES DA SILVA M, MILLIKEN W & PENNINGTON RT. 2011. Analysis of the floristic composition of the Brazilian Savanna vegetation IV: revision of the comparison of the woody vegetation of 367 areas and presentation of a revised data-base of 367 areas. Royal Bot Gard Edinb, Retrieved from http://savanna.rbge.org.uk.
http://savanna.rbge.org.uk...
, Castro et al. 2010CASTRO AAJF, BARROS, JS, COSTA, JM, SANTOS MPD, PIRES MFO, MENDES MRA & SOUSA SR. 2010. Cerrados marginais do Nordeste e ecótonos associados: sítio 10 do PELD (Período 2001/2011). Teresina: EDUFPI/Gráfica do Povo, 56 p., Vieira et al. 2019VIEIRA LTA, COSTA-COUTINHO JM, CASTRO AAJF & MARTINS FR. 2019. A biogeographic and evolutionary analysis of the flora of the North-eastern savanna, Brazil. Plant Ecol & Divers 12: 475-488.). In addition, twenty-one areas were sampled in the northern region of Cerrado (in the states of Piauí, Maranhão, Pará and Amapá; data available at https://doi.org/10.5061/dryad.9cnp5hqd4). To test our hypothesis, we divided the species on these lists into two groups that we will refer to here as “generalists” (SpG) and “marginals” (SpM). First, all species on the lists (N=235) were ranked according to their constancy value and the first five were selected as representatives of the generalist group (Bowdichia virgilioides [754 occurrences], Byrsonima crassifolia [523], Qualea grandiflora [858], Q. parviflora [727], Salvertia convallariodora [561]; Table I). Then, from the lists of the northern region of Cerrado inventories, the species were ranked by importance value and the five were selected (Curatella americana [956], Himatanthus articulatus [441], Parkia platycephala [259], Plathymenia reticulata [604], and Vatairea macrocarpa [413] (Table I).

Table I
Species and metrics used in modeling the potential distribution of northern savannahs in the Cerrado Biome. Nocc: number of occurrences; Status: generalist (Gen), disjunct northern savannah (SD) and marginal northern savannah (SM); Model performance parameters: ROC, TSS, Cut-off threshold (limit values maximized by TSS for binarization), Sensitivity, Specificity; Extension, difference, and proportion of the projected area according to the scenarios. Highlight: gain (blue) or loss (red) of environmental suitability area.

Several ecological indexes in taxocenoses of woody plants (constancy, diversity, richness, evenness, and importance value index - IV) ware used as indicators of environmental degradation through the analysis of standardized. IV is an estimator of the ecological importance of taxon within a forest community, calculated as the sum of the relative density, relative dominance and relative frequency of a given species (see Costa-Coutinho et al. 2019COSTA-COUTINHO JM, JARDIM MAG, CASTRO AAJF & VIANA-JUNIOR AB. 2019. Conexões biogeográficas de savanas brasileiras: partição da diversidade marginal e disjunta e conservação do trópico ecotonal septentrional em um hotspot de biodiversidade. Rev Bras Geog Fís 2: 2406-2427., 2021COSTA-COUTINHO JM, COSTA-NETO SV & JARDIM MAG. 2021. Florística e estrutura do estrato arbóreo em cinco savanas no estado do Pará, Brasil. Rev Bras Geog Fís 14: 215-228.) for more details on the ten species selection criteria.

Finally, in addition to inventory and field survey data, occurrence records of these species were obtained from the Global Biodiversity Information Facility open access platform (http://gbif.org) using the rgbif package (Chamberlain et al. 2019CHAMBERLAIN S, BARVE V, MCGLINN D, OLDONI D, DESMET P, GEFFERT L & RAM K. 2019. rgbif: interface to the Global Biodiversity Information Facility API. R package version 1.3.0. Retrieved from https://CRAN.R-project.org/package=rgbif.
https://CRAN.R-project.org/package=rgbif...
) in R (R Development Core Team 2019R DEVELOPMENT CORE TEAM. 2019. R: A language and environment for statistical computing. Viena: R Foundation for Statistical Computing, Vienna, Austria. Retrieved from https://www.R-project.org/.
https://www.R-project.org/...
). In addition, three pseudo-absence/background databases were created containing ten times the number of occurrences and arranged outside the minimum convex polygon containing the occurrences.

The total known area occurences of each species in South America was used for the model fitting process (see below), as it represents the complete up-to-date data available from the species. We excluded non-georeferenced records, and those outside the expected distribution for the species (through visual inspection), and we kept only records 1 km apart from each other, to minimize the spatial autocorrelation. Although typical of Cerrado, they are plants also recorded in ecotonal areas under the influence of neighboring domains, and for this reason we double checked the records based on the checklist of the present study, in the revised floristic lists of Castro et al. (2010)CASTRO AAJF, BARROS, JS, COSTA, JM, SANTOS MPD, PIRES MFO, MENDES MRA & SOUSA SR. 2010. Cerrados marginais do Nordeste e ecótonos associados: sítio 10 do PELD (Período 2001/2011). Teresina: EDUFPI/Gráfica do Povo, 56 p., Ratter et al. (2011)RATTER JA, BRIDGEWATER S, RIBEIRO JF, FONSÊCA-FILHO J, RODRIGUES DA SILVA M, MILLIKEN W & PENNINGTON RT. 2011. Analysis of the floristic composition of the Brazilian Savanna vegetation IV: revision of the comparison of the woody vegetation of 367 areas and presentation of a revised data-base of 367 areas. Royal Bot Gard Edinb, Retrieved from http://savanna.rbge.org.uk.
http://savanna.rbge.org.uk...
, Vieira et al. (2019)VIEIRA LTA, COSTA-COUTINHO JM, CASTRO AAJF & MARTINS FR. 2019. A biogeographic and evolutionary analysis of the flora of the North-eastern savanna, Brazil. Plant Ecol & Divers 12: 475-488. and the Species List of the Brazilian Flora (BFG 2018BFG. 2018. The Brazil Flora Group. Brazilian Flora 2020: Innovation and collaboration to meet target 1 of the Global Strategy for Plant Conservation (GSPC). Rodrig 69: 1513-1527., http://floradobrasil.jbrj.gov.br). The final database included 6,106 presence records (ranging from 256 to 956) for the ten native species of Brazil, which were significantly represented in Cerrado sites.

WorldClim data on current climate and projections for 2050 (http://worldclim.org, Fick & Hijmans 2017FICK SE & HIJMANS RJ. 2017. Worldclim 2: new 1-km spatial resolution climat surfaces for global land areas. Intern Journ Climatol 37: 4302-4315.), at a resolution of 30 arcseg (about 1 km²) within the spatial boundaries of South America (12°N, 56°S, 91°O, 34°O) were used for the purpose of creating ecological niche models (ENMs). This extension was used to capture the spectrum of climate variation for the entire known distribution of species. Among the 20 variables (altitude and 19 bioclimatic variables), the least collinear variables were selected using the remove Collinearity function (multicollinearity.cutoff = 0.75, nb.points = 10000) from the virtual species package (Leroy et al. 2015LEROY B, MEYNARD CN, BELLARD C & COURCHAMP F. 2015. “Virtualspecies, an R package to generate virtual species distributions.” Ecography. Retrieved from https://doi.org/10.1111/ecog.01388): altitude, annual mean temperature, max temperature of warmest month, isothermality, mean diurnal range, precipitation of coldest quarter, annual precipitation, precipitation of warmest quarter, precipitation seasonality, and precipitation of driest quarter.

Future climate projections were derived from two global atmosphere-ocean circulation models (AOGCM) - the Community Climate System Model (CCSM4) and the Hadley Center Global Environmental Model (HadGEM2-CC) - in two greenhouse gas concentration pathways (RCPs 4.5 and 8.5) foreseen by the Fifth Assessment (CMIP5) of the Intergovernmental Panel on Climate Change (IPCC 2018), representing an optimistic achievable scenario and a “business-as-usual” scenario.

Modeling runs and analyses

To estimate the potential distribution of species, ENMs were generated in the biomod2 package (Thuiller et al. 2019THUILLER W, GEORGES D, ENGLER R & BREINER F. 2019. biomod2: Ensemble Platform for Species Distribution Modeling. R package version 3.3-7.1. Retrieved from https://CRAN.R-project.org/package=biomod2.
https://CRAN.R-project.org/package=biomo...
) by running four different algorithms: Generalized Linear Model (GLM), Artificial Neural Network (ANN), Random Forest (RF), and Maximum Entropy (MAXENT). All parameters for models tuning and selection were left in default mode. Species datasets (presence + pseudo-absence records) were randomly divided into 75% for calibration (training points) and 25% for evaluation (test points) and this procedure was repeated 10 times for each set. To assess the predictive power of the models, the True Skill Statistics (TSS; threshold-dependent) values (Allouche et al. 2006ALLOUCHE O, TSOAR A & KADMON R. 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J Appl Ecol 43: 1223-1232.) and the area under the receiver operating characteristic (ROC) curve (Phillips et al. 2006PHILLIPS SJ, ANDERSON RP & SCHAPIRE RE. 2006. Maximum entropy modeling of species geographic distributions. Ecol Model 190: 231-259.) were measured. Sensitivity (proportion of correctly predicted presences/true positives) and specificity (proportion of correctly predicted absences/true negatives) levels were also reported.

The consensus maps were generated by the committee averaging method to represent the concordances between the different runs. The lower performing models (TSS < 0.5) were eliminated from the consensus building process (ensemble). Thus, five consensus maps were generated per species for each scenario (one current, two RCP 4.5 and two RCP 8.5). Continuous habitat suitability values were transformed into binary data (presence/absence) using a cut-off threshold that maximized TSS (see Cutoff in Table I) and the projected area of occurrence was calculated by multiplying the cell area (considered 1x1km) by the cell count.

We also measured the potential dynamics of change in the range extension (area gain/loss) of the species based on the differences between the projected area for current and each future climate scenario. This analysis was made for each species separately, to recognize ecological functional differences between plant populations. The amount of areas with greater climate stability (referred to as refuges in the present study) was calculated from the amount of pixels considered as presence when overlapping the models of all scenarios – individually, by category (generalist [SpG] and marginal [SpM]), and altogether. Based on these refuge maps, the future effectiveness of present PAs from a climate change perspective was measured, accounting for the size of refuge areas for SpG and SpM and both which overlap with the PAs. The data of the Brazilian PAs were obtained from the website of the Ministry of Environment (http://mapas.mma.gov.br).

The modeling results were visualized through the QGIS Geographic Information System (QGIS 2019) and analyzed using the R Statistical environment and the raster library). All the procedures described above were chosen to balance the best practices of the method (Feng et al. 2019FENG X, PARK DS, WALKER C, PETERSON AT, MEROW C & PAPEŞ M. 2019. A checklist for maximizing reproducibility of ecological niche models. Nat Ecol Evol 3: 1382-1395.) with computational feasibility issues.

RESULTS

The models demonstrated high levels of accuracy according to the TSS (0.86 - 0.90) and ROC (all values 0.99), indicating models with predictive quality (Table I). The area for current projections between SpG and SpM species showed high variation (SpG: from 3.5 to 7.0 million km² and SpM: from 2.0 to 7.2 million km²). Estimates made by AOGCM institutions, in general, maintained consistency, but the highest rates of change with more hostile effects were recorded by CCSM4 (CC) (Figure 1).

Figure 1
Climate stability models for the 10 woody species of the Cerrado in current and future climate change scenarios (2050) (RCP 4.5 and 8.5), according to the global climate models (GCM) CCSM4 (CC) and HadGEM2-CC (HG). Warmer colors represent greater environmental suitability predicted by species for each scenario.

Considering the maps with continuous suitability values, the areas with the highest rating (red color) in the future will be reduced, fragmented and/or displaced in relation to the present, regardless of whether they are SpG or SpM. However, considering cut-off thresholds for the presence (i.e., the binary maps), our results pointed to a tendency to increase the suitable areas in the future, which is greater in the worst scenario (i.e., 2050 RCP 8.5). Only two species, S. convallariodora and H. articulatus showed loss of adequate areas in future projections of different scenarios (Figure 2). Much of the future projections remain in the areas dominated by Brazilian Cerrado, but potentially invasions in the adjacent biomes can occur, especially in the Amazon (Figure 1). This means that the marginal savanna region in central north Brazil would gain adequate areas. And more interestingly, both categories will be affected virtually the same way (i.e., gain of area). Still regarding future projections, it is worth noting a southwestward shift, with increased extensions in the states of Mato Grosso, Rondônia and Acre, and Bolivia.

Figure 2
Potential change in the area by species in different scenarios of future climate change (2050; GCMs CC and HG; RCP 4.5 and RCP 8.5). Blue: expansion; red: retraction. * Marginal species typical of the northern savannahs.

In general, the results of binary maps showed that most projected species are actually being favored with increased potential suitable area in the future. The average gain was of 18.5% in the most optimistic scenario (2050; RCP 4.5) and 26.9% in the worst (2050; RCP 8.5). Comparing the species, H. articulatus had the largest environmentally suitable area predicted in the current scenario, followed by B. crassifolia, C. americana and B. virgilioides. However, three species showed a loss of spatial range: S. convallariodora (SpG) showed 11% reduction in the less pessimistic and 16% in the most pessimistic scenarios; H. articulatus (SpM), also showed between 6 and 14% loss in three of the five scenarios; and there was a similar prediction for P. reticulata (between 3 and 11% loss) in two out the five scenarios.

The distribution of refuge areas varies enormously (Figure 3). For instance, considering the SpGs, virtually the entire Brazilian Cerrado region will continue to be suitable in the future, regardless of the scenario, in addition to the western Mato Grosso, Rondônia, in Brazil and the border areas in Bolivia (Figure 3). In contrast, the SpMs’ refuge areas are concentrated in the central-north portion of Brazil (i.e., in the south of Maranhão, in the north of Tocantins and in the west of Piauí), highlighting that despite having projected an increase in the range (except H. articulatus and P. reticulata), this will occur in non-coincident portions with the current range. Thus, influenced by marginal species, refuge areas considering all species are in this central-north portion of Brazil. In future projections, the 278 protected areas of different categories that overlapped the focal areas will house only 4.6% (5,634 km²) of our projected refuges. Less than 10 current PAs are found specifically in refuge areas that encompass all species, the largest being the Ilha do Bananal/Cantão State Environmental Protection Area in Tocantins and the Chapada das Mesas National Park in southern Maranhão (1.7 million hectares). Only 4.8% (7,822 km²) and 8.1% (142,196 km²) of the marginal and generalist species, respectively, will be protected inside PAs (Figure 3).

Figure 3
Potentially stable climatic areas for conservation actions. Map of species overlap in the four scenarios indicating more stable climatic areas (refuges, in blue) for generalist (SpG) and marginal (SpM) species. Color scales represent overlapping models. The areas were plotted with existing protected areas. The values refer exclusively to the northern region. The table represents the absolute (km²) and relative (%) extent of occurrence of species in protected areas based on the current distribution scenario.

DISCUSSION

The results of this study demonstrate that, even in the most optimistic climate change scenarios (i.e., RCP 4.5), climate requirements will potentially have a strong effect on woody assemblages of savannas from the central-north portion of Brazil in the near future (2050). The ENMs estimated changes in the spatial pattern of habitat suitability for the species and flora composition at macro-regional scale and showed that 70% of the species will occupy new niches and 30% will have smaller ideal ranges. In addition, very few climatically stable areas for the occurrence of these species are under protection.

The understanding of biogeographic processes such as dispersal of organisms, emergence of barriers that promote vicariance, and generation of new lineages and species (cladogenesis), makes it clear that climate change is central to these evolutionary processes, triggering the origin and extinction of organisms within a given historical context (Haffer 2008HAFFER J. 2008. Hypotheses to explain the origin of species in Amazonia. Braz J Biol 68: 917-947.). Some hypotheses (such as Pleistocene refuges and Disturbance-vicariance) have been proposed to explain the great contemporary Neotropical and Brazilian biodiversity (Haffer 2008HAFFER J. 2008. Hypotheses to explain the origin of species in Amazonia. Braz J Biol 68: 917-947., Aleixo et al. 2010ALEIXO ALP, ALBERNAZ AL, GRELLE CEV, VALE MM & RANGE TF. 2010. Mudanças climáticas e a biodiversidade dos biomas brasileiros: passado, presente e futuro. Natur Conserv 8: 194-196.). Heating and cooling cycles are thought to have triggered adaptive processes in different biological groups in the numerous paleogeographic phases.

Episodes of retraction and expansion of forest and open formations combined with isolation and speciation would have affected Cerrado biodiversity (Silva & Bates 2002SILVA JMC & BATES JM. 2002. Biogeographic patterns and conservation in the South American Savanna: a tropical savanna hotspot. BioSci 52: 225-234., Haffer 2008HAFFER J. 2008. Hypotheses to explain the origin of species in Amazonia. Braz J Biol 68: 917-947., Werneck et al. 2012WERNECK FP, NOGUEIRA C, COLLI GR, SITES JW & COSTA GC. 2012. Climatic stability in the Brazilian Savanna: implications for biogeographical connections of South American savannas, species richness and conservation in a biodiversity hotspot. J Biog 39: 1695-1706., Bueno et al. 2016BUENO ML, PENNINGTON RT, DEXTER KG, KAMINO LHY, PONTARA V, NEVES DM, RATTER JA & OLIVEIRA-FILHO AT. 2016. Effects of Quaternary climatic fluctuations on the distribution of Neotropical savanna tree species. Ecogr 40: 403-414.). Therefore, understanding how species might respond to climate changes predicted to occur in the coming years is pivotal to formulate actions of management and conservation of biodiversity. Greater turnover can be expected in future savanna domains in response to climate change, especially in areas with marked west-east moisture gradient (Davidson et al. 2012DAVIDSON EA, ARAÚJO AC, ARTAXO P, BALCH JK, BROWN IF, BUSTAMANTE MMC & WOFSY SC. 2012. The Amazon basin in transition. Nat 481: 321-328.), such as in central-north Brazil. In addition, recent works indicate that this area is more sensitive to global climate change due to the current high rates of deforestation and landscape transformation (Salazar et al. 2007SALAZAR LF, NOBRE CA & OYAMA MD. 2007. Climate change consequences on the biome distribution in tropical South America. Geo Res Let 34: L09708., Malhi et al. 2008MALHI Y, ROBERTS JT, BETTS RA, KILLEEN TJ, LI W & NOBRE CA. 2008. Climate Change, Deforestation, and the Fate of the Amazon. Sci 319: 169-172., IPCC 2018). Although the species are typical of savanna, they are recorded in ecotonal areas under the influence of neighboring domains (BFG 2018BFG. 2018. The Brazil Flora Group. Brazilian Flora 2020: Innovation and collaboration to meet target 1 of the Global Strategy for Plant Conservation (GSPC). Rodrig 69: 1513-1527.) and, as they are heliophilous plants, we had predicted that they will potentially respond by expanding their habitats, possibly increasing competition between floras within and between biomes.

All of our “generalist” species (SpG) demonstrated little change in their ranges according to our models, which can be interpreted as a sign of resilience given the projections of environmental changes mainly in the central-north region of Brazil. For instance, considering only the climate factor, the Climate Observatory/SEEG (http://www.observatoriodoclima.eco.br) forecasts a 72% increase over the average temperature and a decrease in precipitation, with the most negative trends in the Cerrado and the Amazon (Azevedo et al. 2018AZEVEDO TR, COSTA JUNIOR C, BRANDÃO JUNIOR A, CREMER MS, PIATTO M, TSAI DS & KISHINAMI R. 2018. SEEG initiative estimates of Brazilian greenhouse gas emissions from 1970 to 2015. Sci Data 5: 180045., Penereiro et al. 2018PENEREIRO JC, BADINGER A, MACCHERI NA & MESCHIATTI MC. 2018. Distribuições de tendências sazonais de temperatura média e precipitação nos biomas brasileiros. Rev Bras Met 33: 97-113.). Similar projections were observed for the “marginal” species (SpM), although, S. convallariodora, H. articulatus and P. reticulata may lose their climate suitability, be restricted to alternative stable states and adopt new environmental equilibrium ranges. Beisner et al. (2003)BEISNER BE, HAYDON DT & CUDDINGTON K. 2003. Alternative stable states in ecology. Front Ecol Environ 1: 376-382. discussed the perspectives of alternative stable states that suggest that resilience can be achieved either by adaptive changes (i.e., “shifts in variables” according to the authors), which seems to be the case with SpG, or by anticipating changes in the environment through changes in the range (i.e., “shifts in parameters”), as seems to be the case with SpM.

Most species showed spatial range gain in the projections, suggesting that there will be minimal survival conditions for these heliophilous species. This corroborates the assumption of expansion of xeric environments possibly initiated in the Holocene and maintained in the present period (Simões et al. 2019SIMÕES 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. Aus Ecol x:1-13.). Although, the idiosyncratic response of some species (three species showed decreased projected area) reflects the lack of a pattern in the scenarios and indicates that climate change will have a variable influence on the varied plant communities of Cerrado.

Actually, the difficulty of native floras to adapt to climate change tends to aggravate the natural habitats degradation in a few decades. Even widely distributed species can have population sizes reduced in some areas and suffer local extinction in others, in long time series with seasonal tendency to aridity (Simões et al. 2019SIMÕES 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. Aus Ecol x:1-13.). It can be extrapolated that the structural simplification, increased mortality, and reduced average plant density are indicators of changes caused by the “desertification” of the northeastern savannas and semi-arid steppes, the “savannization” of the Amazon, and the “erosion” of central Cerrado, contributing in all cases to the contemporary reduction of phylogenetic diversity and to new patterns of ecological niches (Costa et al. 2012aCOSTA JLPO, VELOSO FILHO FA, AQUINO CMS & CASTRO AAJF. 2012a. Visão geral da biogeografia e dos sistemas universais de classificação fitogeográfica. Geogr Public Avul 10: 5-22., Terribile et al. 2012TERRIBILE LC, LIMA-RIBEIRO MS, ARAÚJO MB, BIZÃO N, COLLEVATTI RG, DOBROVOLSKI R & DINIZ-FILHO JAF. 2012. Areas of Climate Stability of Species Ranges in the Brazilian Savanna: Disentangling Uncertainties Through Time. Natur & Conser 10: 152-159.).

Long-term drought experiments in the Amazon have shown considerable niche resilience to natural climatic variation, but interactions between climate change, deforestation, fire, and potential carbon storage discharge and precipitation lead to an increasingly vulnerable ecosystem (Davidson et al. 2012DAVIDSON EA, ARAÚJO AC, ARTAXO P, BALCH JK, BROWN IF, BUSTAMANTE MMC & WOFSY SC. 2012. The Amazon basin in transition. Nat 481: 321-328.). Although the climate is a predominant driver of community changes, several current factors operate in the disturbance of habitats, preventing the recovery and/or natural growth of landscapes and interfering with the real environmental suitability. Under the conditions analyzed in this study, all species are expected to find adequate habitats in the central-north Brazil, even in the worst climate scenario. However, it is noteworthy that other environmental and anthropogenic complications were not considered, neither the inherent biological relationships of inter-population nor intra-ecosystem interactions. Research has indicated the importance of soils in the distribution of plant species (Siqueira & Durigan 2007SIQUEIRA MF & DURIGAN G. 2007. Modelagem da distribuição geográfica de espécies lenhosas de cerrado no Estado de São Paulo. Rev Bras Bot 30: 233-243.), but edaphic variables were not included in the models of northern Cerrado, because previous analyses pointed to the topographic and climatic attributes as the main predictors of these savannas (Costa-Coutinho et al. 2019COSTA-COUTINHO JM, JARDIM MAG, CASTRO AAJF & VIANA-JUNIOR AB. 2019. Conexões biogeográficas de savanas brasileiras: partição da diversidade marginal e disjunta e conservação do trópico ecotonal septentrional em um hotspot de biodiversidade. Rev Bras Geog Fís 2: 2406-2427., 2021).

In addition, this data also showed less relevance to edaphic aspects, which are subordinated to climate variations, especially the high rainfall regime of Amazonian savannas, drought and sharp thermal amplitude in the northeastern savannas. Similarly, through a modeling study in the Amazon-Cerrado transition, Dionizio et al. (2018)DIONIZIO EA, COSTA MHC, CASTANHO AA, PIRES GF, MARIMON BS, MARIMON-JUNIOR BH & JAIN AKM. 2018. Influence of climate variability, fire and phosphorus limitation on the vegetation structure and dynamics in the Amazon-Savanna border. Biogeosc 15: 919-936. found that the dynamics of environmental effects along the latitude-longitudinal gradient are particularly due to climate, and then due to the frequency of fires and phosphorus limitation in the soil.

The dynamics of environmental suitability are most likely to decrease in the Amazon-Cerrado border, where deforestation is greatest and where climate and plant diversity move between ecosystems (Davidson et al. 2012DAVIDSON EA, ARAÚJO AC, ARTAXO P, BALCH JK, BROWN IF, BUSTAMANTE MMC & WOFSY SC. 2012. The Amazon basin in transition. Nat 481: 321-328.). In line with these authors, lower precipitation in these ecotones will make the conditions between forest (short drought) and Cerrado (long drought) less limiting, promoting its expansion.

ENMs in Cerrado plant lineages gives an idea of the susceptibility of this Biome to current trends in climate change and, ultimately, about land use changes, since a considerable part of Brazil’s greenhouse gas emissions originates from habitat degradation. The present study show that the largest inclusive extent of the projected refuge will potentially be concentrated in the center of the focal area, coinciding with one of the “subhotspots” of the biome (i.e., supercenters of Cerrado biodiversity), and considered by Castro & Martins (1999)CASTRO AAJF & MARTINS FR. 1999. Cerrados do Brasil e do Nordeste: caracterização, área de ocupação e considerações sobre a sua fitodiversidade. Pesq Foc 7: 147-178. as the savanna’s peripheral limits with high. The lower and plastic diversity is expected from peripheral floras in fragmented, ecotonal habitats with high structural complexity acting as environmental filters that cause the homogenization of diversity (Kortz & Magurran 2019KORTZ AR & MAGURRAN AE. 2019. Increases in local richness (α-diversity) following invasion ares offset by biotic homogenization in a biodiversity hotspot. Biol Lett 15: 20190133.). But as the models show, for the species analyzed, many of these areas will provide the ideal conditions for some savanna communities.

The prediction of the real influence of environmental changes on the different elements that act on plant diversity is based on conjectures and are conditioned to fluctuations in direct (e.g., temperature, CO2 emission, solar radiation, precipitation, sea ice extent) and indirect (e.g., food availability, pests, soil moisture, sea level) components that impact biodiversity (IPCC 2018). According to Costa et al. (2012a)COSTA JLPO, VELOSO FILHO FA, AQUINO CMS & CASTRO AAJF. 2012a. Visão geral da biogeografia e dos sistemas universais de classificação fitogeográfica. Geogr Public Avul 10: 5-22., the latest diversification cycles of some biological groups were correlated with recent climate changes; for other groups, though, such changes contributed little to today’s richness and geographical distribution. Terribile et al. (2012)TERRIBILE LC, LIMA-RIBEIRO MS, ARAÚJO MB, BIZÃO N, COLLEVATTI RG, DOBROVOLSKI R & DINIZ-FILHO JAF. 2012. Areas of Climate Stability of Species Ranges in the Brazilian Savanna: Disentangling Uncertainties Through Time. Natur & Conser 10: 152-159. consider appropriate to examine both the past and the future to map the most likely areas of savanna in the future. In this context, assessing the consequences of variations in phenological and reproductive patterns, ecological interactions, length of annual seasons, and responses linked to adaptability, plasticity, migration or extinction in populations, for example, would be a goal of current research (Azevedo et al. 2018AZEVEDO TR, COSTA JUNIOR C, BRANDÃO JUNIOR A, CREMER MS, PIATTO M, TSAI DS & KISHINAMI R. 2018. SEEG initiative estimates of Brazilian greenhouse gas emissions from 1970 to 2015. Sci Data 5: 180045., IPCC 2018IPCC. 2018. Summary for Policymakers. In: Global warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. In: Masson-Delmotte V et al. (Eds), World Meteorological Organization, Geneva, Switzerland, 32 p. Retrieved from https://report.ipcc.ch/sr15/pdf/sr15_spm_final.pdf.
https://report.ipcc.ch/sr15/pdf/sr15_spm...
).

Finally, combined with climate change, deforestation and fires are the factors with the biggest impacts, stimulated by the growing importance of the northern savannas as a cultivation lands for South America, due to a growing competitive advantage. Agricultural expansion and urbanization, which are not limited to a single phytogeographic region, impose an environmental footprint that furthers the savanna’s vulnerability. Contrary to the current environmental policy of the Brazilian government, the identification of these environmental refuges and indication for preservation represent the minimal palliative measures to stop anthropic actions, yearning for greater future effectiveness of PAs, certainly as buffer zones for these events in ecosystem functioning and conservation.

CONCLUSIONS

The predictive power of ENMs showed high reliability and the results provided evidence that climate change will affect the distribution performance of the ten investigated oreadic woody species and alter the potential extent of their fundamental niches. The projected occurrence range coincides with the extension of the savanna biome, but interpenetrations in adjunct biomes are estimated to be greater, especially in the Amazonian border. There was no pattern of displacement of species towards higher elevations and towards climatically milder areas. With the gradual atmospheric warming, plants in the central-north savanna will be affected even in the most optimistic scenario. In both distribution status, the pattern of climatic influence of the species was not the same, which could have consequences on the ecological relationships and functionality of the floras. The main impact for the largest number of species, consistent in most scenarios, was the expansion of potential areas of occurrence, leading to suppression or cohabitation with species of other biomes. Therefore, northern savanna vegetation tends to benefit from the expansion of thermal suitability, although fragmentation and/or displacement of optimal environmental suitability is expected as the scenarios advance, especially for typically marginal plants. The confluence of the most suitable areas is considered a refuge and the largest extension is foreseen in the central-north area of the studied area, mainly involving parts of Maranhão, Tocantins and Pará. Combining data from legal reserves and vegetation suppression, the protected areas as a whole have the potential to protect less than 5% of the identified stable climatic areas. The models generated here show environmental refuges for species of the central-north savannas as the most indicated areas to be focused on conservationist measures. The findings also demonstrate the insufficiency of the PAs for protecting present and future oreadic floras, thus suggesting optimizations of maintenance strategies in the Brazilian Savanna.

ACKNOWLEDGMENTS

The conservation of the vegetable communities of the savannas North and Northeast, Brazil (MCTI/CNPq Nº 01/2016-Process 429317/2016-6). To the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for granting a Research Productivity Scholarship to the second author (Process 306672/2021-9).

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Publication Dates

  • Publication in this collection
    18 July 2022
  • Date of issue
    2022

History

  • Received
    8 Feb 2021
  • Accepted
    15 Oct 2021
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