Acessibilidade / Reportar erro

Climatic niche shift after range expansion of Eustachys (Poaceae)

Abstract

Eustachys presents lower diversity in the Old World than in the Neotropics and it occurs disjunctly between main tropical regions. This qualifies Eustachys as a good model to test whether lineages expand their niches during the process of range expansion. We performed ancestral range reconstruction, compared environmental spaces of the different geographic areas and assessed bioclimatic trait evolution. Ancestral range reconstruction indicated that most speciation in Eustachys occurred in the South America. Ancestral climatic niches of the New World are different from those of African and Australasia lineages. Our results show that Eustachys experienced niche expansion when it reached the New World. Evolutionary history of Eustachys illustrates how the range expansion promoted climatic niche shifts, which could drive unbalanced species richness of the genus among different tropical regions.

Key words
biogeography; disjunction; dispersal; ecological opportunities; grass

INTRODUCTION

Dispersal allows taxa to reach new environmental conditions that are yet occupied in the source areas, promoting niche shifts (Simpson 1953SIMPSON GG. 1953. The major features of evolution. New York: Columbia University Press, 436 p., Yoder et al. 2010YODER JB ET AL. 2010. Ecological opportunity and the origin of adaptive radiations. J Evol Biol 23: 1581-1596.). Niche-based hypotheses suggest a positive relationship between available resources and species richness or between new niche conditions and diversification (Mahler et al. 2010MAHLER DL, REVELL LJ, GLOR RE & LOSOS JB. 2010. Ecological opportunity and the rate of morphological evolution in the diversification of Greater Antillean anoles. Evol 64: 2731-2745., Wiens 2011WIENS JJ. 2011. The causes of species richness patterns across space, time, and clades and the role of “ecological limits”. Q Rev Biol 86: 75-96., Yoder et al. 2010YODER JB ET AL. 2010. Ecological opportunity and the origin of adaptive radiations. J Evol Biol 23: 1581-1596.). Indeed, niche shifts can trigger events of diversification, as observed in a classical example of adaptive radiation among islands (Yoder et al. 2010YODER JB ET AL. 2010. Ecological opportunity and the origin of adaptive radiations. J Evol Biol 23: 1581-1596.). Recent evidences reinforce the role of climate or biome shifts for diversification in plant taxa (Cabral et al. 2021CABRAL FN, TRAD RJ, AMORIM BS, MACIEL JR, AMARAL MDCE & STEVENS P. 2021. Phylogeny, divergence times, and diversification in Calophyllaceae: Linking key characters and habitat changes to the evolution of Neotropical Calophylleae. Mol Phylogenet Evol 157: 107041., Larridon et al. 2021LARRIDON I, GALÁN DÍAZ J, BAUTERS K & ESCUDERO M. 2021. What drives diversification in a pantropical plant lineage with extraordinary capacity for long-distance dispersal and colonization? J Biogeog 48: 64-77., Villaverde et al. 2017VILLAVERDE T, GONZÁLEZ-MORENO P, RODRÍGUEZ-SÁNCHEZ F & ESCUDERO M. 2017. Niche shifts after long-distance dispersal events in bipolar sedges (Carex, Cyperaceae). Am J Bot 104: 1765-1774., Wüest et al. 2015WÜEST RO, ANTONELLI A, ZIMMERMANN NE & LINDER HP. 2015. Available climate regimes drive niche diversification during range expansion. Am Nat 185: 640-652.). However, whether climatic niche shifts are associated with range expansion is still a matter of debate (Pearman et al. 2008PEARMAN PB, GUISAN A, BROENNIMANN O & RANDIN CF. 2008. Niche dynamics in space and time. Trends Ecol Evol 23: 149-158., Petitpierre et al. 2012PETITPIERRE B, KUEFFER C, BROENNIMANN O, RANDIN C, DAEHLER C & GUISAN A. 2012. Climatic niche shifts are rare among terrestrial plant invaders. Science 335: 1344-1348.).

Measuring volume of niche space is the first step to test these hypotheses because geographical areas with different ecological opportunities would exhibit greater niche space (Wiens 2011WIENS JJ. 2011. The causes of species richness patterns across space, time, and clades and the role of “ecological limits”. Q Rev Biol 86: 75-96.). Also, one might expect limited overlapping between niche volumes of geographical areas and divergent niche breadths among species from each different region, if it represents niche expansion. Due to advances in ecological niche modeling, several analytical tools can estimate niche total volumes, defined as environmental space (Qiao et al. 2016QIAO H, PETERSON AT, CAMPBELL LP, SOBERÓN J, JI L & ESCOBAR LE. 2016. NicheA: creating virtual species and ecological niches in multivariate environmental scenarios. Ecography 39: 805-813.). Environmental space is a simplified representation of ecological niche, combining information on geographical occurrence and ecological variables (Soberón & Nakamura 2009SOBERÓN J & NAKAMURA M. 2009. Niches and distributional areas: concepts, methods, and assumptions. PNAS 106: 19644-19650.).

Exploring how intercontinentally disjunct groups have dispersed and diversified allow us to understand how niche shifts are associated with movements of colonizing lineages. Intercontinental disjunctions between tropical regions have been recorded for several taxa (Thorne 1972THORNE RF. 1972. Major disjunctions in the geographic ranges of seed plants. Q Rev Biol 47: 365-411., Raven 1972RAVEN PH. 1972. Plant species disjunctions: a summary. Ann Missouri Bot Gard 59: 234-246.). Advances in techniques for dating evolutionary histories have brought to light new proofs implying that these disjunctions were more likely established by long distance dispersal than vicariance (Christenhusz & Chase 2013CHRISTENHUSZ MJ & CHASE MW. 2013. Biogeographical patterns of plants in the Neotropics–dispersal rather than plate tectonics is most explanatory. Bot J Linn 171: 277-286., McLoughlin 2001MCLOUGHLIN S. 2001. The breakup history of Gondwana and its impact on pre-Cenozoic floristic provincialism. Aust 49: 271-300.). For families such as Poaceae, Gondwanan vicariance and recent long dispersal events explain intercontinental disjunctions of ancient and young lineages, respectively (Bouchenak-Khelladi et al. 2010BOUCHENAK-KHELLADI Y, VERBOOM GA, SAVOLAINEN V & HODKINSON TR. 2010. Biogeography of the grasses (Poaceae): a phylogenetic approach to reveal evolutionary history in geographical space and geological time. Bot J Linn 162: 543-557.). For example, molecular clock analysis indicated that Poaceae originated in Gondwana 96 Mya and its subfamily Chloridoideae most likely originated in Africa and/or Asia 30 Mya ago and later dispersed to the Americas (Bouchenak-Khelladi et al. 2010BOUCHENAK-KHELLADI Y, VERBOOM GA, SAVOLAINEN V & HODKINSON TR. 2010. Biogeography of the grasses (Poaceae): a phylogenetic approach to reveal evolutionary history in geographical space and geological time. Bot J Linn 162: 543-557., Cotton et al. 2015COTTON JL, WYSOCKI WP, CLARK LG, KELCHNER SA, PIRES JC, EDGER PP, MAYFIELD-JONES D & DUVALL MR. 2015. Resolving deep relationships of PACMAD grasses: a phylogenomic approach. BMC Plant Biol 15: 1-11., Peterson et al. 2010PETERSON PM, ROMASCHENKO K & JOHNSON G. 2010. A classification of the Chloridoideae (Poaceae) based on multi-gene phylogenetic trees. Mol Phylogenet Evol 55: 580-598.).

As a member of the Chloridoideae subfamily, Eustachys Desv. is a good model to test the hypothesis that range expansion can promote climatic niche shifts, since the genus present a intercontinental disjunct pattern (Bouchenak-Khelladi et al. 2010BOUCHENAK-KHELLADI Y, VERBOOM GA, SAVOLAINEN V & HODKINSON TR. 2010. Biogeography of the grasses (Poaceae): a phylogenetic approach to reveal evolutionary history in geographical space and geological time. Bot J Linn 162: 543-557., Molina 1996MOLINA AM. 1996. Revision taxonomica del genero Eustachys Desv (Poaceae: Chloridoideae, Cynodonteae) de Sudamerica. Candollea 51: 225-272.). In addition, this monophyletic genus of the family Poaceae is represented by 15 species that have diversified in four main lineages, which are geographically structured suggesting that Eustachys expanded its range from Africa (2 spp) into Autralasia (1 spp), and into New World, where most species (13 spp) of Eustachys occur (Molina 1996MOLINA AM. 1996. Revision taxonomica del genero Eustachys Desv (Poaceae: Chloridoideae, Cynodonteae) de Sudamerica. Candollea 51: 225-272., Peterson et al. 2015PETERSON PM, ROMASCHENKO K & ARRIETA YH. 2015. A molecular phylogeny and classification of the Eleusininae with a new genus, Micrachne (Poaceae: Chloridoideae: Cynodonteae). Taxon 64: 445-467.). If Eustachys experienced a niche shift along its range expansion, the total volume of environmental space will differ between source and colonized areas. Also, lineages will show divergent scenarios of evolution in environmental space, such as significantly distinct niche breadths. Niche shift also could explain the unbalanced species richness of Eustachys between Africa, Australasia and the New World.

Here, we assess whether the range expansion of Eustachys is associated with evolution into a new realized climatic niche and into a greater environmental space. We hypothesize that range expansion of Eustachys promoted a shift in realized climatic niche in the evolutionary history of the genus and allowed it occupying climatic niches different from the source areas in Africa and Australasia. To address our main objective, we explore two questions: a) where is the most likely ancestral range of Eustachys in the New World?; and b) is range expansion of Eustachys to the New World associated with niche expansion?

MATERIALS AND METHODS

Phylogenetic analysis and divergence times

With the aim to infer the phylogenetic relationships within Eustachys, we sampled forty one species across genera of the tribe Eleusinae and used Aeluropus lagopoides (L.) Chiov. as the outgroup (Supplementary Material - Fig. S1). Sampling of Eustachys includes eleven species, which represents the entire morphological and biogeographical variation of the genus based on Peterson et al. 2015PETERSON PM, ROMASCHENKO K & ARRIETA YH. 2015. A molecular phylogeny and classification of the Eleusininae with a new genus, Micrachne (Poaceae: Chloridoideae: Cynodonteae). Taxon 64: 445-467.. We collected sequences of five DNA regions — one nuclear (ITS) and four plastid (rpl32-trnL, ndhA, rps16-trnK, rps16) — from data available in genbank (Benson et al. 2013BENSON DA, CAVANAUGH M, CLARK K, KARSCH-MIZRACHI I, LIPMAN DJ, OSTELL J & SAYERS EW. 2013. GenBank. Nucleic Acids Res 41: D36-D42.). Accessions of genbank sequences and further information about vouchers are presented in Table SI. Automatic alignment of the sequences were carried out in Geneious v.7.1.7 (Kearse et al. 2012KEARSE M ET AL. 2012. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinform 28: 1647-1649.) using the MUSCLE algorithm (Edgar 2004EDGAR RC. 2004. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinform 5: 1-19.). We performed manual adjustments when necessary, and concatenated the alignments of the five DNA regions using Geneious v.7.1.7. As a result, a database with 4,035 characters was produced.

We performed the Bayesian Inference (BI) and divergence time (DT) analysis in BEAST v.1.10.4 (Suchard et al. 2018SUCHARD MA, LEMEY P, BAELE G, AYRES DL, DRUMMOND AJ & RAMBAUT A. 2018. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol 4: vey016.). The database was partitioned to analyze each region independently. For each partition, we selected a substitution model based on the results of an Akaike’s Information Criterion analysis (Akaike 1998AKAIKE H. 1998. Information theory and an extension of the maximum likelihood principle. In: PARZEN E & TANABE K (Eds), Selected papers of Hirotugu Akaike, Springer Science + Business Media: Berlim, p. 199-213.), executed in JModelstest v.2.1.6 (Darriba et al. 2012DARRIBA D, TABOADA GL, DOALLO R & POSADA D. 2012. jModelTest 2: more models, new heuristics and parallel computing. Nat Methods 9: 772-772.). The BI, DT and JModelTest were run through CIPRES Science Gateway (Miller et al. 2011MILLER MA, PFEIFFER W & SCHWARTZ T. 2011. The CIPRES science gateway: a community resource for phylogenetic analyses. In Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery. https://doi.org/10.1145/2016741.2016785.
https://doi.org/10.1145/2016741.2016785...
). We applied the HKY-Gamma model for partitions represented by ITS and rps16-trnL, HKY-Inv for rps16, and JC-Gamma for rpl32-trnL and ndhA. Two independent Markov chains of 50,000,000 generations with trees being sampled every 1,000 generations were run. After the analyses, we discarded the first 10% of the generations in each Markov chain and used the remaining trees to access the maximum credibility tree and to calculate the values of posterior probability (PP) of each node.

The divergence time estimates were conducted with an uncorrelated relaxed clock model (Drummond et al. 2006DRUMMOND AJ, HO SYW, PHILLIPS MJ & RAMBAUT A. 2006. Relaxed phylogenetics and dating with confidence. PLoS Biol 4: e88.), with a lognormal relaxed distribution rates, and a birth–death speciation model (Gernhard 2008GERNHARD T. 2008. The conditioned reconstructed process. J Theor Biol 253: 769-778.) as a tree prior. The node age of tribe Eleusinae was secondary calibrated following Liu et al. (2011)LIU Q, TRIPLETT JK, WEN J & PETERSON PM. 2011. Allotetraploid origin and divergence in Eleusine (Chloridoideae, Poaceae): evidence from low-copy nuclear gene phylogenies and a plastid gene chronogram. Ann Bot 108: 1287-1298. in which a mean of 17.5 Mya. We applied a standard variation of 1.5, which corresponds to a variation of 15 to 20 Mya. Mean age for each clade of Eleusinae are presented in Table SII.

Ancestral range reconstruction

Information about geographical distribution of the species was collected from the Global Biodiversity Information System (GBIF). Only data that were georeferenced and identified by specialists were kept. Literature searches were carried out to remove areas in which species had been introduced or naturalized. Based on geographical range patterns identified for each species after the cleaning procedures in the dataset, we classified five areas of distribution: A) Africa; B) Australasia; C) North America; D) Central America; and E) South America (Table SI). Species occurring in the Caribbean were included in the Central America classification.

We reconstructed the ancestral range of the main nodes in the Eustachys phylogeny, applying a bayesian analysis implemented in RASP v.4 (available at http://mnh.scu.edu.cn/soft/blog/RASP/). RASP tests which biogeographical model best fits the evolutionary history and geographical distributions of the studied group (Yu et al. 2015YU Y, HARRIS AJ, BLAIR C & HE X. 2015. RASP (Reconstruct Ancestral State in Phylogenies): a tool for historical biogeography. Mol Phylogenet Evol 87: 46-49., 2020). We tested three biogeographic models: 1) S-DIVA (Statistical Dispersal-Vicariance Analysis) which optimizes an extinction, dispersal and vicariance matrix applying less “costs” to vicariance and calculates statistical support for each ancestral range in each node against several alternative scenarios (Yu et al. 2010YU Y, HARRIS AJ & HE XJ. 2010. S-DIVA (statistical dispersal-vicariance analysis): a tool for inferring biogeographic histories. Mol Phylogenet Evol 56: 848-850.); 2) S-DEC (Statistical Dispersal-Extinction-Cladogenesis) assumes that dispersal mediates range expansion and extinction mediates range contraction and calculates the probability of a event along a phylogeny branch according to the proportion of the same branch and the instantaneous transitions rates between geographic areas (Beaulieu et al. 2013BEAULIEU JM, TANK DC & DONOGHUE MJ. 2013. A Southern Hemisphere origin for campanulid angiosperms, with traces of the break-up of Gondwana. BMC Evol Biol 13: 80.); and 3) BAYAREA (Bayesian inference for discrete Areas) that calculates the probability of a biogeographic history using an “data-augmentation” approach in which a continuous-time Markov chain is used to simulate events of colonization and local extinction (Landis et al. 2013LANDIS MJ, MATZKE NJ, MOORE BR & HUELSENBECK JP. 2013. Bayesian analysis of biogeography when the number of areas is large. Syst Biol 62: 789-804.).

Because all the three biogeographical models include estimations of uncertainty, we used 1,000 trees randomly selected from a dataset of combined Markov Chains of dating analysis with 10,000 phylogenetic trees to explore which biogeographical model best explained the evolutionary history of Eustachys. We tested the three models implemented in RASP in two independent scenarios. First, we reconstructed the ancestral range without any restriction of connections among the geographical areas. Second, we applied restrictions to connections among Australasia, North America and Central America, and between North America and South America. In both scenarios, we ran one analysis setting the minimum number of areas allowed by nodes, and another analysis setting the maximum number of areas. Since the focus of our study is the genus Eustachys, to reconstruct the ancestral range and niche evolution (see Niche evolution and ecological divergence below), we pruned the consensus tree excluding the outgroup and the other genera of tribe Eleusinae using the ape package (Paradis et al. 2004PARADIS E, CLAUDE J & STRIMMER K. 2004. APE: analyses of phylogenetics and evolution in R language. Bioinform 20: 289-290.) in R environment (R Core Team 2020).

Niche evolution and ecological divergence

To test evolution of realized climatic niches in Eustachys and environmental space divergence among the geographical areas, we used 19 bioclimatic variables available in WorldClim 2.1 (Fick & Hijmans 2017FICK SE & HIJMANS RJ. 2017. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol 37: 4302-4315.) after clipping the variables to the extent of Eustachys occurrence (-176.6W, 175.1E, -40.8S, 36.8N), and applying a Spearman correlation analysis (threshold 0.85) to select the most independent bioclimatic variables. The selected variables were: BIO1 (annual mean temperature), BIO2 (mean diurnal range temperature), BIO4 (temperature seasonality), BIO5 (max temperature of warmest month), BIO8 (mean temperature of wettest quarter), BIO12 (annual precipitation), BIO13 (precipitation of wettest month), and BIO15 (Precipitation Seasonality). We performed these analyses in the packages “ntbox” (Osorio-Olvera et al. 2020OSORIO-OLVERA L, LIRA-NORIEGA A, SOBERÓN J, TOWNSEND PA, FALCONI M, CONTRERAS-DÍAZ RG, MARTÍNEZ-MEYER E, BARVE V & BARVE N. 2020. ntbox: an R package with graphical user interface for modelling and evaluating multidimensional ecological niches. Methods Ecol Evol 11: 1199-1206.) and “raster” v3.3 implemented in R.

We used the occurrence data to extract climatic data of the eight bioclimatic variables and then run a principal component analysis to represent the environmental space occupied by species of Eustachys of each geographical area in 3D using the software NicheA 3.0 (Qiao et al. 2016QIAO H, PETERSON AT, CAMPBELL LP, SOBERÓN J, JI L & ESCOBAR LE. 2016. NicheA: creating virtual species and ecological niches in multivariate environmental scenarios. Ecography 39: 805-813.). We estimated the volume of environmental space of each geographical area as a minimum convex polyhedron (MCP). Then, we calculated the pairwise overlap between each area as a ratio of x/y, where x is the intersection of two environmental spaces and y is the volume of the smaller polyhedron in the compared pairwise.

For measuring phylogenetic signals of realized climatic niche in Eustachys, we performed a phylogenetic reconstruction of ancestral climatic traits. Firstly, using the occurrence data, we extracted climatic data and calculated the mean values of each bioclimatic for each species. Then, we estimated the evolution of each bioclimatic variable assuming a Brownian evolutionary model (sensu Revell 2013REVELL LJ. 2013. Two new graphical methods for mapping trait evolution on phylogenies. Methods Ecol Evol 4: 754-759.). Blomberg’s K and Pagel’s λ values of phylogenetic signal were calculated for each bioclimatic variable using the “Phytools” package (Revell 2012REVELL LJ. 2012. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol Evol 3: 217-223.) for R. We also calculated the niche breadth of bioclimatic variables that presented phylogenetic signals for each species of Eustachys. To identify statistical significant differences among niche breadth of each species, Kruskal-Wallis and post hoc Wilcoxon tests were performed. In the Wilcoxon test, the p-value was corrected by the Holm method.

Additionally, we performed an Age Overlap Correlation Analysis (AOC) (Fitzpatrick & Turelli 2006FITZPATRICK BM & TURELLI M. 2006. The geography of mammalian speciation: mixed signals from phylogenies and range maps. Evol 60: 601-615.) implemented in the package phyloclim 1.5-1 (Heibl & Calenge 2013HEIBL C & CALENGE C. 2013. Phyloclim: integrating phylogenetics and climatic niche modeling. R package version 0.9-4.). In this analysis, we explored the null hypothesis of absence of niche overlap along the evolutionary history of Eustachys. AOC also describes changes in niche overlap along the time. We used both D and I statistics of niche overlap and performed a Monte Carlo resampling of 10.000 replicates (Fitzpatrick & Turelli 2006FITZPATRICK BM & TURELLI M. 2006. The geography of mammalian speciation: mixed signals from phylogenies and range maps. Evol 60: 601-615.).

RESULTS

Ancestral range reconstruction indicated the S-DEC with restriction and three areas by node as the best model to explain the evolutionary history and patterns of geographical distribution in Eustachys (LnL = -21.37, AICw = 0.75, Table SIII). In this model, intercontinental dispersions are assumed to have greater “costs” than vicariance. Also, in this model the probable ancestral range in each node is assumed as only a combination of three areas. However, this model presented some inconsistencies with the age of 4.8 Mya of Eustachys (HPD95% = 6.6–3.4 Mya) recovered by molecular dating analysis.

The selected model showed that the ancestral ranges of all Eustachys probably covered Africa, Australasia and South America (Fig. 1; ABE = 81%). For the common ancestor of Eustachys tenera plus American lineages, the model indicated Australasia plus South America as the ancestral range (Fig. 1; BE = 100%). According to the model, two vicariance events established the main patterns of continental disjunctions in Eustachys: the first segregated the African lineages from the other lineages (ABE->A|BE, PP = 0.81); and the second led to the lineages from Australasia plus the Americas (BE->B|E, PP = 0.61).

Figure 1
BEAST chronogram of Bayesian analysis of time divergence, geographical areas, ancestral range reconstruction, and volumes of the minimum convex polyhedron of the environmental space of each geographical area for Eustachys. Blue bars in phylogeny represent 95% confidence intervals. Posterior probability (PP) values are shown above branches only for the main clades with high support. The map shows the coded geographical areas used in the analysis. Pier chart shows the posterior probabilities of the ancestral ranges. The bar chart represents the minimum convex polyhedron (MCP) values of each geographical area. The colors used in the map, in the phylogeny and in the bar chart represent the geographical areas. Combinations of ancestral ranges found are presented in the above map. Area codes: A = Africa, B = Australasia, C = North America, D = Central America, and E = South America.

For the American lineages, the model identified South America as the most likely ancestral range (Fig. 1; E = 61%). Four dispersion events occurred from South to North America and three into South America. Five speciation events were identified in South America, and three in North America. These results point to intense evolutionary dynamics of Eustachys during the last 2.1 Mya (HPD95% = 1.2–2.9 Mya) in South America. See supplementary material for the complete age estimates for the genera of tribe Eleusinae (Fig. S1).

Ecological divergence analysis showed that South America presented the largest environmental space compared to other regions (MCP = 25.74). This indicates a higher volume of realized niche in South America when compared to other areas (Fig. 1). Overlaps between areas were often small (Table I). Pairwise comparisons of environmental spaces showed low values of overlap between South America and Australasia (Overlapping = 12.83), and South America and Africa (Overlapping = 11.66). However, the lowest values were found between North America and Australasia (Overlapping = 2.08), and North America and Africa (Overlapping = 0.57).

Table I
Pairwise overlapping values of environmental spaces between geographical areas of the distribution of Eustachys.

Four bioclimatic variables presented phylogenetic signals: BIO5 (max temperature of warmest month, K=0.69, logL=-17.94, λ=0.83), BIO8 (mean temperature of wettest quarter, K=0.56, logL=-22.31, λ=0.99), BIO12 (annual precipitation, K=1.00, logL=-76.11, λ=0.96), and BIO13 (precipitation of wettest month, K=0.88, logL=-53.08, λ=0.980). Reconstruction of the environmental variables showed a divergent pattern between the lineages, especially between the New World lineages and Paleotropical lineages (Fig. 2). For these variables, we found a negative slope higher than 0.5 in the AOC results (Fig. 3), indicating that recently diverged nodes are more similar than the early diverged nodes. However, all AOC results were inconclusive (P > 0.05), probably as an effect of the low number of internal nodes evaluated.

Figure 2
Representation of the evolution of Eustachys in each environmental space of the bioclimatic variables that presented a phylogenetic signal. Bars represent the variation of each environmental variable. Bio5 = max temperature of warmest month, Bio8 = mean temperature of wettest quarter, Bio12 = annual precipitation, and Bio13 precipitation of wettest month.
Figure 3
Results of Age Overlap Correlation analysis (AOC) of the bioclimatic variables that presented phylogenetic signals. Values represent both D and I metric of niche overlap in function of time of divergence of clades. Dots represent nodes in the phylogenetic tree. Line is the fitted regression. All AOC results were inconclusive (P > 0.05). Bio5 = max temperature of warmest month, Bio8 = mean temperature of wettest quarter, Bio12 = annual precipitation, and Bio13 precipitation of wettest month.

Niche breadth comparison among species confirmed the divergent patterns found in previous analysis (Fig. 4). Our results revealed significant differences for all bioclimatic variables that presented phylogenetic signals (BIO 5: Χ² = 1347.1, df = 963, P < 0.001; BIO8: Χ² = 1394, df = 996, P < 0.001; BIO12: Χ² = 1143.1, df = 744, P < 0.001; BIO 13: Χ² = 504.62, df = 261, P < 0.001). Eustachys paspaloides has the most divergent niche breadths for all bioclimatic variables when compared with other lineages (Tables II and III), as the E. tenera diverges more from american lineages in the niche breadths of BIO5 and BIO 8 (Table III). In the temperature environmental spaces, North American lineages occupy smaller niche breadths while South American lineages present larger niche breadths (Fig. 4). In the precipitation environmental spaces, E. tenera presents the largest niche breadth and all American lineages occupy small niche breadths.

Figure 4
Representation of niche breadth of each species in the environmental spaces of the bioclimatic variables with phylogenetic signals. Outliers were omitted in the graph. Bio5 = max temperature of warmest month, Bio8 = mean temperature of wettest quarter, Bio12 = annual precipitation, and Bio13 precipitation of wettest month. Abbreviated names of species of Eustachys. pasp: E. paspaloides; tene: E. tenera; glau: E. glauca; petr: E. petraea; negl: E. neglecta; flor: E. floridana; retu: E. retusa; dist: E. distichophylla; glab: E. glabrescens; cari: E. caribea; calv: E. calvescens.
Table II
Wilcoxon pairwise comparison of niche breadth of Bio5 (max temperature of warmest month, lower table) and Bio8 (mean temperature of wettest quarter, upper table) of each species of Eustachys. In the columns, names of species were abbreviated. Significance levels after applying a Holm correction: * P < 0.05; ** P < 0.01; *** P < 0.001; ns, non significant. Abbreviated names of species of Eustachys. pasp: E. paspaloides; tene: E. tenera; glau: E. glauca; petr: E. petraea; negl: E. neglecta; flor: E. floridana; retu: E. retusa; dist: E. distichophylla; glab: E. glabrescens; cari: E. caribea; calv: E. calvescens.
Table III
Wilcoxon pairwise comparison of niche breadth of Bio12 (annual precipitation, lower table) and Bio13 (precipitation of wettest month, upper table) of each species of Eustachys. In the columns, names of species were abbreviated. Significance levels after applying a Holm correction: * P < 0.05; ** P < 0.01; *** P < 0.001; ns, non significant. Abbreviated names of species of Eustachys. pasp: E. paspaloides; tene: E. tenera; glau: E. glauca; petr: E. petraea; negl: E. neglecta; flor: E. floridana; retu: E. retusa; dist: E. distichophylla; glab: E. glabrescens; cari: E. caribea; calv: E. calvescens.

DISCUSSION

According to our results, Eustachys occupied a greater volume in the environmental space when it reached the New World, suggesting an expansion of its realized climatic niche. The realized climatic niches of Eustachys in the North, Central and South America are different from those of the African and Australasia lineages. In addition, South and North American lineages evolved in different environmental spaces in terms of each climatic variable. Evolutionary history of Eustachys illustrates how the range expansion promoted shifts in the realized climatic niche, which could drive unbalanced species richness among different tropical regions.

Ancestral range reconstruction points out that the vicariance process established the realized geographic pattern of distribution of species of Eustachys. However, there is an incongruence between the best model of geographic distribution recovered in ancestral range reconstruction and the evidence from dated phylogenies of Chloridoideae. According to Bouchenak-Khelladi et al. (2010)BOUCHENAK-KHELLADI Y, VERBOOM GA, SAVOLAINEN V & HODKINSON TR. 2010. Biogeography of the grasses (Poaceae): a phylogenetic approach to reveal evolutionary history in geographical space and geological time. Bot J Linn 162: 543-557., Cotton et al. (2015)COTTON JL, WYSOCKI WP, CLARK LG, KELCHNER SA, PIRES JC, EDGER PP, MAYFIELD-JONES D & DUVALL MR. 2015. Resolving deep relationships of PACMAD grasses: a phylogenomic approach. BMC Plant Biol 15: 1-11., and to our own results, Chloridoideae diverged from its early ancestor 30 Mya and Eustachys ~4.8 Mya. This timeframe is incoherent with the vicariance by tectonic plate movements (Christenhusz & Chase 2013CHRISTENHUSZ MJ & CHASE MW. 2013. Biogeographical patterns of plants in the Neotropics–dispersal rather than plate tectonics is most explanatory. Bot J Linn 171: 277-286., Jokat et al. 2003JOKAT W, BOEBEL T, KÖNIG M & MEYER U. 2003. Timing and geometry of early Gondwana breakup. J Geophys Res Solid Earth 108: 2428., Raven 1972RAVEN PH. 1972. Plant species disjunctions: a summary. Ann Missouri Bot Gard 59: 234-246.). At ~4.8 Mya, tectonic plate drift had positioned continents in their contemporary configuration (Jokat et al. 2003JOKAT W, BOEBEL T, KÖNIG M & MEYER U. 2003. Timing and geometry of early Gondwana breakup. J Geophys Res Solid Earth 108: 2428.). Thus, we assume that long distance dispersal explains the geographical expansion of Eustachys from the Old World to the New World

Geographical and evolutionary patterns found in Eustachys is one more example of the theory of intercontinental disjunctions (Thorne 1972THORNE RF. 1972. Major disjunctions in the geographic ranges of seed plants. Q Rev Biol 47: 365-411.). Such disjunctions have been explained mainly by vicariance events, but new evidence supports intercontinental disjunctions as a result of long distance dispersal more than vicariance (Christenhusz & Chase 2013CHRISTENHUSZ MJ & CHASE MW. 2013. Biogeographical patterns of plants in the Neotropics–dispersal rather than plate tectonics is most explanatory. Bot J Linn 171: 277-286., Raven 1972RAVEN PH. 1972. Plant species disjunctions: a summary. Ann Missouri Bot Gard 59: 234-246.). In addition, long distance dispersal events from Africa to Australasia and from Australasia to South America have been recorded in several angiosperms species (Cuenca et al. 2008CUENCA A, ASMUSSEN-LANGE CB & BORCHSENIUS F. 2008. A dated phylogeny of the palm tribe Chamaedoreeae supports Eocene dispersal between Africa, North and South America. Mol Phylogenet Evol 46: 760-775.).

Evolutionary dynamics of Eustachys substantiates a niche expansion during the colonization of the New World, which could explain the high diversity of the genus in South and North America (Molina 1996MOLINA AM. 1996. Revision taxonomica del genero Eustachys Desv (Poaceae: Chloridoideae, Cynodonteae) de Sudamerica. Candollea 51: 225-272.). Indeed, we found that Eustachys experienced most of its diversification events in the New World and the speciation in South America was accompanied by the expansion into a greater environmental space and by differentiation of realized niche. The volume of environmental space was relatively higher in South America compared to all other regions and the environmental spaces of Central and North America diverged from those of Australasia and Africa. We also found a general trend of older lineages present less overlap than younger lineages in AOC analysis. Expanding and differentiating environmental spaces of Eustachys agree with the expected effects of increasing ecological opportunities and niche shifts (Wiens 2011WIENS JJ. 2011. The causes of species richness patterns across space, time, and clades and the role of “ecological limits”. Q Rev Biol 86: 75-96.).

Evidences support that regions climatically stable and limited in niche breadth can trigger higher diversification (MacArthur 1972MACARTHUR RH. 1972. Geographical Ecology: Patterns in the Distribution of Species. Princeton: Princeton University Press, 288 p.). In our study, we detected an opposite pattern. The region where Eustachys presentes greater rates of speciation also possesses greater niche volume and hosts species with larger niche breadths in the temperature environmental spaces. However, our AOC results indicate that niche is not the only force acting in diversification of Eustachys. In grass genera, diversification can have several drivers, such as polyploidy and hybridization (Liu et al. 2011LIU Q, TRIPLETT JK, WEN J & PETERSON PM. 2011. Allotetraploid origin and divergence in Eleusine (Chloridoideae, Poaceae): evidence from low-copy nuclear gene phylogenies and a plastid gene chronogram. Ann Bot 108: 1287-1298.). Thus, one would expect that other forces previously documented for Poaceae could act conjointly with niche expansion in the diversification of Eustachys. Nevertheless, differences in niche volume among areas, differences of extension of niche breadth among species and niche expansion potentially explain the imbalance in the number of species of Eustachys among regions.

Several tropical groups have higher numbers of species in the Neotropics than in any other tropical region. For example, the main lineages of Protiae diversified more in the Neotropics than in the Old World (Fine et al. 2014FINE PV, ZAPATA F & DALY DC. 2014. Investigating processes of neotropical rain forest tree diversification by examining the evolution and historical biogeography of the Protieae (Burseraceae). Evol 68: 1988-2004.); the Ocotea Aubl. complex increased its rate of speciation after being dispersed from the Old World to New World (Chanderbali et al. 2001CHANDERBALI AS, VAN DER WERFF H & RENNER SS. 2001. Phylogeny and historical biogeography of Lauraceae: evidence from the chloroplast and nuclear genomes. Ann Missouri Bot Gard 88: 104-134.); and several lineages of Euphorbia L. reached higher diversification after colonizing the Neotropics (Riina et al. 2013RIINA R ET AL. 2013. A worldwide molecular phylogeny and classification of the leafy spurges, Euphorbia subgenus Esula (Euphorbiaceae). Taxon 62: 316-342.). Other ecologically dominant groups in Neotropical ecosystems present the same pattern of higher diversification in the Neotropics (Pennington & Dick 2004PENNINGTON RT & DICK CW. 2004. The role of immigrants in the assembly of the South American rainforest tree flora. Philos Trans R Soc Lond B Biol Sci 359: 1611-1622.). Moreover, some lineages remain less diversified after colonizing the Old World, such as Dalechampia Plum. ex L. (Armbruster 1994ARMBRUSTER WS. 1994. Early evolution of Dalechampia (Euphorbiaceae): insights from phylogeny, biogeography, and comparative ecology. Ann Missouri Bot Gard 81: 303-317.) and Rhipsalis Gaertn. (Calvente et al. 2011CALVENTE A, ZAPPI DC, FOREST F & LOHMANN LG. 2011. Molecular phylogeny, evolution, and biogeography of South American epiphytic cacti. Int J Plant Sci 172: 902914.).

Eustachys also expanded its range to new latitudinal limits along its evolutionary history. This expansion is associated with events of speciation in North America, where the smallest and most differentiated environmental space is found. Jansson et al. (2013)JANSSON R, RODRÍGUEZ-CASTAÑEDA G & HARDING LE. 2013. What can multiple phylogenies say about the latitudinal diversity gradient? A new look at the tropical conservatism, out of the tropics, and diversification rate hypotheses. Evol 67: 1741-1755. found that latitudinal transitions are frequent in tropical lineages and predominates over the presumed tropical conservatism, indicating that tropical lineages have few difficulties in colonizing new habitats. Eustachys adds one more example to the body of this hypothesis because its evolutionary history illustrates transitions to new environmental conditions.

We are aware that limitations in the dataset of climatic niches impose cautions for interpreting our results on niche reconstruction. Unfortunately, no dataset with climatic information of the last 5 or 10 Mya is available. Despite that, our dated phylogeny allows us to infer that the diversification of Eustachys happened during a period of intense environmental change in South America (Ehlers & Poulsen 2009EHLERS TA & POULSEN CJ. 2009. Influence of Andean uplift on climate and paleoaltimetry estimates. Earth Planet Sci Lett 281: 238-248.). Driven mainly by Andean orogeny and climate changes, the last 5 Mya in South America recorded an intensification in climate changes, local tectonic pulses along the eastern coast, changes in watercourses, redirection of drainage systems, intense biotic interchange and marine transgressions (Antonelli & Sanmartín 2011ANTONELLI A & SANMARTÍN I. 2011. Why are there so many plant species in the Neotropics? Taxon 60: 403-414., Antonelli et al. 2018ANTONELLI A ET AL. 2018. Conceptual and empirical advances in Neotropical biodiversity research. PeerJ 6: e5644., Cody et al. 2010CODY S, RICHARDSON JE, RULL V, ELLIS C & PENNINGTON RT. 2010. The great American biotic interchange revisited. Ecography 33: 326-332.). These events acting synergistically made the Neotropical region a land of evolutionary opportunities for Eustachys.

ACKNOWLEDGMENTS

The MIP and JRM are grateful to the Prefeitura do Recife for its support of this work. BSA thanks Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for a postdoctoral scholarship. We thank the reviewers and editors for their valuable suggestions that increased the quality of this paper.

SUPPLEMENTARY MATERIAL

Figure S1.

Tables SI, SII, SIII.

REFERENCES

  • AKAIKE H. 1998. Information theory and an extension of the maximum likelihood principle. In: PARZEN E & TANABE K (Eds), Selected papers of Hirotugu Akaike, Springer Science + Business Media: Berlim, p. 199-213.
  • ANTONELLI A & SANMARTÍN I. 2011. Why are there so many plant species in the Neotropics? Taxon 60: 403-414.
  • ANTONELLI A ET AL. 2018. Conceptual and empirical advances in Neotropical biodiversity research. PeerJ 6: e5644.
  • ARMBRUSTER WS. 1994. Early evolution of Dalechampia (Euphorbiaceae): insights from phylogeny, biogeography, and comparative ecology. Ann Missouri Bot Gard 81: 303-317.
  • BEAULIEU JM, TANK DC & DONOGHUE MJ. 2013. A Southern Hemisphere origin for campanulid angiosperms, with traces of the break-up of Gondwana. BMC Evol Biol 13: 80.
  • BENSON DA, CAVANAUGH M, CLARK K, KARSCH-MIZRACHI I, LIPMAN DJ, OSTELL J & SAYERS EW. 2013. GenBank. Nucleic Acids Res 41: D36-D42.
  • BOUCHENAK-KHELLADI Y, VERBOOM GA, SAVOLAINEN V & HODKINSON TR. 2010. Biogeography of the grasses (Poaceae): a phylogenetic approach to reveal evolutionary history in geographical space and geological time. Bot J Linn 162: 543-557.
  • CABRAL FN, TRAD RJ, AMORIM BS, MACIEL JR, AMARAL MDCE & STEVENS P. 2021. Phylogeny, divergence times, and diversification in Calophyllaceae: Linking key characters and habitat changes to the evolution of Neotropical Calophylleae. Mol Phylogenet Evol 157: 107041.
  • CALVENTE A, ZAPPI DC, FOREST F & LOHMANN LG. 2011. Molecular phylogeny, evolution, and biogeography of South American epiphytic cacti. Int J Plant Sci 172: 902914.
  • CHANDERBALI AS, VAN DER WERFF H & RENNER SS. 2001. Phylogeny and historical biogeography of Lauraceae: evidence from the chloroplast and nuclear genomes. Ann Missouri Bot Gard 88: 104-134.
  • CHRISTENHUSZ MJ & CHASE MW. 2013. Biogeographical patterns of plants in the Neotropics–dispersal rather than plate tectonics is most explanatory. Bot J Linn 171: 277-286.
  • CODY S, RICHARDSON JE, RULL V, ELLIS C & PENNINGTON RT. 2010. The great American biotic interchange revisited. Ecography 33: 326-332.
  • COTTON JL, WYSOCKI WP, CLARK LG, KELCHNER SA, PIRES JC, EDGER PP, MAYFIELD-JONES D & DUVALL MR. 2015. Resolving deep relationships of PACMAD grasses: a phylogenomic approach. BMC Plant Biol 15: 1-11.
  • CUENCA A, ASMUSSEN-LANGE CB & BORCHSENIUS F. 2008. A dated phylogeny of the palm tribe Chamaedoreeae supports Eocene dispersal between Africa, North and South America. Mol Phylogenet Evol 46: 760-775.
  • DARRIBA D, TABOADA GL, DOALLO R & POSADA D. 2012. jModelTest 2: more models, new heuristics and parallel computing. Nat Methods 9: 772-772.
  • DRUMMOND AJ, HO SYW, PHILLIPS MJ & RAMBAUT A. 2006. Relaxed phylogenetics and dating with confidence. PLoS Biol 4: e88.
  • EDGAR RC. 2004. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinform 5: 1-19.
  • EHLERS TA & POULSEN CJ. 2009. Influence of Andean uplift on climate and paleoaltimetry estimates. Earth Planet Sci Lett 281: 238-248.
  • FICK SE & HIJMANS RJ. 2017. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol 37: 4302-4315.
  • FINE PV, ZAPATA F & DALY DC. 2014. Investigating processes of neotropical rain forest tree diversification by examining the evolution and historical biogeography of the Protieae (Burseraceae). Evol 68: 1988-2004.
  • FITZPATRICK BM & TURELLI M. 2006. The geography of mammalian speciation: mixed signals from phylogenies and range maps. Evol 60: 601-615.
  • GERNHARD T. 2008. The conditioned reconstructed process. J Theor Biol 253: 769-778.
  • HEIBL C & CALENGE C. 2013. Phyloclim: integrating phylogenetics and climatic niche modeling. R package version 0.9-4.
  • JANSSON R, RODRÍGUEZ-CASTAÑEDA G & HARDING LE. 2013. What can multiple phylogenies say about the latitudinal diversity gradient? A new look at the tropical conservatism, out of the tropics, and diversification rate hypotheses. Evol 67: 1741-1755.
  • JOKAT W, BOEBEL T, KÖNIG M & MEYER U. 2003. Timing and geometry of early Gondwana breakup. J Geophys Res Solid Earth 108: 2428.
  • KEARSE M ET AL. 2012. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinform 28: 1647-1649.
  • LANDIS MJ, MATZKE NJ, MOORE BR & HUELSENBECK JP. 2013. Bayesian analysis of biogeography when the number of areas is large. Syst Biol 62: 789-804.
  • LARRIDON I, GALÁN DÍAZ J, BAUTERS K & ESCUDERO M. 2021. What drives diversification in a pantropical plant lineage with extraordinary capacity for long-distance dispersal and colonization? J Biogeog 48: 64-77.
  • LIU Q, TRIPLETT JK, WEN J & PETERSON PM. 2011. Allotetraploid origin and divergence in Eleusine (Chloridoideae, Poaceae): evidence from low-copy nuclear gene phylogenies and a plastid gene chronogram. Ann Bot 108: 1287-1298.
  • MACARTHUR RH. 1972. Geographical Ecology: Patterns in the Distribution of Species. Princeton: Princeton University Press, 288 p.
  • MAHLER DL, REVELL LJ, GLOR RE & LOSOS JB. 2010. Ecological opportunity and the rate of morphological evolution in the diversification of Greater Antillean anoles. Evol 64: 2731-2745.
  • MCLOUGHLIN S. 2001. The breakup history of Gondwana and its impact on pre-Cenozoic floristic provincialism. Aust 49: 271-300.
  • MILLER MA, PFEIFFER W & SCHWARTZ T. 2011. The CIPRES science gateway: a community resource for phylogenetic analyses. In Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery. https://doi.org/10.1145/2016741.2016785
    » https://doi.org/10.1145/2016741.2016785
  • MOLINA AM. 1996. Revision taxonomica del genero Eustachys Desv (Poaceae: Chloridoideae, Cynodonteae) de Sudamerica. Candollea 51: 225-272.
  • OSORIO-OLVERA L, LIRA-NORIEGA A, SOBERÓN J, TOWNSEND PA, FALCONI M, CONTRERAS-DÍAZ RG, MARTÍNEZ-MEYER E, BARVE V & BARVE N. 2020. ntbox: an R package with graphical user interface for modelling and evaluating multidimensional ecological niches. Methods Ecol Evol 11: 1199-1206.
  • PARADIS E, CLAUDE J & STRIMMER K. 2004. APE: analyses of phylogenetics and evolution in R language. Bioinform 20: 289-290.
  • PEARMAN PB, GUISAN A, BROENNIMANN O & RANDIN CF. 2008. Niche dynamics in space and time. Trends Ecol Evol 23: 149-158.
  • PENNINGTON RT & DICK CW. 2004. The role of immigrants in the assembly of the South American rainforest tree flora. Philos Trans R Soc Lond B Biol Sci 359: 1611-1622.
  • PETERSON PM, ROMASCHENKO K & ARRIETA YH. 2015. A molecular phylogeny and classification of the Eleusininae with a new genus, Micrachne (Poaceae: Chloridoideae: Cynodonteae). Taxon 64: 445-467.
  • PETERSON PM, ROMASCHENKO K & JOHNSON G. 2010. A classification of the Chloridoideae (Poaceae) based on multi-gene phylogenetic trees. Mol Phylogenet Evol 55: 580-598.
  • PETITPIERRE B, KUEFFER C, BROENNIMANN O, RANDIN C, DAEHLER C & GUISAN A. 2012. Climatic niche shifts are rare among terrestrial plant invaders. Science 335: 1344-1348.
  • QIAO H, PETERSON AT, CAMPBELL LP, SOBERÓN J, JI L & ESCOBAR LE. 2016. NicheA: creating virtual species and ecological niches in multivariate environmental scenarios. Ecography 39: 805-813.
  • R CORE TEAM. 2020. R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
    » https://www.R-project.org/
  • RAVEN PH. 1972. Plant species disjunctions: a summary. Ann Missouri Bot Gard 59: 234-246.
  • REVELL LJ. 2012. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol Evol 3: 217-223.
  • REVELL LJ. 2013. Two new graphical methods for mapping trait evolution on phylogenies. Methods Ecol Evol 4: 754-759.
  • RIINA R ET AL. 2013. A worldwide molecular phylogeny and classification of the leafy spurges, Euphorbia subgenus Esula (Euphorbiaceae). Taxon 62: 316-342.
  • SIMPSON GG. 1953. The major features of evolution. New York: Columbia University Press, 436 p.
  • SOBERÓN J & NAKAMURA M. 2009. Niches and distributional areas: concepts, methods, and assumptions. PNAS 106: 19644-19650.
  • SUCHARD MA, LEMEY P, BAELE G, AYRES DL, DRUMMOND AJ & RAMBAUT A. 2018. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol 4: vey016.
  • THORNE RF. 1972. Major disjunctions in the geographic ranges of seed plants. Q Rev Biol 47: 365-411.
  • VILLAVERDE T, GONZÁLEZ-MORENO P, RODRÍGUEZ-SÁNCHEZ F & ESCUDERO M. 2017. Niche shifts after long-distance dispersal events in bipolar sedges (Carex, Cyperaceae). Am J Bot 104: 1765-1774.
  • WIENS JJ. 2011. The causes of species richness patterns across space, time, and clades and the role of “ecological limits”. Q Rev Biol 86: 75-96.
  • WÜEST RO, ANTONELLI A, ZIMMERMANN NE & LINDER HP. 2015. Available climate regimes drive niche diversification during range expansion. Am Nat 185: 640-652.
  • YODER JB ET AL. 2010. Ecological opportunity and the origin of adaptive radiations. J Evol Biol 23: 1581-1596.
  • YU Y, BLAIR C & HE X. 2020. RASP 4: ancestral state reconstruction tool for multiple genes and characters. Mol Biol Evol 37: 604-606.
  • YU Y, HARRIS AJ, BLAIR C & HE X. 2015. RASP (Reconstruct Ancestral State in Phylogenies): a tool for historical biogeography. Mol Phylogenet Evol 87: 46-49.
  • YU Y, HARRIS AJ & HE XJ. 2010. S-DIVA (statistical dispersal-vicariance analysis): a tool for inferring biogeographic histories. Mol Phylogenet Evol 56: 848-850.

Publication Dates

  • Publication in this collection
    10 June 2024
  • Date of issue
    2024

History

  • Received
    9 May 2022
  • Accepted
    17 Aug 2023
Academia Brasileira de Ciências Rua Anfilófio de Carvalho, 29, 3º andar, 20030-060 Rio de Janeiro RJ Brasil, Tel: +55 21 3907-8100 - Rio de Janeiro - RJ - Brazil
E-mail: aabc@abc.org.br