# Biogeographic history of a large clade of ectomycorrhizal fungi, the Russulaceae, in the Neotropics and adjacent regions

Jan Hackel, Terry W Henkel, Pierre-arthur Moreau, Eske de Crop, Annemieke Verbeken, Mariana Sà, Bart Buyck, Maria-alice Neves, Aída Vasco-palacios, Felipe Wartchow, et al.

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Jan Hackel, Terry W Henkel, Pierre-arthur Moreau, Eske de Crop, Annemieke Verbeken, et al. Biogeographic history of a large clade of ectomycorrhizal fungi, the Russulaceae, in the Neotropics and adjacent regions. New Phytologist, 2022, 236 (2), pp.698-713. 10.1111/nph.18365. hal-04035633

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Biogeographic history of a large clade of ectomycorrhizal fungi,
the Russulaceae, in the Neotropics and adjacent regions

Jan Hackel¹,² ID, Terry W. Henkel³ ID, Pierre-Arthur Moreau⁴ ID, Eske De Crop⁵, Annemieke Verbeken⁵ ID, Mariana Sà⁶, Bart Buyck⁷ ID, Maria-Alice Neves⁸ ID, Aída Vasco-Palacios⁹ ID, Felipe Wartchow¹⁰ ID, Heidy Schimann¹¹ ID, Fabian Carriconde¹², Sigisfredo Garnica¹³ ID, Régis Courtecuisse⁴, Monique Gardes² ID, Sophie Manzi² ID, Eliane Louisanna¹¹ and Mélanie Roy²,¹⁴ ID

¹Royal Botanic Gardens, Kew, Richmond-upon-Thames TW9 3AE, UK; ²Laboratoire Evolution et Diversité Biologique (UMR 5174), Université Toulouse III – Paul Sabatier/CNRS/IRD, 31062, Toulouse cedex 9, France; ³Department of Biological Sciences, California State Polytechnic University, Humboldt, Arcata, CA 95521, USA; ⁴Faculté de Pharmacie, Laboratoire des Sciences Végétales et Fongiques (LGCgE, ER4), Université de Lille, 59006, Lille, France; ⁵Department of Biology, Ghent University, 9000, Gent, Belgium; ⁶Centro Universitário de João Pessoa, PB 58053-000, João Pessoa, Brazil; ⁷Institut de Systématique, Évolution, Biodiversité (ISYEB), Muséum National d'Histoire Naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, 75231, Paris cedex 05, France; ⁸Departamento de Botânica, Universidade Federal de Santa Catarina, SC 88040-900, Florianópolis, Brazil; ⁹Microbiología Ambiental-School of Microbiology, Laboratory of Taxonomy and Ecology of Fungi-Institute of Biology, University of Antioquia, 050010, Medellín, Colombia; ¹⁰Departamento de Sistemática e Ecologia, Universidade Federal da Paraíba, PB 58051-970, João Pessoa, Brazil; ¹¹UMR Ecologie des Forêts de Guyane, AgroParisTech/CIRAD/CNRS/Université des Antilles/Université de la Guyane/INRA, 97379, Kourou cedex, French Guiana; ¹²Institut Agronomique néo-Calédonien (IAC), Equipe Sol & Végétations (SolVeg), BP18239, 98848, Nouméa, New Caledonia; ¹³Instituto de Bioquímica y Microbiología, Universidad Austral de Chile, 5049000, Valdivia, Chile; ¹⁴Instituto Franco-Angentino para el Estudio del Clima y sus Impactos (UMI IFAECI/CNRS-CONICET-UBA-IRD), Universidad de Buenos Aires, C1428EGA, Ciudad Autonoma de Buenos Aires, Argentina

Author for correspondence:
Jan Hackel
Email: j.hackel@kew.org

Received: 22 June 2022
Accepted: 23 June 2022

New Phytologist (2022)
doi: 10.1111/nph.18365

**Key words:** boreotropical migration, dispersal, diversification, ectomycorrhizal fungi, Neotropics, Patagonia, Russulaceae, vicariance.

Summary

* The biogeography of neotropical fungi remains poorly understood. Here, we reconstruct the origins and diversification of neotropical lineages in one of the largest clades of ectomycorrhizal fungi in the globally widespread family Russulaceae.

* We inferred a supertree of 3285 operational taxonomic units, representing worldwide internal transcribed spacer sequences. We reconstructed biogeographic history and diversification and identified lineages in the Neotropics and adjacent Patagonia.

* The ectomycorrhizal Russulaceae have a tropical African origin. The oldest lineages in tropical South America, most with African sister groups, date to the mid-Eocene, possibly coinciding with a boreotropical migration corridor. There were several transatlantic dispersal events from Africa more recently. Andean and Central American lineages mostly have north-temperate origins and are associated with North Andean uplift and the general north-south biotic interchange across the Panama isthmus, respectively. Patagonian lineages have Australasian affinities. Diversification rates in tropical South America and other tropical areas are lower than in temperate areas.

* Neotropical Russulaceae have multiple biogeographic origins since the mid-Eocene involving dispersal and co-migration. Discontinuous distributions of host plants may explain low diversification rates of tropical lowland ectomycorrhizal fungi. Deeply diverging neotropical fungal lineages need to be better documented.

Introduction

A fundamental challenge of evolutionary biology is to deter-
mine the drivers of the exceptional neotropical biodiversity
(Antonelli & Sanmartín, 2011; Hughes et al., 2013; Antonelli
et al., 2018; Palma-Silva et al., 2022). Phylogenetic biogeogra-
phy has shown how continental-scale events such as the rise
of the Andes (Antonelli et al., 2009; Hoorn et al., 2010;
Pérez-Escobar et al., 2022), biotic interchange between North
and South America (Cody et al., 2010; Bacon et al., 2015),

and transoceanic dispersal, including across the Atlantic from
Africa (Pennington & Dick, 2004; Renner, 2004), have shaped
extant diversity of neotropical plants and animals. Though
some historical biogeographic studies have included neotropi-
cal fungi (Matheny et al., 2009; Leavitt et al., 2012; Wilson
et al., 2012; Tedersoo et al., 2014b; Harrower et al., 2015;
Amalfi, 2016), more are needed given the ecological impor-
tance of fungi as saprotrophs, pathogens, or mutualistic sym-
bionts, which can influence the distribution of associated
plants and vice versa (Peay et al., 2016).
Ectomycorrhizal (ECM) fungi are obligate mutualistic root symbionts, mainly of trees (Smith & Read, 2010; Tedersoo et al., 2020). They have global ecosystem importance by sustaining the biomass of the majority of trees worldwide (Soudzilovskaia et al., 2019; Steidinger et al., 2019). Unlike the majority of organisms, most ECM fungal groups peak in diversity and abundance in temperate latitudinal zones (Tedersoo & Nara, 2010; Tedersoo et al., 2014a; Steidinger et al., 2019). This suggests that they may have originated and have a longer history and/or have diversified faster in the temperate zone. Nonetheless, ECM trees are dominant in some tropical forests, where the symbiosis plays a key role in nutrient cycling and competitive abilities (Henkel, 2003; McGuire, 2007; Corrales et al., 2016, 2018; Carriconde et al., 2019; Henkel & Mayor, 2019; Hall et al., 2020). The importance of ECM fungi in the Neotropics is exemplified by the recent discoveries of high-diversity sites with many undescribed species (e.g. Henkel et al., 2012; Roy et al., 2016; Vasco-Palacios et al., 2018; Delgat et al., 2020; Corrales & Ovrebo, 2021). ECM fungi thus form an important component of many neotropical ecosystems.

The current geographic distribution of ECM fungi is the product of environment and host plant presence (van der Linde et al., 2018), as well as historical contingencies such as area of origin and dispersal limitation (Peay et al., 2016). The Neotropics contain phylogenetically diverse ECM host plants distributed across a variety of habitats and elevation zones, suggesting distinct biogeographic ECM domains. For example, ECM host plants in the neotropical lowlands are from predominantly tropical lineages in the Fabaceae, Cistaceae, Dipterocarpaceae, Polygaceae, and Nyctaginaceae, whereas mainly north-temperate Betulaceae, Fagaceae, and Juglandaceae occur at higher elevations in the Andes or Central America (Tedersoo, 2017; Tedersoo & Brundrett, 2017; Corrales et al., 2018). Patagonia, in southern South America, has yet another dominant host lineage, the Nothofagaceae, whose associated macromycota is quite removed from that of northern South America (Singer, 1953; Trierveiler-Pereira et al., 2014), although Nothofagaceae were probably present at tropical latitudes in South America in the Eocene (Jaramillo et al., 2006).

Though many ECM fungal lineages have broad distributions (Tedersoo et al., 2014a), the drivers of their biogeographic spread have been difficult to identify. A major problem is distinguishing between continental vicariance, overland migration, or overseas dispersal. Moyersoen (2006) hypothesized that Africa–South American (i.e. Gondwanan) vicariance, between 120 and 90 million years ago (Ma) (Müller et al., 2016), explained the presence of *Pakaraimaea*, a phylogenetically distinct genus of ECM host plants, in South America. Africa–South America vicariance has, however, been refuted for most other groups of plants (Pennington & Dick, 2004), including the pantropical ECM gymnosperm *Gnetum* (Won & Renner, 2006). It was also rejected for the ECM fungal genus *Inocybe* (Matheny et al., 2009). In turn, vicariance is likely responsible for the Australian–Patagonian (i.e. southern Gondwanan) disjunction of Nothofagaceae (Cook & Crisp, 2005). An alternative explanation, boreotropical migration across land routes when Palaeocene/Eocene tropical climates

extended into high latitudes (Wolfe, 1975), was suggested for disjunctions in the north-temperate host lineage Juglandaceae (Zhang et al., 2022) and the ECM fungal groups *Amanita* sect. *Caesarea* (Sánchez-Ramírez et al., 2014) and Sclerodermatinae (Wilson et al., 2012). Over the past 20 Myr, narrowing and closure of the Panama isthmus facilitated north–south dispersal (Bacon et al., 2015; O'Dea et al., 2016), and the rapid rise of the northern Andes 5–8 Ma created high-altitude environments for north-temperate arrivals (Pérez-Escobar et al., 2022). The southward extensions of the north-temperate ECM host genera *Alnus* and *Quercus* into the Andes are examples of this (Tedersoo, 2017).

An important group of mushroom-forming ECM fungi is found in the Russulaceae (Russulales, Agaricomycetes, Basidiomycota), a speciose family that is globally distributed over low and high latitudes wherever ECM vegetation is found. Recent systematic work has clarified Russulaceae relationships (Buyck et al., 2008, 2018; Verbeken et al., 2014; Wisitrassameewong et al., 2016; De Crop et al., 2017; Wang et al., 2018): the four mushroom-forming genera – *Lactarius*, *Lactifluus*, *Multifurca*, and *Russula*, along with several nested sequestrate genera – have >4500 species (He et al., 2019) and form a monophyletic ECM lineage emerging from a small grade of saprotrophic genera (Looney et al., 2018, 2022). For simplicity, we refer to this ECM lineage (equivalent to ‘russula-lactarius’ sensu Tedersoo et al., 2010a) as ‘Russulaceae’ in the following. Russulaceae are routinely recovered in sporocarp and DNA-based surveys, including in the Neotropics (Tedersoo et al., 2010b; Tedersoo & Nara, 2010; Smith et al., 2011; Henkel et al., 2012; Roy et al., 2016; Vasco-Palacios et al., 2018; Corrales & Ovrebo, 2021). They associate with most known ECM plant lineages (Tedersoo & Brundrett, 2017), as well as orchids (Dearnaley, 2007).

Most species of Russulaceae are temperate, including boreal, in distribution. This includes the majority of the largest genus *Russula*, for which a temperate origin and a higher temperate diversification rate relative to the Tropics has been inferred (Looney et al., 2016). However, a tropical African origin has long been posited for Russulaceae based on endemism and morphological distinctiveness (Pirozynski, 1983; Buyck et al., 1996). In the wider Neotropics, Russulaceae occur in all highland and lowland regions where ECM vegetation is found, and modern work has revealed a plethora of new species (Buyck & Ovrebo, 2002; Miller et al., 2002, 2012; Wartchow & Cavalcanti, 2010; Cheype & Campo, 2012; Sà et al., 2013, 2019; Sà & Wartchow, 2013, 2016; Wartchow et al., 2013; Montoya et al., 2014; Trierveiler-Pereira et al., 2014; Crous et al., 2017; Delgat et al., 2020; Duque Barbosa et al., 2020; Silva-Filho et al., 2020; Manz et al., 2021; Vera et al., 2021). Several lowland neotropical Russulaceae have affinities with tropical African species (Buyck, 1990; Buyck & Ovrebo, 2002; De Crop et al., 2017). Molecular divergence time estimates vary, however. A recent phylogenomic study (Looney et al., 2022) estimated a crown age of c. 60 Myr (uncertainty range 57–64 Myr) for the ECM Russulaceae, which places its diversification firmly after Gondwanan breakup. Prior estimates of Looney et al. (2016) and Varga et al. (2019) (58 and 83 Myr, respectively) also supported a post-Gondwanan scenario.
A much older estimate of 188 Myr (Sánchez-García *et al.*, 2020) appears to be an outlier (Fig. 1), pre-dating even the radiation of the oldest ECM host plant lineage, Pinaceae, in the Late Jurassic (Tedersoo, 2017). Here, we assume that the ECM Russulaceae diversified when South America was already separated from Africa, and we reconstruct their biogeographic history in the Neotropics under this scenario.

To accomplish this, we generated a time-calibrated phylogeny by supplementing a backbone tree of globally representative sequences with new data from a large, collaborative sampling effort focusing on the Neotropics. The resulting supertree was used to estimate range evolution and diversification. We tested the following hypotheses regarding neotropical Russulaceae:

(1) Tropical South American lowlands host old lineages that are related to tropical African taxa, whereas the Andes and the adjacent Patagonia have younger lineages unrelated to tropical lowland taxa.

(2) Dispersal into the Neotropics coincided with Palaeocene and Eocene boreotropical conditions and the closure of the Panama isthmus.

(3) Tropical South America and with other tropical areas have a lower diversification rate than temperate areas.

## Materials and Methods

### Sample collection and sequencing

We aimed to generate a phylogenetic tree of Russulaceae that is globally representative and well sampled for the Neotropics. We collected sporocarps and ECM root tips, and obtained samples from dried fungarium specimens, from several neotropical and neighbouring countries: Belize, Brazil, British Virgin Islands, Chile, Colombia, Costa Rica, Ecuador, French Guiana, Guadeloupe, Guyana, Martinique, Panama, and Puerto Rico. Tissue samples were preserved in 2x cetyltrimethyl ammonium

bromide solution. DNA was extracted using a Wizard Genomic DNA Purification kit (Promega). We were able to amplify the internal transcribed spacer (ITS) region from 241 specimens, using standard primers and protocols (Gardes & Bruns, 1993). In addition, partial large ribosomal subunit (LSU; primers CTB6 + TW14 (White *et al.*, 1990), or LR0R + LR7 (Vilgalys & Hester, 1990)) and partial RNA polymerase II gene, second largest subunit (*rpb2*; primers fRPB2-5F + bRPB2-7cR (Liu *et al.*, 1999)), were amplified for 222 and 43 samples, respectively. Amplicons were then Sanger-sequenced (GATC Biotech, Konstanz, Germany, or Macrogen, Lille, France) and chromatograms edited in *GENEIOUS v.6* (Biomatters, Auckland, New Zealand).

### Internal transcribed spacer dataset assembly

To produce a tree that would include as much diversity of Russulaceae as possible, including undescribed taxa and environmental samples, we used an approach based on operational taxonomic units (OTUs) similar to that of Looney *et al.* (2016).

We downloaded all 35 944 ITS sequence records annotated as Russulaceae (as of August 2021) on the International Nucleotide Sequence Database Collaboration or the fungal sequence database UNITE (Kõljalg *et al.*, 2013) using the PLUTOF web platform (https://plutof.ut.ee). Sequences annotated as 'chimeric' were excluded, and we added our 241 new ITS sequences. The ITS1–5.8S–ITS2 region was extracted from this set using ITSx v.1.1.3 (Bengtsson-Palme *et al.*, 2013), keeping only matches at least 50 bp long. Nineteen sequences associated with backbone tips (see later) that did not pass this filtering step were added back in. The resulting set of 29 479 sequences was then clustered into OTUs using VSEARCH v.2.9.1 (Rognes *et al.*, 2016) with the cluster representative being the longest sequence (--cluster_fast option). We used a 97% identity threshold, which is probably conservative (i.e. lumping species) but appropriate for the macroevolutionary scale of our study. Sequences clustered into 3543 OTUs, and their representative sequences were used for subsequent analyses.

### Phylogenetics

A 'supertree' approach was used, estimating first a backbone phylogeny using conserved markers and then inserting backbone-constrained, genus-level phylogenies estimated from the ITS sequences. For the backbone, we first assembled a set of nuclear LSU (nrLSU) (28S), *rpb1* (RNA polymerase II gene, largest subunit), and *rpb2* sequences from 437 accessions of Russulaceae and seven outgroup Russulales, based on previous studies (Buyck *et al.*, 2008, 2018, 2020; Verbeken *et al.*, 2014; Looney *et al.*, 2016; De Crop *et al.*, 2017; Wang *et al.*, 2018). We added 28 of the newly sequenced Russulaceae for which nrLSU and/or *rpb2* were amplified successfully. In the backbone accessions, 324 matched accessions in the ITS dataset and were used to constrain the genus phylogenies (see later). Sequences for each locus were aligned with MAFFT/E-INS-I v.7.407 (Katoh & Standley, 2013), end columns with >90% missing data were trimmed, and

<figure><img src="image_4.png" /><figcaption>**Fig. 1** Overview of published crown age estimates for the ectomycorrhizal Russulaceae (*Lactarius*, *Lactifluus*, *Multifurca*, and *Russula*). The Looney *et al.* (2022) estimate (in bold) was used for calibration in this study. Dots are median values/point estimates, error bars represent 95% posterior density intervals (Looney *et al.*, 2016, 2022) and the range in 10 calibrated trees (Varga *et al.*, 2019).</figcaption></figure>
alignments then concatenated. A maximum likelihood phylogeny was estimated using RAxML v.8 (Stamatakis, 2014), a GTR+Γ substitution model for each of the LSU, *rpb1*, and *rpb2* partitions, and 1000 rapid bootstrap searches. Transfer bootstrap expectation (TBE) was calculated in addition to traditional Felsenstein bootstrap support, which is sensitive to 'rogue taxa' in large datasets (Lemoine *et al.*, 2018).

We then estimated phylogenies from the ITS dataset of representative OTU sequences. To improve alignment and tree estimation, we divided them into three genus datasets (combining the small *Multifurca* with its sister *Lactarius*). The ITS sequences were searched via BLASTN (Altschul *et al.*, 1990) against the ITS sequences associated with backbone tips to assign them to a genus dataset. Sequences with <70% similarity to a backbone ITS sequence and only a single OTU member were discarded as likely chimeric or mislabelled as Russulaceae. Rapid alignments and trees were made with MAFFT (automatic option) and FASTTREE v.2.1.10 (Price *et al.*, 2010) for visual inspection. We removed a further three sequences that appeared as conspicuously long branches. The final set of ITS sequences per genus was then aligned (with suitable outgroup sequences from the other genera) using MAFFT/E-INS-I. Alignments were trimmed and RAxML trees inferred as described for the backbone, specifying ITS1, 5.8S, and ITS2 partitions; splits that had a TBE support of 0.7 or higher in the backbone tree were constrained in the tree search.

To generate a single Russulaceae supertree, we first time-calibrated the backbone tree, with outgroups removed, using penalized likelihood in TREEPL v.1.0 (Smith & O'Meara, 2012). The smoothing parameter value was selected through random-subsample-and-replicate cross-validation for orders of magnitude between $10^{-1}$ and $10^3$. In the absence of known Russulaceae fossils, we fixed the crown age to 1. Subclade trees were time-calibrated in the same manner (with a further 83 long-branch tips removed) and then inserted into the backbone tree using the 'bind.tree' function in R, scaling branch lengths relative to the backbone crown age of the clade replaced. To provide an absolute timescale, we report ages obtained when multiplying branch lengths with the age estimate of Looney *et al.* (2022); that is, 60 Myr with a range of 57–64 Myr (Fig. 1). The final supertree contained 3285 tips, corresponding to OTUs identified in the ITS dataset and representing 29 167 ITS sequences.

For phylogenetic tree manipulation and plotting, we used the packages APE v.5.3 (Paradis & Schliep, 2019), GEIGER v.2.0.6.1 (Harmon *et al.*, 2008), PHYTOOLS v.0.6.60 (Revell, 2011), and PLOTRIX v.3.7.5 (Lemon, 2006) in R v.3.6.1.

## Biogeographic areas

We compared the biogeographic histories of Russulaceae among parts of the Neotropics and adjacent regions that feature different ECM host plant assemblages (Tedersoo, 2017; Nouhra *et al.*, 2019; Delgat *et al.*, 2020) (Fig. 1a): (1) Central America/Caribbean, with both tropical-origin ECM host plant lineages such as *Coccoloba* or Nyctaginaceae tribe Pisonieae and temperate-origin Fagaceae, Juglandaceae, and Pinaceae. (2) The Andes, with the temperate-derived *Alnus acuminata*, widespread

in the central part of the range, and *Quercus humboldtii*, restricted to northern Colombia, and some lowland Nyctaginaceae that reach the montane Yungas (Geml *et al.*, 2014). (3) Lowland tropical South America, with several distinct, tropical host plant groups in the Cistaceae, Fabaceae, Polygonaceae, Nyctaginaceae, Dipterocarpaceae (e.g. *Dicymbe*, *Aldina*, *Coccoloba*, *Guapira*, *Neea*, *Pakaraimaea*, *Pseudomonotes*). (4) Patagonia, with Nothofagaceae (Tedersoo, 2017). We defined these areas by merging the corresponding ecoregions of Morrone (2014, 2015), using the shapefiles of Löwenberg-Neto (2014, 2015). The rest of the global range of Russulaceae was divided into the five broad regions Afrotropics, Australasia with Oceania, Indomalaya, Nearctic, and Palaearctic (Fig. 1a; Dinerstein *et al.*, 2017).

Operational taxonomic units were assigned to one or more of these areas first by the country recorded for each ITS sequence clustering with the OTU, if this was unambiguous. We then used, in the following order, sampling coordinates, area descriptions geocoded with the 'geocode_OSM' R function, and information from the original literature associated to the record (for some of the remaining unassigned tips) to assign remaining sequences, using the R packages SF (Pebesma, 2018) and TMAP-TOOLS (Tennekes, 2020). A total of 25 937 sequences (88.9% of those represented in the supertree) and 3153 OTUs (96%) could be assigned in this way (Table 1). We plotted the tip areas against the tree for visual inspection. In five instances, the placement (isolated tropical South American or Patagonian tip inside a north-temperate clade) and the host and sampling metadata suggested introduced occurrences; these areas were ignored.

We summarized the overlap in OTUs between areas to assess recent dispersal and compared it with estimates of more ancient dispersal (see later).

## Biogeographic modelling

We estimated ancestral areas using a simple Markov model of trait evolution. The frequently used dispersal-extinction-

<table><caption>**Table 1** Overview of internal transcribed spacer (ITS) sequences and operational taxonomic units (OTUs) by geographic area.</caption><thead><tr><th>Area</th><th>ITS sequences</th><th>OTUs</th></tr></thead><tbody><tr><td><strong>Focal</strong></td><td></td><td></td></tr><tr><td>Andes</td><td>46</td><td>0.2%</td><td>22</td><td>0.7%</td></tr><tr><td>Central America/Caribbean</td><td>514</td><td>1.8%</td><td>213</td><td>6.5%</td></tr><tr><td>Patagonia</td><td>16</td><td>0.1%</td><td>9</td><td>0.3%</td></tr><tr><td>Tropical S. America</td><td>303</td><td>1%</td><td>109</td><td>3.3%</td></tr><tr><td><strong>Nonfocal</strong></td><td></td><td></td></tr><tr><td>Afrotropic</td><td>1055</td><td>3.6%</td><td>417</td><td>12.7%</td></tr><tr><td>Australasia and Oceania</td><td>445</td><td>1.5%</td><td>226</td><td>6.9%</td></tr><tr><td>Indomalayan</td><td>1585</td><td>5.4%</td><td>659</td><td>20.1%</td></tr><tr><td>Nearctic</td><td>4550</td><td>15.6%</td><td>737</td><td>22.4%</td></tr><tr><td>Palearctic</td><td>17 423</td><td>59.7%</td><td>1293</td><td>39.4%</td></tr><tr><td>Unassigned</td><td>3230</td><td>11.1%</td><td>132</td><td>4%</td></tr><tr><td>Total</td><td>29 167</td><td></td><td>3285</td><td></td></tr></tbody></table>

The numbers shown are for sequences represented in the final Russulaceae supertree, after various filtering steps. Note that OTU numbers and percentages do not sum to 100% as one OTU can occur in several areas.
cladogenesis model (Ree *et al.*, 2005) proved too computationally
expensive for our phylogeny and also has various issues (Ree &
Sanmartín, 2018). We fitted a one-parameter trait evolution
model to the supertree and the tip areas assigned in the CORHMM
R package v.2.7 (Beaulieu *et al.*, 2021), which can handle poly-
morphic tips and missing values.

With the estimated ancestral areas, we summarized lineages
that have a relative likelihood of > 0.5 to occur in one of the four
focal areas. We recovered their stem ages (divergence from groups
outside the focal areas) and, if applicable, crown ages (first diver-
gence within the focal areas). We then assessed, under the two
ages scenarios, whether these ages coincide with the following
biogeographic events: the split between South America and
Antarctica, 50 Ma (van de Lagemaat et al., 2021); boreotropical
conditions during the Palaeocene and Eocene (Wolfe, 1975);
rapid north Andean uplift, 8–5 Ma (Pérez-Escobar et al., 2022);
and the Panama isthmus biotic interchange, beginning 20 Ma
(O'Dea et al., 2016).

To count the number of dispersal events (i.e. area state
changes) and infer dispersal rates *post hoc*, we stochastically
mapped area evolution histories on the supertree 100 times using
the 'makeSimmap' function in CORHMM. From these stochastic
maps, we obtained median values and 95% quantile ranges of
dispersal counts between areas. We also summarized dispersal
counts to and from each area over time. For this, we used 10
equal-sized time windows since the origin of Russulaceae (repre-
senting 6 Myr windows under our calibration), which proved a
reasonable compromise between detecting patterns in time vs
uncertainty (i.e. the smaller the windows, the more uncertainty
there is around the event counts).

Diversification analysis

Diversification rates were estimated for the full tree using BAMM v.2.5 (Rabosky, 2014). Critique, especially of earlier versions of BAMM (Moore et al., 2016), has been addressed (Rabosky et al., 2017); BAMM was best suited to our purpose as we needed specific per-branch rates for comparing diversification rates per area (see later). We ran BAMM for 200 million Markov chain Monte Carlo generations and sampling every 10 000th generation. Effective sample sizes were ensured to be > 200 using the R package CODA (Plummer et al., 2006), and the first 20% of posterior samples were discarded as burn-in. Note that the conservative ITS clustering cut-off likely underestimated the number of species, and thus the most recent diversification rates.

In the absence of a feasible method to jointly model diversifica-
tion and range evolution (Goldberg et al., 2011) for such a large
phylogeny and multiple areas, we partitioned per-branch diversi-
fication rates by area in an approach similar to Chazot
et al.(2021). We randomly paired the BAMM posterior samples
with the area evolution stochastic maps. For each pair, the tree
branches were divided into segments with the same range and
diversification regime and no longer than 2% of the root height.
We then calculated the mean and 95% credible interval of
diversification rate per area, both overall and for each of 20

equal-sized time windows. The R code for this is available in the
online repository.

Results

Internal transcribed spacer sequences and occurrence in
biogeographic areas

We compiled a dataset of 29 167 global ITS sequences of the ecto-
mycorrhizal Russulaceae clade. These were obtained through a
series of filtering steps applied to 35 944 sequences retrieved from
public databases, combined with 241 new sequences generated for
neotropical taxa. These sequences clustered into 3285 OTUs at a
97% similarity threshold, represented as tips in the Russulaceae
supertree (Table 1), with 2234 belonging to *Russula*, 565 to *Lac-
tarius*, 472 to *Lactifluus*, and 14 to *Multifurca*. Of these, 879
sequences and 353 OTUs could be assigned to one of four focal
areas of the Neotropics and adjacent regions, with Central Amer-
ica/Caribbean having the highest numbers. Most sequences and
OTUs in the dataset were assigned to the Palaearctic and Nearctic
areas, respectively. The Palaearctic was overrepresented among
sequences compared with OTUs (59.7% vs 39.4%), indicating a
higher sampling depth in this area than in the others.

Russulaceae phylogeny and divergence times

We inferred a 3285-OTU Russulaceae supertree (Fig. 2b) based on ITS phylogenies constrained with a backbone phylogeny. The 444-tip backbone phylogeny we inferred from LSU, *rpb1*, and *rpb2* data represents all named subgenera of the four Russulaceae genera (Supporting Information Fig. S1). Relationships among *Russula* subgenera were difficult to resolve in previous studies (Looney *et al.*, 2016; Bazzicalupo *et al.*, 2017; Buyck *et al.*, 2018, 2020). We recovered low Felsenstein bootstrap, but high TBE, support among *Russula* subgenera and subg. *Heterophyllidia* as sister to the other subgenera. The backbone tree also suggests – based on a single LSU sequence – that the tropical South American *Russula campinensis* is sister to the rest of the genus and does not fall in any of the subgenera described. In *Lactarius*, the poorly defined subgenus *Russularia* is para-phyletic, and several unclassified lineages diverged earlier than the named subgenera, as found previously (Verbeken *et al.*, 2014; Wisitrassameewong *et al.*, 2016). The backbone notably supported an undescribed tropical South American species from Guyana (OTU KC155399) as sister to the remainder of *Lactarius*. Within *Lactifluus*, our backbone differed from relationships found previously (De Crop *et al.*, 2017; Delgat *et al.*, 2020) in finding TBE support for sister relationships between both subg. *Lactariopsis*/subg. *Pseudogymnocarpi* and subg. *Lactifluus*/subg. *Gymnocarpi*.

Under the age scenario of Looney *et al.* (2022), the estimated
crown age of the largest genus *Russula* was c. 56 Myr (uncertainty
range 53–59 Myr), followed by *Lactifluus* at 50 Myr (47–53 Myr),
*Lactarius* at 42 Myr (40–45 Myr), and *Multifurca* at 34 Myr (32–
36 Myr) (Fig. 2; see also the calibrated backbone in Fig. S1).
<figure><img src="image_5.png" /></figure>

**Fig. 2** Ancestral range estimation and neotropical lineages of ectomycorrhizal Russulaceae (*Lactarius*, *Lactifluus*, *Multifurca* and *Russula*). (a) Defined areas, including the four focal areas (enlarged inset): Afr, Afrotropics; And, Andes; Aus, Australasia; CAm, Central America/Caribbean; Ind, Indomalaya; Nea, Nearctic; Pal, Palaearctic. (b) Dated supertree of the ectomycorrhizal Russulaceae with inferred ancestral ranges. The 3285 tips represent 29 167 internal transcribed spacer sequences clustered into operational taxonomic units. Ages are based on the previous estimate of 60 Myr (uncertainty range 47–64 Myr; Looney et al., 2022) for the crown age of the ectomycorrhizal Russulaceae. Ancestral ranges were estimated under a one-parameter trait evolution model integrating over multiple-state tips. Branches are coloured by the area with the highest relative likelihood as part of the inferred ancestral range at the child node. Relative likelihoods for ancestral areas are given as pie charts for genera, subgenera, and the Russulaceae crown node. Coloured dots indicate the stem branches of 110 lineages with an estimated origin in one of the focal areas (grey indicates that none of two or more focal areas has a relative likelihood of > 0.5). (c) Stem ages and crown ages (where applicable) of 110 lineages with an estimated origin in one of the focal areas. Grey polygons and horizontal lines indicate major biogeographic events in the region.

## Biogeographic origins and neotropical lineages

The Afrotropics were supported as the most likely ancestral area of Russulaceae in our biogeographic analysis (Fig. 2; see also all tips/OTUs detailed in Fig. S3). This was also the case for each of the three largest genera, *Lactarius*, *Lactifluus*, and *Russula*, with relative likelihoods of > 0.95 for the Afrotropics at these nodes. The earliest diverging clades at subgenus level in these three genera were also each estimated as Afrotropic in origin, except *Russula* subgenera *Russula* and *Crassotunicata* (Fig. S1a).

We found 110 distinct Russulaceae lineages occurring in the wider Neotropics, of which 76 are single-OTU lineages and 34 clades with more than one OTU (Fig. 2b,c; Table 2; see also lineages numbered in Fig. S3). The oldest lineages are found in tropical South America, with the oldest stem age at c. 42 Myr (40–45 Myr), indicating arrival in the mid-Eocene at the earliest. Some of these clades have spread to other areas: some Central American/Caribbean clades included tropical South America OTUs, and vice versa (e.g. nos. 53, 60, 66 and 73 in *Russula*, and nos. 106, 107 and 110 in *Lactifluus*; Fig. S3), whereas one tropical South American clade of *Lactifluus* (no. 106) included Australasian taxa. Estimated ages of these lineages allow us to assess whether they overlap with major biogeographic events that have shaped the regional biota (Fig. 2c).

The seven Andean lineages in *Russula*, *Lactarius*, and *Lactifluus* all appeared to have immigrated relatively recently, with no diversification *in situ*. The stem ages of all but one lineage (which appears as an old outlier) coincide with or are younger than the rapid north Andean uplift 5–8 Ma. These Andean lineages mainly emerge from Nearctic and/or Palaearctic clades, consistent with north-to-south migration. Only two Nyctaginaceae-associated OTUs from the Yungas emerge from lowland tropical South American clades (*Lactifluus* UDB004277|L6094 and *Russula* UDB004278|L6090c; Fig. S3). There were also 12 Andean OTUs shared with other areas, mainly Central America/Caribbean and the Nearctic (Fig. 3a), suggesting very recent immigration into the Andes.

The four Patagonian lineages (*Russula*: nos. 7, 8 and 61; *Lactarius*: no. 94; Fig. S3c,r,ae) diverged at different times since c. 18 Ma and much more recently than the South America–Antarctica split. All four emerge from within or are sister to Australasian clades. Note that ITS sequences appear to be the only record of *Lactarius* associated with *Nothofagus* – based on sequence metadata – in the Patagonian region, as the genus was not listed in a previous overview (Barroetaveña et al., 2019). These and their closest relatives from Australasia represent a yet undescribed clade of *Lactarius*.
<table><caption>**Table 2** Overview of Russulaceae lineages in the Neotropics and adjacent regions.</caption><thead><tr><th>Area</th><th>No. of lineages</th><th>Of which clades</th><th>Oldest crown ages (Myr)</th><th>Oldest stem age (Myr)</th></tr></thead><tbody><tr><td>Andes</td><td>7</td><td>0</td><td>—</td><td>16.3 (15.4–17.3)</td></tr><tr><td>Central America/Caribbean</td><td>80</td><td>16</td><td>13.1 (12.5–14)</td><td>26.3 (25–28.1)</td></tr><tr><td>Patagonia</td><td>4</td><td>3</td><td>11.8 (11.2–12.5)</td><td>17.8 (16.9–18.9)</td></tr><tr><td>Tropical South America</td><td>19</td><td>15</td><td>29.9 (28.4–31.9)</td><td>42.4 (40.3–45.2)</td></tr></tbody></table>

These represent lineages that have an ancestral relative likelihood of > 0.5 to occur in the area but may also occur in other areas. Ages are based on the previous estimate of 60 Myr (uncertainty range 47–64 Myr; Looney *et al.*, 2022) for the crown age of the ectomycorrhizal Russulaceae. Values in parentheses are age uncertainty ranges based on the 95% highest posterior density interval (57–64 Myr) of Looney *et al.* (2022).

**Fig. 3** Connectivity between biogeographic areas in the ectomycorrhizal Russulaceae (*Lactarius*, *Lactifluus*, *Multifurca*, and *Russula*). (a) Overlap in operational taxonomic units (OTUs) between areas. Edge thickness is proportional to the number of shared OTUs. (b) Inferred numbers of dispersal events between areas. Edge thickness is proportional to the number of dispersals. Edges were only drawn for rates whose 95% quantile range excludes zero. The counts are mean numbers of dispersals inferred from stochastic mapping under the estimated dispersal/area transition rate.

<figure><img src="image_6.png" /></figure>

The 80 lineages from Central America/Caribbean occurred in *Russula*, *Lactarius*, and *Lactifluus*. Whereas *Multifurca* occurs in Central American oak forests (Montoya *et al.*, 2003; Wang *et al.*, 2018), no ITS sequence assignable to that area was available. None of the lineages is old enough to have diverged under Palaeocene boreotropical conditions. All but three ages are coincident with the increased biotic interchange across the Panama isthmus. The large majority of Central American/Caribbean lineages emerged from north-temperate clades, whereas some occurred in clades with South American relatives.

Of the 19 lowland tropical South American lineages, several branched deeply at subgenus level. In *Russula*, a clade composed of *R. campinensis* (an unusual pleurotoid species from lowland tropical South America; Henkel *et al.*, 2000) and three related OTUs branched at *c.* 33 Ma (no. 82, Fig. S3x). Together with OTUs from several other areas, this group is sister to the remainder of *Russula*. From Guyana, KC155399 with two sequences (no. 95) represents an undescribed lineage of *Lactarius* sister to the rest of the genus (Fig. S3a). Another well-supported ancient lowland tropical South American clade of *Lactarius* resides in subg. *Plinthogalus* (no. 93, Fig. S3a,e). In *Lactifluus*, our tree places a lowland tropical South American clade with *Lactifluus ceraceus* and related OTUs (no. 105, Fig. S3a) sister to subg. *Lactifluus* and not in subg. *Pseudogymnocarpi* (Crous *et al.*, 2017).

All lowland tropical South American lineages diverged well after the Africa–South America split. However, several of these

old lineages were sister to clades with an estimated African origin (e.g. nos. 42, 62 and 82 in *Russula*; no. 95 in *Lactarius*; nos. 105, 106 and 101 in *Lactifluus*). Boreotropical migration can potentially account for these relationships in seven lineages that diverged in the Eocene. The other 12 lineages were too young for boreotropical migration. The youngest of these is a South American lineage clearly emerging from within an African clade (no. 63, *Russula puiggarii* and relatives) at *c.* 9 Ma, strongly suggesting direct dispersal across the Atlantic.

## Dispersal to and from the Neotropics

We summarized overlap in OTUs between areas, representing recent dispersal, and also estimated past dispersal events between them (Fig. 3). Two higher latitude areas, Nearctic and Palaearctic, have the highest OTU overlap (Fig. 3a) and the highest estimated dispersal count (Fig. 3b), followed by the Palaearctic and Indomalaya. Patagonia shared no OTU with any of the focal areas of the Neotropics. It, however, had possible ancient dispersal links with several other areas, which may reflect the uncertainty in simulating dispersal routes along branches, as plotting of ancestral areas strongly suggested the Patagonian lineages are related to Australasian lineages, as already noted herein. The Andes were most strongly linked with the Nearctic and Central America/Caribbean. Central America/Caribbean was most strongly linked with the Nearctic and Palaearctic. Lowland tropical South America only shared
<figure><img src="image_7.png" /></figure>

**Fig. 4** Dispersal to and from the Neotropics through time in the ectomycorrhizal Russulaceae (*Lactarius*, *Lactifluus*, *Multifurca* and *Russula*). The counts are median numbers of dispersals inferred from stochastic mapping for 10 equally spaced time periods between the root of Russulaceae and the present. Values are given for (a–d) the four focal areas and (e) specifically for dispersal between the Afrotropics and tropical South America. Shaded areas are 95% quantile ranges. Ages are based on the previous estimate of 60 Myr (uncertainty range 47–64 Myr; Looney *et al.*, 2022) for the crown age of the ectomycorrhizal Russulaceae. Crown ages of the four genera are indicated for reference (Ru, *Russula*; Lf, *Lactifluus*; La, *Lactarius*; Mu, *Multifurca*). Ma, million years ago.

OTUs with Central America/Caribbean but had most dispersal links with the Afrotropics.

We also summarized Russulaceae immigration and emigration for the neotropical focal areas (Fig. 4). All areas showed an

increase towards the present, reflecting their increasing number of extant lineages over time. In most areas, immigration and emigration were roughly equal across time periods, but a markedly stronger recent increase in immigration compared with emigration was seen in Central America/Caribbean. Dispersals to lowland tropical South America were mostly unidirectional from the Afrotropics, albeit with large uncertainty intervals (Fig. 4e).

## Diversification rates

The estimated per-branch net diversification rates ranged from $c. 0.06$ to $0.9 \text{ Myr}^{-1}$ (Fig. 5a). There were rate increases in some clades, such as at the base and within *Lactarius* subg. *Lactarius*, in the crown clade of *Lactifluus* subg. *Lactifluus*, and within *Russula* subg. *Heterophyllidia*. *Russula* subg. *Russula* exhibited a rapid, mainly temperate crown diversification. Partitioning diversification rates by area showed that the Nearctic and Palaearctic had diversification rates on average *c.* 1.3–1.4 times higher than those of tropical South America, the Afrotropics, and Patagonia, with the Andes and Central America/Caribbean exhibiting intermediate values (Fig. 5b).

Diversification rates plotted over time for the different areas are shown in Fig. 6. The putative area of origin for Russulaceae, the Afrotropics, showed a steady decline in diversification from initially high values at the crown diversification (Fig. 6e). By contrast, in the Nearctic and Palaearctic there were much more recent peaks at *c.* 9–12 Ma followed by a slowdown. Diversification also declined in tropical South America after the possible first emergence of lineages there at *c.* 35–40 Ma. In the Andes and Central America/Caribbean, there were slight recent upticks in diversification (Fig. 6a,b).

## Discussion

A tropical African origin of ectomycorrhizal Russulaceae but fastest diversification in the temperate zone

We estimated that the speciose, globally distributed ECM clade in Russulaceae, as well its three largest genera, likely originated in tropical Africa (Fig. 1). An Afrotropical origin for Russulaceae had long been postulated (Pirozynski, 1983; Buyck *et al.*, 1996) but a biogeographic analysis of the largest genus, *Russula* (Looney *et al.*, 2016), suggested a temperate origin for that genus. This discrepancy for *Russula* may be explained by increased collection and sequencing having led to tropical taxa now being better represented in phylogenetic analyses (Buyck *et al.*, 2018). Early diverging tropical lineages in *Russula* were revealed in our study, possibly resulting from our larger sampling of ITS sequences – 18 778 ITS sequences compared with 3348 in Looney *et al.* (2016). Unstable relationships among the major lineages of *Russula* were found in previous studies (Looney *et al.*, 2016; Bazzicalupo *et al.*, 2017; Buyck *et al.*, 2018, 2020). The fact that we inferred African origins for most subgenera within *Russula*, however, supports an overall Africa origin of *Russula* even if the true relationships were different. Thus, results for both the largest genus, *Russula*, and
<figure><img src="image_8.png" /></figure>

**Fig. 5** Net diversification across clades and areas in the ectomycorrhizal (ECM) Russulaceae (Lactarius, Lactifluus, Multifurca, and Russula). Diversification rates were inferred with *BAMM* v.2.5 (Rabosky, 2014). (a) Per-branch net diversification rates averaged across posterior samples. The full 3385-tip supertree is shown with the distribution of tips. Ages and rates are based on the previous estimate of 60 Myr (uncertainty range 47–64 Myr; Looney *et al.*, 2022) for the crown age of the ECM Russulaceae. Subgenera containing clades with increased diversification rates are labelled. Ma, million years ago. (b) Net diversification rates per area. Violin plots are coloured by area; the white dots represent median values, and thick and thin vertical lines show 1× and 1.5× interquartile ranges, respectively. Diversification rates were averaged for branch segments in random pairs of *BAMM* posterior samples with stochastic ancestral area maps.

the earliest diverging genus, *Lactifluus*, further support the overall African origin of Russulaceae.

Tropical origins have been inferred for several ECM fungal lineages (Matheny et al., 2009; Dentinger et al., 2010; Kennedy et al., 2012; Sánchez-Ramírez et al., 2014; Han et al., 2018). In many of these groups, including Russulaceae, the greater species diversity in higher latitude regions therefore likely results from more recent, faster diversification relative to the Tropics. This is supported by our results of highest rates in the Nearctic and Palaearctic and the lowest in the Afrotropics and tropical South America (Fig. 5b), where it declined over time (Fig. 6). Most likely, the vast temperate and boreal forests dominated by ECM host lineages, such as Fagaceae and Pinaceae, offered opportunities for rapid diversification of lineages, as suggested previously (Bruns et al., 1998; Ryberg & Matheny, 2012; Looney et al., 2016). By contrast, the discontinuous,

clustered host distribution in the Tropics would have offered less niche space. Our dispersal analyses corroborated this scenario, with both a high number of shared OTUs and dispersals between the north-temperate regions (Fig. 3). The rapid increases of diversification rates we observed for Russulaceae in the Nearctic and Palaearctic indeed coincide with the spread of temperate vegetation after the Eocene thermal optimum (Zachos et al., 2001). Some of these north-temperate lineages then migrated southward again into tropical latitudes, including Central America and the Andes (see later).

We suggest that ECM fungal diversity in tropical areas accumulated over a longer time period and more gradually than at higher latitudes. There are, however, also young clades of Russulaceae both in the Neotropics and Palaeotropics, and a simplistic terminology of ‘cradles’ vs ‘museums’ of biodiversity should probably be avoided (Vasconcelos et al., 2022). Further discoveries of fossil fungi, as well
<figure><img src="image_9.png" /><figcaption>**Fig. 6** Diversification rates within areas through time in the ectomycorrhizal (ECM) Russulaceae (Lactarius, Lactifluus, Multifurca and Russula). Diversification rates were averaged for branch segments in random pairs of BAMM posterior samples with stochastic ancestral area maps, for 20 equally spaced time periods between the root of Russulaceae and the present. (a–i) Rates for the nine biogeographic areas defined, with the focal areas at the top (a–d). Shaded areas are 95% quantile ranges. Ages and rates are based on the previous estimate of 60 Myr (uncertainty range 47–64 Myr; Looney et al., 2022) for the crown age of the ECM Russulaceae. Crown ages of the four genera are indicated for reference (Ru, Russula; Lf, Lactifluus; La, Lactarius; Mu, Multifurca). Afr, Afrotropics; And, Andes; Aus, Australasia; CAm, Central America/Caribbean; Ind, Indomalaya; Nea, Nearctic; Pal, Palaearctic; Ma, million years ago.</figcaption></figure>

as ECM host plants, will hopefully refine the timeline of ECM fun-
gal biogeography, especially in the Tropics.

Lowland neotropical Russulaceae: ancient lineages,
potential boreotropical migration, and evidence for
transatlantic dispersal

Lowland tropical South America harbours several deep-
branching lineages within *Russula*, *Lactifluus*, and *Lactarius*, and
most have affinities with tropical African lineages (Fig. 3b).
Gondwanan vicariance is ruled out under the age scenario we
considered. Splits between African and neotropical lineages are
moreover asynchronous in time, making vicariance unlikely even
if the very old age estimate of Sánchez-García *et al.* (2020) were
accepted. Migration across an Eocene boreotropical vegetation
corridor, supposedly together with host plants, could explain
some of the oldest Africa–South America divergences in

Russulaceae. The ECM dipterocarp genus *Pseudomonotes* from
northern South America diverged from its tropical African sister
genus in the Eocene, so it could have co-migrated during that
time (Bansal *et al.*, 2022). The monotypic *Pakaraimaea* is proba-
bly older, but its precise affinities and age are yet to be confirmed
(Ashton *et al.*, 2021). Both these ECM hosts are dominated by
Russulaceae mycobionts in northern South America (Smith *et al.*,
2013; Vasco-Palacios *et al.*, 2018).

Several of the lowland South American lineages with African
ancestors must have dispersed across the Atlantic, as they diverged
after boreotropical conditions. The peak of dispersal from Africa to
South America occurred after c. 30 Ma (Fig. 4). Tropical transat-
lantic dispersals are well evidenced in some tropical plant lineages
(Pennington & Dick, 2004; Hughes *et al.*, 2013). The successful
dispersal of ECM fungi across oceans seems unlikely, as spores must
survive the long journey and encounter a suitable habitat with a
compatible host tree (Kropp & Albee-Scott, 2010; Horton *et al.*,
2013). Various mechanisms of dispersal are debated, including by
wind or birds (Caiafa et al., 2021), but also co-dispersal of fungi
and host plants (Golan & Pringle, 2017). Spore attachment to float-
ing fruits has been suggested as a means of fungal co-dispersal with
propagules of ECM Pisonia (Kropp & Albee-Scott, 2010) and Coc-
coloba (Séne et al., 2018). Rafting of entire trees with roots and soil
could theoretically vector plants and their fungal symbionts (Golan
& Pringle, 2017). Possible ECM host candidates for co-dispersal
from Africa to the Neotropics are *Aldina* and *Dicymbe*, which
diverged from African ancestors in the Oligocene to Miocene, and
thus after boreotropical conditions (Tedersoo, 2017). Extant species
of these genera are major ECM host plants throughout the Guiana
Shield and host a plethora of ECM fungi, including Russulaceae
(Singer et al., 1983; Moyersoen, 1993; Smith et al., 2011; Vasco-
Palacios et al., 2018).

North-to-south migration into the Neotropics

Most Russulaceae in the Andes have biogeographic affinities with
north-temperate lineages, distinct from those of lowland tropical
South America (with the exception of Nyctaginaceae-associated
species in the lower Yungas). We also found more OTUs shared
between the Andes and northern regions than OTUs unique to
the Andes, indicating recent range expansion. This suggests co-
migration with *Alnus* and *Quercus* as they moved southward in
the Pleistocene (Tedersoo, 2017). *Alnus acuminata* is a
widespread pioneer species in middle elevation zones from Mex-
ico to the Andes (Wicaksono et al., 2017), and southward co-
migration of the ECM host species and its mycobionts has been
suggested previously (Kennedy et al., 2011).

In Central America and the Caribbean, immigration from the
north, at a time of generally increased biotic exchange, appears to
be the dominant dispersal direction. This is coherent with the
importance of north-temperate hosts such as *Quercus* and *Pinus*
in the region (Halling & Mueller, 2005; Tedersoo, 2017). Our
data indeed show a strong recent increase in Russulaceae immi-
gration vs emigration (Fig. 4b). However, South American Rus-
sulaceae lineages have also migrated northwards into the region.
Delgat *et al.* (2020) previously showed that most *Lactifluus* species
on Caribbean islands have South American affinities as opposed
to north-temperate-derived Central American species (Delgat
*et al.*, 2020). The neotropical host lineages *Coccoloba* or *Pisonieae*
probably moved northwards with their mycobionts before the
Panama isthmus closure (Tedersoo, 2017). Clearly, the Central
American/Caribbean region, which we defined very broadly here,
has been a zone of exchange between north-temperate and
neotropical lineages, which must have involved dispersal path-
ways across the Caribbean islands.

A distinct Patagonian ectomycorrhizal macromycota

The Patagonian macromycota has long been recognized as distinct (Singer, 1953; Trierveiler-Pereira et al., 2014). Our results demonstrated that Patagonian Russulaceae have no affinity with either Andean or tropical lowland South American Russulaceae, despite the fact that the sole extant Patagonian host plant group

Nothofagaceae extended considerably northward in Eocene South America (Jaramillo et al., 2006). Divergence times of Patagonian Russulaceae do not indicate a vicariant association with the South America–Antarctica split, unlike in the *Nothofagus*-specific fungal parasite *Cyttaria* (Peterson et al., 2010). Even during the increasing glaciation of Antarctica, *Nothofagus* likely persisted in coastal areas until the Pleistocene (Poole & Cantrill, 2006) and provided geographic ‘stepping stones’ for bird-vectored ECM fungal dispersal between South America and Australasia (Caiafa et al., 2021).

Conclusions

Most biogeographic studies of the Neotropics have focused on
plants or animals. Here, we explored the neotropical biogeogra-
phy of one of the largest families of ECM fungi, the Russulaceae,
drawing the following conclusions:

(1) Tropical South American lowlands host several old lineages related to tropical African taxa, whereas the Andes and the adjacent Patagonia have younger, unrelated lineages.

(2) Some lineages may have dispersed into lowland tropical South America during Palaeocene/Eocene boreotropical conditions. Several, however, immigrated more recently via transatlantic dispersal from tropical Africa. Most origins of Central American/Caribbean taxa coincide with general increased biotic interchange across the closing Panama isthmus.

(3) Tropical South America and the Afrotropics have lower diversification rates than temperate areas, probably due to the discontinuous distribution of ECM hosts.

Our analysis demonstrates the need for more taxonomic and eco-
logical work on neotropical ECM fungi. In the Russulaceae, several
deep-branching neotropical lineages remain to be described. Our
coarse-scale analysis needs to be followed by detailed regional work
on host and environmental drivers of neotropical ECM fungal bio-
geography. Russulaceae have adapted to environments as contrast-
ing as wet Amazonia (Singer & Araujo, 1979; Singer &
Aguiar, 1986; Vasco-Palacios et al., 2018) and the semi-arid
Caatinga (Sà et al., 2019), which we here all lumped under one geo-
graphic unit. Neotropical ECM fungi are phylogenetically diverse
and may well perform unique and potentially irreplaceable ecologi-
cal functions that need to be documented. This is particularly
urgent in a time when neotropical forests are being destroyed at
unprecedented levels (Gomes et al., 2019).

Acknowledgements

JH was funded by a 'Future Leaders in Plant and Fungal Science'
fellowship by the Royal Botanic Gardens, Kew. JH and MR
received funding from the CNRS Nouragues Research Station
(Mycotin project) and from the Agence Nationale de la Recherche
(CEBA, ref. ANR-10-LABX-25-01, DIADEMA and DIAMOND
projects). TWH was supported by National Science Foundation
grants DEB-0918591, DEB-1556338, and National Geographic
Society's Committee for Research and Exploration grants 6679-99
and 7435-03. EDC was supported by the 'Special Research Fund
Ghent University' (BOF), grants B/13485/01 and BOF-PDO-
2017-001201. Computational resources used at the UK's Crop
Diversity Bioinformatics HPC (James Hutton Institute and National Institute of Agricultural Botany (NIAB)) were funded by BBSRC grant BB/S019669/1. Curators of the fungal collections at the Center for Forestry Research (Madison, WI, USA), and the Field Museum of Natural History (Chicago, IL, USA) are gratefully acknowledged for specimen loans and sampling permission. Melissa C. W. Jaeger and Jaime Duque helped collect specimens in Brazil, and Jean-Louis Cheype kindly provided specimens from French Guiana. In Guyana, Mei Lin Chin, M. Catherine Aime, and numerous Patamona indigenous field assistants participated in field work, and the Guyana Environmental Protection Agency provided research permits. The Société Mycologique de Nouvelle-Calédonie also participated in fieldwork. Laura Martínez-Suz, Oscar A. Pérez-Escobar, and Jérôme Chave provided valuable feedback on earlier versions of this manuscript. Kessy Abarenkov provided support for data download from the UNITE database, and the scientific computing teams at the James Hutton Institute and the NIAB provided technical support. Special thanks go out to Steven L. Miller and Jorinde Nuytinck for their advice during earlier stages of the study. Comments by three anonymous referees were invaluable for improving this paper.

## Author contributions

JH and MR conceived the study. TWH, EDC, AV, P-AM, BB, HS and MG helped refine the study design. JH, P-AM, TWH, M-AN, FW, RC, MS, AV-P, SG, FC and MG collected material in the field. JH, MS, AV-P, EL, FC and SM performed laboratory work. JH, MR and TWH wrote the manuscript. All authors commented and agreed on the manuscript.

## ORCID

Bart Buyck https://orcid.org/0000-0001-6824-5280

Monique Gardes https://orcid.org/0000-0001-7153-8455

Sigisfredo Garnica https://orcid.org/0000-0001-8283-9413

Jan Hackel https://orcid.org/0000-0002-9657-5372

Terry W. Henkel https://orcid.org/0000-0001-9760-8837

Sophie Manzi https://orcid.org/0000-0001-5907-6999

Pierre-Arthur Moreau https://orcid.org/0000-0003-4783-3643

Maria-Alice Neves https://orcid.org/0000-0002-1810-4890

Mélanie Roy https://orcid.org/0000-0002-4565-2331

Heidy Schimann https://orcid.org/0000-0002-9139-920X

Aída Vasco-Palacios https://orcid.org/0000-0003-0539-9711

Annemieke Verbeken https://orcid.org/0000-0002-6266-3091

Felipe Wartchow https://orcid.org/0000-0003-4930-565X

## Data availability

Data and intermediate results, as well as R scripts for dispersal and diversification analyses, are available in an open Zenodo repository (doi: 10.5281/zenodo.4727866).

## References

Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. 1990. Basic local alignment search tool. *Journal of Molecular Biology* 215: 403–410.

Amalfi M. 2016. *Fomitiporia (Basidiomycota) revisited: species concept, phylogenetic structure and biogeographical patterns*. PhD thesis, Université Catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium.

Antonelli A, Ariza M, Albert J, Andermann T, Azevedo J, Bacon C, Faurby S, Guedes T, Hoorn C, Lohmann LG *et al*. 2018. Conceptual and empirical advances in Neotropical biodiversity research. *PeerJ* 6: e5644.

Antonelli A, Nylander JAA, Persson C, Sanmartín I. 2009. Tracing the impact of the Andean uplift on Neotropical plant evolution. *Proceedings of the National Academy of Sciences, USA* 106: 9749–9754.

Antonelli A, Sanmartín I. 2011. Why are there so many plant species in the Neotropics? *Taxon* 60: 403–414.

Ashton PS, Morley RJ, Heckenhauer J, Prasad V. 2021. The magnificent Dipterocarps: précis for an Epitaph? *Kew Bulletin* 76: 87–125.

Bacon CD, Silvestro D, Jaramillo C, Smith BT, Chakrabarty P, Antonelli A. 2015. Biological evidence supports an early and complex emergence of the Isthmus of Panama. *Proceedings of the National Academy of Sciences, USA* 112: 6110–6115.

Bansal M, Morley RJ, Nagaraju SK, Dutta S, Mishra AK, Selveraj J, Kumar S, Niyolia D, Harish SM, Abdelrahim OB *et al*. 2022. Southeast Asian Dipterocarp origin and diversification driven by Africa-India floristic interchange. *Science* 375: 455–460.

Barroetaveña C, Salomón MES, Bassani V. 2019. Rescuing the ectomycorrhizal biodiversity associated with South American Nothofagaceae forest, from the 19th century naturalists up to molecular biogeography. *Forestry: An International Journal of Forest Research* 92: 500–511.

Bazzicalupo AL, Buyck B, Saar I, Vauras J, Carmean D, Berbee ML. 2017. Troubles with mycorrhizal mushroom identification where morphological differentiation lags behind barcode sequence divergence. *Taxon* 66: 791–810.

Beaulieu J, O'Meara B, Oliver J, Boyko J. 2021. *CORHMM: hidden Markov models of character evolution*. R package v.2.7. [WWW document] URL https://cran.r-project.org/web/packages/corHMM/ [accessed 10 February 2022].

Bengtsson-Palme J, Ryberg M, Hartmann M, Branco S, Wang Z, Godhe A, De Wit P, Sánchez-García M, Ebersberger I, de Sousa F *et al*. 2013. Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data. *Methods in Ecology and Evolution* 4: 914–919.

Bruns TD, Szaro TM, Gardes M, Cullings KW, Pan JJ, Taylor DL, Horton TR, Kretzer A, Garbelotto M, Li Y. 1998. A sequence database for the identification of ectomycorrhizal basidiomycetes by phylogenetic analysis. *Molecular Ecology* 7: 257–272.

Buyck B. 1990. New taxa of tropical Russulae: *Pseudoepitheliosinae* subsect. nov. *Mycotaxon* 39: 317–327.

Buyck B, Hofstetter V, Eberhardt U, Verbeken A, Kauff F. 2008. Walking the thin line between *Russula* and *Lactarius*: the dilemma of *Russula* subsect. *Ochricompactae*. *Fungal Diversity* 28: 15–40.

Buyck B, Ovrebo CL. 2002. New and interesting *Russula* species from Panamá. *Mycologia* 94: 888–901.

Buyck B, Thoen D, Watling R. 1996. Ectomycorrhizal fungi of the Guinea–Congo Region. *Proceedings of the Royal Society of Edinburgh Section B: Biological Sciences* 104: 313–333.

Buyck B, Wang X-H, Adamčíková K, Caboň M, Jančovičová S, Hofstetter V, Adamčík S. 2020. One step closer to unravelling the origin of *Russula*: subgenus *Glutinosae* subg. nov. *Mycosphere* 11: 285–304.

Buyck B, Zoller S, Hofstetter V. 2018. Walking the thin line... ten years later: the dilemma of above- versus below-ground features to support phylogenies in the Russulaceae (Basidiomycota). *Fungal Diversity* 89: 267–292.

Caiafa MV, Jusino MA, Wilkie AC, Díaz IA, Sieving KE, Smith ME. 2021. Discovering the role of Patagonian birds in the dispersal of truffles and other mycorrhizal fungi. *Current Biology* 31: 5558–5570.e3.
Carriconde F, Gardes M, Bellanger J-M, Letellier K, Gigante S, Gourmelon V, Ibanez T, McCoy S, Goxe J, Read *J* et al. 2019. Host effects in high ectomycorrhizal diversity tropical rainforests on ultramafic soils in New Caledonia. *Fungal Ecology* 39: 201–212.

Chazot N, Condamine FL, Dudas G, Peña K, Kodandaramaiah U, Matos-Maraví P, Aduse-Poku K, Elias M, Warren AD, Lohman DJ et al. 2021. Conserved ancestral tropical niche but different continental histories explain the latitudinal diversity gradient in brush-footed butterflies. *Nature Communications* 12: 5717.

Cheype J-L, Campo E. 2012. *Russula rubropunctatissima* Cheype & E. Campo – une nouvelle russule découverte en Guyane Française. *Bulletin de la Société Mycologique Française* 128: 127–135.

Cody S, Richardson JE, Rull V, Ellis C, Pennington RT. 2010. The Great American biotic interchange revisited. *Ecography* 33: 326–332.

Cook LG, Crisp MD. 2005. Not so ancient: the extant crown group of *Nothofagus* represents a post-Gondwanan radiation. *Proceedings of the Royal Society B: Biological Sciences* 272: 2535–2544.

Corrales A, Henkel TW, Smith ME. 2018. Ectomycorrhizal associations in the tropics - biogeography, diversity patterns and ecosystem roles. *New Phytologist* 220: 1076-1091.

Corrales A, Mangan S.A, Turner BL, Dalling JW. 2016. An ectomycorrhizal nitrogen economy facilitates monodominance in a neotropical forest. *Ecology Letters* 19: 383–392.

Corrales A, Ovrebo CL. 2021. Fungi of the Fortuna Forest Reserve: taxonomy and ecology with emphasis on ectomycorrhizal communities. In: Dalling J, Turner B, eds. *Smithsonian contributions to botany. Fortuna Forest Reserve, Panama: interacting effects of climate and soils on the biota of a wet premontane tropical forest*, 137–153. Washington, DC, USA: Smithsonian Institution.

Crous PW, Wingfield MJ, Burgess TI, Carnegie AJ, Hardy GESJ, Smith D, Summerell BA, Cano-Lira JF, Guarro J, Houbraken J *et al*. 2017. Fungal Planet description sheets: 625–715. *Persoonia – Molecular Phylogeny and Evolution of Fungi* 39: 270–467.

De Crop E, Nuytinck J, Van de Putte K, Wísitrassameewong K, Hackel J, Stubbe D, Hyde KD, Roy M, Halling RE, Moreau P-A *et al*. 2017. A multi-gene phylogeny of *Lactifluus* (Basidiomycota, Russulales) translated into a new infrageneric classification of the genus. *Persoonia* 38: 58–80.

Dearnaley JDW. 2007. Further advances in orchid mycorrhizal research. *Mycorrhiza* 17: 475–486.

Delgat L, Courteussie R, De Crop E, Hampe F, Hofmann TA, Manz C, Piepenbring M, Roy M, Verbeken A. 2020. *Lactifluus* (Russulaceae) diversity in Central America and the Caribbean: melting pot between realms. *Persoonia* 44: 278–300.

Dentinger BTM, Ammirati JF, Both EE, Desjardin DE, Halling RE, Henkel TW, Moreau P-A, Nagasawa E, Soytong K, Taylor AF *et al*. 2010. Molecular phylogenetics of porcini mushrooms (*Boletus* section *Boletus*). *Molecular Phylogenetics and Evolution* 57: 1276–1292.

Dinerstein E, Olson D, Joshi A, Vynne C, Burgess ND, Wikramanayake E, Hahn N, Palminteri S, Hedao P, Noss *R* et al. 2017. An ecoregion-based approach to protecting half the terrestrial realm. *BioScience* 67: 534–545.

Duque Barbosa JA, Delgat L, Galvão Elias S, Verbeken A, Neves MA, de Carvalho A. 2020. A new section, *Lactifluus* section *Neotropicus* (Russulaceae), and two new *Lactifluus* species from the Atlantic Forest, Brazil. *Systematics and Biodiversity* 18: 347–361.

Gardes M, Bruns TD. 1993. ITS primers with enhanced specificity for basidiomycetes – application to the identification of mycorrhizae and rusts. *Molecular Ecology* 2: 113–118.

Geml J, Pastor N, Fernandez L, Pacheco S, Semenova TA, Becerra AG, Wicaksono CY, Nouhra ER. 2014. Large-scale fungal diversity assessment in the Andean Yungas forests reveals strong community turnover among forest types along an altitudinal gradient. *Molecular Ecology* 23: 2452–2472.

Golan JJ, Pringle A. 2017. Long-distance dispersal of fungi. In: *The fungal kingdom*. Hoboken, NJ, USA: John Wiley & Sons, 309–333.

Goldberg EE, Lancaster LT, Ree RH. 2011. Phylogenetic inference of reciprocal effects between geographic range evolution and diversification. *Systematic Biology* 60: 451–465.

Gomes VHF, Vieira ICG, Salomão RP, ter Steege H. 2019. Amazonian tree species threatened by deforestation and climate change. *Nature Climate Change* 9: 547–553.

Hall JS, Harris DJ, Saltonstall K, Medjibe VP, Ashton MS, Turner BL. 2020. Resource acquisition strategies facilitate *Gilbertiodendron dewevrei* monodominance in African lowland forests. *Journal of Ecology* 108: 433–448.

Halling RE, Mueller GM. 2005. *Common mushrooms of the Talamanca Mountains, Costa Rica*. Bronx, NY, USA: New York Botanical Garden Press.

Han LH, Feng B, Wu G, Halling RE, Buyck B, Yorou NS, Ebika STN, Yang ZL. 2018. African origin and global distribution patterns: evidence inferred from phylogenetic and biogeographical analyses of ectomycorrhizal fungal genus *Strobilomyces*. *Journal of Biogeography* 45: 201–212.

Harmon LJ, Weir JT, Brock CD, Glor RE, Challenger W. 2008. GEIGER: investigating evolutionary radiations. *Bioinformatics* 24: 129–131.

Harrower E, Bougher NL, Henkel TW, Horak E, Matheny PB. 2015. Long-distance dispersal and speciation of Australasian and American species of *Cortinarius* sect. *Cortinarius*. *Mycologia* 107: 697–709.

He M-Q, Zhao R-L, Hyde KD, Begerow D, Kemler M, Yurkov A, McKenzie EHC, Raspé O, Kakishima M, Sánchez-Ramírez S *et al*. 2019. Notes, outline and divergence times of Basidiomycota. *Fungal Diversity* 99: 105–367.

Henkel TW. 2003. Monodominance in the ectomycorrhizal *Dicymbe corymbosa* (Caesalpiniaceae) from Guyana. *Journal of Tropical Ecology* 19: 417–437.

Henkel TW, Aime MC, Chin MML, Miller SL, Vilgalys R, Smith ME. 2012. Ectomycorrhizal fungal sporocarp diversity and discovery of new taxa in *Dicymbe* monodominant forests of the Guiana Shield. *Biodiversity and Conservation* 21: 2195–2220.

Henkel TW, Aime MC, Miller SL. 2000. Systematics of pleurotoid Russulaceae from Guyana and Japan, with notes on their ectomycorrhizal status. *Mycologia* 92: 1119–1132.

Henkel TW, Mayor JR. 2019. Implications of a long-term mast seeding cycle for climatic entrainment, seedling establishment and persistent monodominance in a Neotropical, ectomycorrhizal canopy tree. *Ecological Research* 34: 472–484.

Hoorn C, Wesselingh FP, ter Steege H, Bermudez MA, Mora A, Sevink J, Sanmartín I, Sanchez-Meseguer A, Anderson CL, Figueiredo JP *et al*. 2010. Amazonia through time: Andean uplift, climate change, landscape evolution, and biodiversity. *Science* 330: 927–931.

Horton TR, Swaney DP, Galante TE. 2013. Dispersal of ectomycorrhizal basidiospores: the long and short of it. *Mycologia* 105: 1623–1626.

Hughes CE, Pennington RT, Antonelli A. 2013. Neotropical plant evolution: assembling the big picture. *Botanical Journal of the Linnean Society* 171: 1–18.

Jaramillo C, Rueda MJ, Mora G. 2006. Cenozoic plant diversity in the Neotropics. *Science* 311: 1893–1896.

Katoh K, Standley DM. 2013. MAFFT multiple sequence alignment software v.7: improvements in performance and usability. *Molecular Biology and Evolution* 30: 772–780.

Kennedy PG, Garibay-Orijel R, Higgins LM, Angeles-Arguiz R. 2011. Ectomycorrhizal fungi in Mexican *Alnus* forests support the host co-migration hypothesis and continental-scale patterns in phylogeography. *Mycorrhiza* 21: 559–568.

Kennedy PG, Matheny PB, Ryberg KM, Henkel TW, Uehling JK, Smith ME. 2012. Scaling up: examining the macroecology of ectomycorrhizal fungi. *Molecular Ecology* 21: 4151–4154.

Köljalg U, Nilsson RH, Abarenkov K, Tedersoo L, Taylor AFS, Bahram M, Bates ST, Bruns TD, Bengtsson-Palme J, Callaghan TM *et al*. 2013. Towards a unified paradigm for sequence-based identification of fungi. *Molecular Ecology* 22: 5271–5277.

Kropp BR, Albee-Scott S. 2010. *Inocybe tauensis*, a new species from the Samoan Archipelago with biogeographic evidence for a Paleotropical origin. *Fungal Biology* 114: 790–796.

van de Lagemaat SHA, Swart MLA, Vaes B, Kosters ME, Boschman LM, Burton-Johnson A, Bijl PK, Spakman W, van Hinsbergen DJJ. 2021. Subduction initiation in the Scotia Sea region and opening of the Drake Passage: when and why? *Earth-Science Reviews* 215: 103551.

Leavitt SD, Esslinger TL, Lumbsch HT. 2012. Neogene-dominated diversification in neotropical montane lichens: dating divergence events in the lichen-forming fungal genus *Oropogon* (Parmeliaceae). *American Journal of Botany* 99: 1764–1777.
Lemoine F, Entfellner J-BD, Wilkinson E, Correia D, Felipe MD, Oliveira T, Gascuel O. 2018. Renewing Felsenstein's phylogenetic bootstrap in the era of big data. *Nature* 556: 452–456.

Lemon J. 2006. *PLOTRIX*: a package in the red light district of R. *R News* 6(4): 8–12.
van der Linde S, Suz LM, Orme CDL, Cox F, Andreae H, Asi E, Atkinson B, Benham S, Carroll C, Cools N *et al*. 2018. Environment and host as large-scale controls of ectomycorrhizal fungi. *Nature* 558: 243–248.

Liu YJ, Whelen S, Hall BD. 1999. Phylogenetic relationships among ascomycetes: evidence from an RNA polymerase II subunit. *Molecular Biology and Evolution* 16: 1799–1808.

Looney B, Miyauchi S, Morin E, Drula E, Courty PE, Kohler A, Kuo A, LaButti K, Pangilinan J, Lipzen A *et al*. 2022. Evolutionary transition to the ectomycorrhizal habit in the genomes of a hyper-diverse lineage of mushroom-forming fungi. *New Phytologist* 233: 2294–2309.

Looney BP, Meidl P, Piatek MJ, Miettinen O, Martin FM, Matheny PB, Labbé JL. 2018. Russulaceae: a new genomic dataset to study ecosystem function and evolutionary diversification of ectomycorrhizal fungi with their tree associates. *New Phytologist* 218: 54–65.

Looney BP, Ryberg M, Hampe F, Sánchez-García M, Matheny PB. 2016. Into and out of the tropics: global diversification patterns in a hyperdiverse clade of ectomycorrhizal fungi. *Molecular Ecology* 25: 630–647.

Löwenberg-Neto P. 2014. Neotropical region: a shapefile of Morrone's (2014) biogeographical regionalisation. *Zootaxa* 3802: 300.

Löwenberg-Neto P. 2015. Andean region: a shapefile of Morrone's (2015) biogeographical regionalisation. *Zootaxa* 3985: 600.

Manz C, Adamčík S, Looney BP, Corrales A, Ovrebo C, Adamčíková K, Hofmann TA, Hampe F, Piepenbring M. 2021. Four new species of *Russula* subsection *Roseinae* from tropical montane forests in western Panama. *PLoS ONE* 16: e0257616.

Matheny PB, Aime MC, Bougher NL, Buyck B, Desjardin DE, Horak E, Kropp BR, Lodge DJ, Soytong K, Trappe JM *et al*. 2009. Out of the Palaeotropics? Historical biogeography and diversification of the cosmopolitan ectomycorrhizal mushroom family Inocybaceae. *Journal of Biogeography* 36: 577–592.

McGuire KL. 2007. Common ectomycorrhizal networks may maintain monodominance in a tropical rainforest. *Ecology* 88: 567–574.

Miller SL, Aime MC, Henkel TW. 2002. Russulaceae of the Pakaraima Mountains of Guyana. I. New species of pleurotoid *Lactarius*. *Mycologia* 94: 545–553.

Miller SL, Aime MC, Henkel TW. 2012. Russulaceae of the Pakaraima Mountains of Guyana 2. New species of *Russula* and *Lactifluus*. *Mycotaxon* 121: 233–253.

Montoya L, Bandala VM, Garay E. 2014. Two new species of *Lactarius* associated with *Alnus acuminata* subsp. *arguta* in Mexico. *Mycologia* 106: 949–962.

Montoya L, Bandala VM, Halling R. 2003. *Lactarius furcatus* in Mexico and Costa Rica. *Mycotaxon* 87: 311–316.

Moore BR, Höhna S, May MR, Rannala B, Huelsenbeck JP. 2016. Critically evaluating the theory and performance of Bayesian analysis of macroevolutionary mixtures. *Proceedings of the National Academy of Sciences, USA* 113: 9569–9574.

Morrone JJ. 2014. Biogeographical regionalisation of the Neotropical region. *Zootaxa* 3782: 1–110.

Morrone JJ. 2015. Biogeographical regionalisation of the Andean region. *Zootaxa* 3936: 207–236.

Moyersoen B. 1993. *Ectomicorrizas y micorrizas vesiculo-arbusculares en Caatinga Amazonica*. Caracas, Venezuela: O Huber.

Moyersoen B. 2006. *Pakaraimaea dipterocarpacea* is ectomycorrhizal, indicating an ancient Gondwanaland origin for the ectomycorrhizal habit in Dipterocarpaceae. *New Phytologist* 172: 753–762.

Müller RD, Seton M, Zahirovic S, Williams SE, Matthews KJ, Wright NM, Shephard GE, Maloney KT, Barnett-Moore N, Hosseinpour M *et al*. 2016. Ocean basin evolution and global-scale plate reorganization events since Pangea breakup. *Annual Review of Earth and Planetary Sciences* 44: 107–138.

Nouhra ER, Palfner G, Kuhar F, Pastor N, Smith ME. 2019. Ectomycorrhizal fungi in South America: their diversity in past, present and future research. In: Pagano MC, Lugo MA, eds. *Fungal biology. Mycorrhizal fungi in South America*. Cham, Switzerland: Springer International, 73–95.

O'Dea A, Lessios HA, Coates AG, Eytan RI, Restrepo-Moreno SA, Cione AL, Collins LS, de Queiroz A, Farris DW, Norris RD *et al*. 2016. Formation of the Isthmus of Panama. *Science Advances* 2: e1600883.

Palma-Silva C, Turchetto-Zolet AC, Fay MF, Vasconcelos T. 2022. Drivers of exceptional Neotropical biodiversity: an updated view. *Botanical Journal of the Linnean Society* 199: 1–7.

Paradis E, Schliep K. 2019. *APE* 5.0: an environment for modern phylogenetics and evolutionary analyses in R. *Bioinformatics* 35: 526–528.

Peay KG, Kennedy PG, Talbot JM. 2016. Dimensions of biodiversity in the Earth mycobiome. *Nature Reviews Microbiology* 14: 434–447.

Pebesma E. 2018. Simple features for R: standardized support for spatial vector data. *The R Journal* 10: 439–446.

Pennington RT, Dick CW. 2004. The role of immigrants in the assembly of the South American rainforest tree flora. *Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences* 359: 1611–1622.

Pérez-Escobar OA, Zizka A, Bermúdez MA, Meseguer AS, Condamine FL, Hoorn C, Hooghiemstra H, Pu Y, Bogarín D, Boschman LM *et al*. 2022. The Andes through time: evolution and distribution of Andean floras. *Trends in Plant Science* 27: 364–378.

Peterson KR, Pfister DH, Bell CD. 2010. Cophylogeny and biography of the fungal parasite *Cyttaria* and its host *Nothofagus*, southern beech. *Mycologia* 102: 1417–1425.

Pirozynski KA. 1983. Pacific mycogeography: an appraisal. *Australian Journal of Botany Supplementary Series* 13: 137–160.

Plummer M, Best N, Cowles K, Vines K. 2006. CODA: convergence diagnosis and output analysis for MCMC. *R News* 6: 7–11.

Poole I, Cantrill DJ. 2006. Cretaceous and Cenozoic vegetation of Antarctica integrating the fossil wood record. *Geological Society, London, Special Publications* 258: 63–81.

Price MN, Dehal PS, Arkin AP. 2010. FASTTREE 2 – approximately maximum-likelihood trees for large alignments. *PLoS ONE* 5: e9490.

Rabosky DL. 2014. Automatic detection of key innovations, rate shifts, and diversity-dependence on phylogenetic trees. *PLoS ONE* 9: e89543.

Rabosky DL, Mitchell JS, Chang J. 2017. Is BAMM flawed? Theoretical and practical concerns in the analysis of multi-rate diversification models. *Systematic Biology* 66: 477–498.

Ree RH, Moore BR, Webb CO, Donoghue MJ. 2005. A likelihood framework for inferring the evolution of geographic range on phylogenetic trees. *Evolution* 59: 2299–2311.

Ree RH, Sanmartín I. 2018. Conceptual and statistical problems with the DEC+J model of founder-event speciation and its comparison with DEC via model selection. *Journal of Biogeography* 45: 741–749.

Renner S. 2004. Plant dispersal across the tropical Atlantic by wind and sea currents. *International Journal of Plant Sciences* 165: S23–S33.

Revell LJ. 2011. *PHYTOOLS*: an R package for phylogenetic comparative biology (and other things). *Methods in Ecology and Evolution* 3: 217–223.

Rognes T, Flouri T, Nichols B, Quince C, Mahé F. 2016. VSEARCH: a versatile open source tool for metagenomics. *PeerJ* 4: e2584.

Roy M, Schimann H, Braga-Neto R, Silva RAED, Duque J, Frame D, Wartchow F, Neves MA. 2016. Diversity and distribution of ectomycorrhizal fungi from Amazonian lowland white-sand forests in Brazil and French Guiana. *Biotropica* 48: 90–100.

Ryberg M, Matheny PB. 2012. Asynchronous origins of ectomycorrhizal clades of Agaricales. *Proceedings of the Royal Society B: Biological Sciences* 279: 2003–2011.

Sà MCA, Baseia IG, Wartchow F. 2013. *Lactifluus dunensis*, a new species from Rio Grande do Norte, Brazil. *Mycosphere* 4: 261–265.

Sà MCA, Delgat L, Verbeken A, Sulzbacher MA, Baseia IG, Wartchow F. 2019. A new species of *Lactifluus* (Russulales, Agaricomycetes) from the Brazilian caatinga semiarid region. *New Zealand Journal of Botany* 57: 169–178.

Sà MCA, Wartchow F. 2013. *Lactifluus aurantiorugosus* (Russulaceae), a new species from Southern Brazil. *Darwiniana, Nueva Serie* 1: 54–60.

Sà MCA, Wartchow F. 2016. *Russula omnileuca*, a new species from Pernambuco, Brazil. *Sydowia* 68: 63–68.

Sánchez-García M, Ryberg M, Khan FK, Varga T, Nagy LG, Hibbett DS. 2020. Fruiting body form, not nutritional mode, is the major driver of diversification
in mushroom-forming fungi. *Proceedings of the National Academy of Sciences, USA* 117: 32528-32534.

Sánchez-Ramírez S, Tulloss RE, Amalfi M, Moncalvo J-M. 2014. Palaeotropical origins, boreotropical distribution and increased rates of diversification in a clade of edible ectomycorrhizal mushrooms (*Amanita* section *Caesareae*). *Journal of Biogeography* 42: 351–363.

Séne S, Selosse M-A, Forget M, Lambourdière J, Cissé K, Diédhiou AG, Rivera-Ocasio E, Kodja H, Kameyama N, Nara K et al. 2018. A pantropically introduced tree is followed by specific ectomycorrhizal symbionts due to pseudo-vertical transmission. *The ISME Journal* 12: 1806–1816.

Silva-Filho AGS, Sá MCA, Komura DL, Moncalvo J-M, Margaritescu S, Roy M, Wartchow F. 2020. Two novel species of *Lactifluus* subg. *Pseudogymnocarpi* (Russulaceae) from Brazil. *Phytotaxa* 436: 222–236.

Singer R. 1953. Four years of mycological work in southern South America. *Mycologia* 45: 865-891.

Singer R, Aguiar IA. 1986. Litter decomposing and ectomycorrhizal Basidiomycetes in an igapó forest. *Plant Systematics and Evolution* 153: 107–117.

Singer R, Araujo I, Ivory M. 1983. The ectotrophically mycorrhizal fungi of the neotropical lowlands, especially Central Amazonia (Litter decomposition and ectomycorrhiza in Amazonian forests 2.). *Beihefie zur Nova Hedwigia* 77: 1–352.

Singer R, Araujo IJS. 1979. Litter decomposition and Ectomycorrhiza in Amazonian forests. 1. A comparison of litter decomposing and ectomycorrhizal Basidiomycetes in latosol-terra-firme rain forest and white podzol campinarana. *Acta Amazonica* 9: 25-42.

Smith ME, Henkel TW, Catherine Aime M, Fremier AK, Vilgalys R. 2011. Ectomycorrhizal fungal diversity and community structure on three co-occurring leguminous canopy tree species in a Neotropical rainforest. *New Phytologist* 192: 699-712.

Smith ME, Henkel TW, Uehling JK, Fremier AK, Clarke HD, Vilgalys R. 2013. The ectomycorrhizal fungal community in a neotropical forest dominated by the endemic dipterocarp *Pakaraimaea dipterocarpacea*. *PLoS ONE* 8: e55160.

Smith SA, O'Meara BC. 2012. TREEPL: divergence time estimation using penalized likelihood for large phylogenies. *Bioinformatics* 28: 2689-2690.

Smith SE, Read DJ. 2010. *Mycorrhizal symbiosis*. New York, NY, USA: Academic Press.

Soudzilovskaia NA, van Bodegom PM, Terrer C, van't Zelfde M, McCallum I, Luke McCormack M, Fisher JB, Brundrett MC, de Sá NC, Tedersoo L. 2019. Global mycorrhizal plant distribution linked to terrestrial carbon stocks. *Nature Communications* 10: 5077.

Stamatakis A. 2014. RAXML v.8: a tool for phylogenetic analysis and post-analysis of large phylogenies. *Bioinformatics* 30: 1312–1313.

Steidinger BS, Crowther TW, Liang J, Nuland MEV, Werner GDA, Reich PB, Nabuurs GJ, de Miguel S, Zhou M, Picard N et al. 2019. Climatic controls of decomposition drive the global biogeography of forest-tree symbioses. *Nature* 569: 404–408.

Tedersoo L. 2017. Global biogeography and invasions of ectomycorrhizal plants: past, present and future. In: Tedersoo L, ed. *Ecological studies. Biogeography of mycorrhizal symbiosis*. Cham, Switzerland: Springer International, 469–531.

Tedersoo L, Bahram M, Pölme S, Köljalg U, Yorou NS, Wijesundera R, Ruiz LV, Vasco-Palacios AM, Thu PQ, Suija A et al. 2014a. Global diversity and geography of soil fungi. *Science* 346: 1256688.

Tedersoo L, Bahram M, Ryberg M, Otsing E, Köljalg U, Abarenkov K. 2014b. Global biogeography of the ectomycorrhizal/sebacina lineage (Fungi, Sebacinales) as revealed from comparative phylogenetic analyses. *Molecular Ecology* 23: 4168–4183.

Tedersoo L, Bahram M, Zobel M. 2020. How mycorrhizal associations drive plant population and community biology. *Science* 367: eaba1223.

Tedersoo L, Brundrett MC. 2017. Evolution of ectomycorrhizal symbiosis in plants. In: Tedersoo L, ed. *Ecological studies. Biogeography of mycorrhizal symbiosis*. Cham, Switzerland: Springer International, 407–467.

Tedersoo L, May TW, Smith ME. 2010a. Ectomycorrhizal lifestyle in fungi: global diversity, distribution, and evolution of phylogenetic lineages. *Mycorrhiza* 20: 217–263.

Tedersoo L, Nara K. 2010. General latitudinal gradient of biodiversity is reversed in ectomycorrhizal fungi. *New Phytologist* 185: 351–354.

Tedersoo L, Sadam A, Zambrano M, Valencia R, Bahram M. 2010b. Low diversity and high host preference of ectomycorrhizal fungi in Western Amazonia, a neotropical biodiversity hotspot. *The ISME Journal* 4: 465–471.

Tennekes M. 2020. *TMAPTOOLS: thematic map tools*. R package v.3.0. [WWW document] URL https://cran.r-project.org/web/packages/tmaptools/index.html [accessed 3 July 2020].

Trierveiler-Pereira L, Smith ME, Trappe JM, Nouhra E. 2014. Sequestrate fungi from Patagonian *Nothofagus* forests: *Cystangium* (Russulaceae, Basidiomycota). *Mycologia* 107: 13–302.

Varga T, Krizsán K, Földi C, Dima B, Sánchez-García M, Sánchez-Ramírez S, Szöllősi GJ, Szarkándi JG, Papp V, Albert L et al. 2019. Megaphylogeny resolves global patterns of mushroom evolution. *Nature Ecology & Evolution* 3: 668.

Vasconcelos T, O'Meara BC, Beaulieu JM. 2022. Retiring “cradles” and “museums” of biodiversity. *The American Naturalist* 199: 194–205.

Vasco-Palacios AM, Hernandez J, Peñuela-Mora MC, Franco-Molano AE, Boekhout T. 2018. Ectomycorrhizal fungi diversity in a white sand forest in western Amazonia. *Fungal Ecology* 31: 9–18.

Vera M, Adamčík S, Adamčíková K, Hampe F, Caboň M, Manz C, Ovrebo C, Piepenbring M, Corrales A. 2021. Morphological and genetic diversification of *Russula floriformis*, sp. nov., along the Isthmus of Panama. *Mycologia* 113: 807–827.

Verbeken A, Stubbe D, van de Putte K, Eberhardt U, Nuytinck J. 2014. Tales of the unexpected: angiocarpous representatives of the Russulaceae in tropical South East Asia. *Persoonia* 32: 13–24.

Vilgalys R, Hester M. 1990. Rapid genetic identification and mapping of enzymatically amplified ribosomal DNA from several *Cryptococcus* species. *Journal of Bacteriology* 172: 4238–4246.

Wang X-H, Halling RE, Hofstetter V, Lebel T, Buyck B. 2018. Phylogeny, biogeography and taxonomic re-assessment of *Multifurca* (Russulaceae, Russulales) using three-locus data. *PLoS ONE* 13: e0205840.

Wartchow F, Bezerra JL, Cavalcanti MAQ. 2013. *Lactifluus batistae* (Russulaceae), a new species from Bahia, Brazil. *Agrotrópica* 25: 103–108.

Wartchow F, Cavalcanti MAQ. 2010. *Lactarius rupestris*—a new species from the Brazilian semi-arid region. *Mycotaxon* 112: 55–63.

White TJ, Bruns TD, Lee SB, Taylor JW. 1990. Analysis of phylogenetic relationships by amplification and direct sequencing of ribosomal RNA genes. In: Innis MA, Gelfand DH, Sninsky JN, White TJ, eds. *PCR protocols: a guide to methods and applications*. London, UK: Academic Press, 315–322.

Wicaksono CY, Aguirre-Guiterrez J, Nouhra E, Pastor N, Raes N, Pacheco S, Geml J. 2017. Contracting montane cloud forests: a case study of the Andean alder (*Alnus acuminata*) and associated fungi in the Yungas. *Biotropica* 49: 141–152.

Wilson AW, Binder M, Hibbett DS. 2012. Diversity and evolution of ectomycorrhizal host associations in the Sclerodermatineae (Boletales, Basidiomycota). *New Phytologist* 194: 1079–1095.

Witurssameewong K, Looney BP, Le HT, De Crop E, Das K, Van de Putte K, Eberhardt U, Jiayu G, Stubbe D, Hyde KD et al. 2016. *Lactarius* subgenus *Russularia* (Basidiomycota, Russulales): novel Asian species, worldwide phylogeny and evolutionary relationships. *Fungal Biology* 120: 1554–1581.

Wolfe JA. 1975. Some aspects of plant geography of the northern hemisphere during the late Cretaceous and Tertiary. *Annals of the Missouri Botanical Garden* 62: 264–279.

Won H, Renner SS. 2006. Dating dispersal and radiation in the gymnosperm *Gnetum* (Gnetales)—clock calibration when outgroup relationships are uncertain. *Systematic Biology* 55: 610–622.

Zachos J, Pagani M, Sloan L, Thomas E, Billups K. 2001. Trends, rhythms, and aberrations in global climate 65 Ma to present. *Science* 292: 686–693.
Zhang Q, Ree RH, Salamin N, Xing Y, Silvestro D. 2022. Fossil-informed models reveal a boreotropical origin and divergent evolutionary trajectories in the walnut family (Juglandaceae). *Systematic Biology* 71: 242–258.

## Supporting Information

Additional Supporting Information may be found online in the Supporting Information section at the end of the article.

**Fig. S1** Russulaceae backbone phylogeny.

**Fig. S2** Russulaceae backbone phylogeny, time calibrated.

**Fig. S3** Detailed Russulaceae supertree.

Please note: Wiley Blackwell are not responsible for the content or functionality of any Supporting Information supplied by the authors. Any queries (other than missing material) should be directed to the *New Phytologist* Central Office.