Dissecting the difference in tree species richness between
Africa and South America
Pedro Luiz Silva de Miranda
, Kyle G. Dexter
, Michael D. Swaine
, Ary Teixeira de Oliveira-Filho
, Olivier J. Hardy
, and Adeline Fayolle
Edited by Douglas Schemske, Michigan State University, East Lansing, MI; received July 4, 2021; accepted February 17, 2022
Differences in species diversity over continental scales represent imprints of evolution-
ary, ecological, and biogeographic events. Here, we investigate whether the higher tree
species richness in South America relative to Africa is due to higher richness in certain
taxonomic clades, irrespective of vegetation type, or instead due to higher richness in
speciﬁc biomes across all taxonomic clades. We used tree species inventory data to
address this topic and began by clustering inventories from each continent based on
species composition to derive comparable vegetation units. We found that moist forests
in South America hold approximately four times more tree species than do moist forests
in Africa, supporting previous studies. We also show that dry vegetation types in South
America, such as tropical dry forests and savannas, hold twice as many tree species as do
those in Africa, even though they cover a much larger area in Africa, at present and over
geological time. Overall, we show that the marked species richness difference between
South America and Africa is due primarily to a key group of families in the South
American Amazon and Atlantic moist forests, which while present and speciose in
Africa, are markedly less diverse there. Moreover, we demonstrate that both South
American and African tree ﬂoras are organized similarly and that speciose families on
one continent are likely speciose on the other. Future phylogenetic and functional trait
work focusing on these key families should provide further insight into the processes
leading to South America’s exceptional plant species diversity.
taxonomic diversity jtropical trees jtropical moist forest jtropical dry forest jsavanna
Plant diversity is not evenly distributed across the biosphere—the tropics are more spe-
cies rich than other regions, and moist tropical forests have more plant species than the
dry tropics (1, 2). Historically, the distribution of biodiversity has been investigated
from a broadscale historical perspective (pattern description over large geographic
scales) or from a local ecological perspective (hypothesis testing at community scales)
(3), both leading to key ﬁndings. Among the numerous hypotheses that have been pro-
posed, high plant species richness in tropical moist regions has been associated with
high water availability and reduced climatic seasonality (4, 5), while the decrease in
plant species richness toward the poles has been linked (among several other factors) to
current plant clades having a tropical origin and lacking the adaptations required to
inhabit temperate or boreal zones (6–8). From a different perspective, according to the
species-area relationship (9), species richness and area are positively correlated (an
increase in area will likely lead to an increase in richness), an effect which is modulated
by how environmentally stable an area has been over geological time (10). Importantly,
in the tropics, this effect may be partly enhanced by higher speciation and/or lower
extinction rates [(11) and references therein]. Moreover, it has been hypothesized that
favorable environmental conditions may enhance biotic interactions, which in turn
favor higher diversiﬁcation rates (12, 13). Though differences in plant richness between
temperate and tropical zones are well understood, differences in plant species richness
among tropical regions remain largely unexplored [though see (4, 14–17)]. Tropical
Africa’s depauperate forest tree ﬂora, in comparison to tropical South America and
Southeast Asia—the odd-man-out pattern—has been investigated relatively rarely
despite awareness of the pattern since at least 1973 (18, 19).
Among regions, differences in timing of the origin and diversiﬁcation of lineages,
along with differences in dispersal and extinction, may lead to substantial discrepancies
in species richness known as diversity anomalies (6). These anomalies are imprints of
past evolutionary and ecological events and are, therefore, key evidence to unravel how
communities were assembled over time. By comparing regional ﬂoras, Richards (18)
ﬁrst showed that African tropical moist forests held fewer species than similar forests
elsewhere and suggested that its depauperate ﬂora is linked to harsher past and present-
day climatic conditions, as well as to differences in human occupation. Latin America
as a whole has 3.8 times as many plant species as tropical Africa (20), and much of this
Our full-scale comparison of Africa
and South America’slowland
tropical tree ﬂoras shows that
both Africa and South America’s
moist and dry tree ﬂoras are
organized similarly: plant families
that are rich in tree species on one
continent are also rich in tree
species on the other continent,
and these patterns hold across
moist and dry environments.
Moreover, we conﬁrm that there
is an important difference in tree
species richness between the two
continents, which is linked to a
few families that are exceptionally
diverse in South American moist
forests, although dry formations
also contribute to this difference.
Plant families only present on one
of the two continents do not
contribute substantially to
differences in tree species
Gembloux Agro-Bio Tech, University
of Liege, 5030 Gembloux, Belgium;
GeoSciences, University of Edinburgh, Edinburgh EH8
9YL, United Kingdom;
Institute of Biological and
Environmental Sciences, University of Aberdeen,
Aberdeen AB24 3FX, United Kingdom;
anica, Universidade Federal de Minas Gerais, Belo
Horizonte, 31270-901, Brazil; and
and Ecology, Facult
e des Sciences, Universit
e Libre de
Bruxelles, 1050 Brussels, Belgium
Author contributions: P.L.S.d.M. and A.F. designed
research; P.L.S.d.M. led research; P.L.S.d.M., K.G.D.,
and A.F. performed research; M.D.S., A.T.d.O.-F., and
A.F. contributed data; P.L.S.d.M., K.G.D., and A.F.
analyzed data; and P.L.S.d.M., K.G.D., M.D.S., A.T.d.O.-
F., O.J.H., and A.F. wrote the paper.
The authors declare no competing interest.
This article is a PNAS Direct Submission.
Copyright © 2022 the Author(s). Published by PNAS.
This open access article is distributed under Creative
License 4.0 (CC BY-NC-ND).
To whom correspondence may be addressed. Email:
This article contains supporting information online at
Published March 29, 2022.
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diversity difference is due to the exceptional diversity of South
America, which is notable for being greater than that of Africa
even though South America is 59% of the size. Further research
has also linked differences in tree species richness at the plot
level (i.e., alpha diversity) between moist forests in Western
and Central Africa and the Amazon to differences in current
climatic and ecological conditions [water availability (4)], turn-
over rates (15), stem density (21), and the presence of elephants
and other megaherbivores in Africa (22). These studies focused
only on moist tropical forests, particularly parts of the Amazon
forest and Western and Central African (Guineo-Congolian)
forests. Drier biomes and vegetation types have been scarcely
considered. This is likely due to lack of comparable assimilated
data from the dry tropics, but sufﬁcient data are now available
[e.g., (23) for Africa and (24) for South America]. Therefore,
the full extent of anomalies in plant species richness between
the two continents, considering all tropical biomes, is ripe for
dissection and explanation [e.g., (20)].
The striking ﬂoristic similarity between Africa and South
America has already been highlighted by Gentry (25) and
recently conﬁrmed using phylogenetic approaches (16, 26). In
most accounts, the high number of shared families and genera
(27) between the two continents is attributed to their common
geological past—Western Gondwana—whose split presumably
led to vicariance-driven divergence events, though this view has
been ﬁrmly contested [e.g., evidence for vicariance is easily dis-
torted or lost by sampling errors (28)]. The rise of angiosperms
roughly coincides with the Western Gondwanan split (start:
∼130 Mya, end: ∼90 Mya), when the Gondwanan ﬂora was
dominated by gymnosperms (e.g., Araucauria and Podocarpus)
and seed ferns (e.g., Komlopteris and Pachypteris) (29). Angio-
sperms only dominated African and South American ﬂoras after
the mass extinction event marking the Cretaceous–Paleogene
(K-Pg) boundary [∼65 Mya (30–32)], when both continents
were already isolated from one another, as well as from other
land masses. The K-Pg boundary extinction event was followed
by an increase in the diversity of plant genera (33, 34) and by
the origin and diversiﬁcation of important pantropical and spe-
ciose plant families [e.g., Fabaceae (35)]. Therefore, the tree
species richness difference between Africa and South America
most likely results from biogeographic events that took place
after the end of the Cretaceous. Consequently, the observed
taxonomic and phylogenetic similarities are as likely or more
likely to be related to (long-distance) dispersal events via vari-
ous routes than to vicariance (18, 36–39).
Observed differences in tree species richness between Africa
and South America have often been attributed to mechanisms
that would impact net diversiﬁcation rates, primarily in moist
tropical forests. In addition to differences in current climate
(4), South American tropical moist forests cover a larger area
and have been subjected to weaker expansion/contraction cycles
than their African counterparts (40). In addition, the Amazon
forest, which potentially harbors ∼16,000 species of trees (41,
42), may also act as a biodiversity pump by being the source of
lineages of plants and animals found in other South American
biomes (43). Much less research attention has been given to
drier biomes, which in Africa cover most of the continent,
extend over large environmental gradients (44), and have done
so over geological time. Furthermore, since the beginning of
the Pliocene, Africa has become increasingly arid due to
changes in ocean currents (34), while in South America, the
Andes limited continental desiccation during glacial periods
(40, 45). Given the larger area occupied by dry biomes in
Africa, we may expect that they are more diverse than the dry
biomes of South America. Therefore, the greater overall tree
species richness of South America in relation to Africa may be
linked entirely to its moist forests, which must also hold sufﬁ-
cient tree species in order to surpass any potential richness dif-
ference in favor of Africa in the dry tropics. Conversely, as
plant clades and families are fundamentally different in their
net diversiﬁcation rates and their biogeographic histories (46,
47), differences in tree species richness between Africa and
South America might be linked simply to plant families that
are entirely (or almost entirely) restricted to South America
[e.g., Malpighiaceae (48), Vochysiaceae (18, 49), and to a lesser
degree Arecaceae (50, 51)]. However, how much individual
families contribute to the overall tree species richness difference
between the two continents remains unknown, especially in
Here, we sought to test whether South America’s high tree
species richness compared to Africa is driven solely by higher
species richness in moist forest vegetation or whether there are
meaningful differences in species richness between the two con-
tinents’dry formations as well. We compare ﬂoristic proﬁles,
the distribution of species richness per family, for Africa and
South America as the means to understand how their tree ﬂoras
are taxonomically organized. We hypothesize that differences in
tree species richness between the two continents are mainly
linked to their moist forests, though dry formations may mean-
ingfully contribute to total tree species counts. Furthermore, we
hypothesize that much of the diversity difference will be due to
the families that are restricted, or nearly so, to South America.
African and South American Vegetation Clusters. We assem-
bled tree species checklists for both Africa and South America
from various sources (see Materials and Methods). In order to
develop standardized units for comparison, we ﬁrst delimited
11 vegetation clusters in Africa and 12 in South America
(Fig. 1 and SI Appendix, Fig. S1) via hierarchical clustering
based on ﬂoristic turnover among tree species inventories (com-
puted for each pair of sites using the Simpson index of beta
diversity). We conducted the clustering analyses for both conti-
nents separately, given that they share few tree species. This
allowed us to achieve equivalent and comparable ﬂoristic clus-
ters via a standardized methodology. Overall, Africa is domi-
nated by drier vegetation clusters (7 out of 11, Fig. 2Aand SI
Appendix, Fig. S2A), whereas moist forest clusters are more
prevalent in South America (7 out of 12, Fig. 2Band SI
Appendix, Fig. S2 Aand C). Comparatively, African clusters are
drier than the ones in South America, with the Sahel being the
driest cluster across the two continents (Fig. 2Cand SI
Appendix, Fig. S2 Band D). South America also holds moist
forests with colder temperature regimes (Amazonian-Andean
foothill forests, Amazonian Guiana shield forests, and subtropi-
cal Atlantic forest; Fig. 2C) that have no analog in the
To compare the climatic space occupied by vegetation clus-
ters in both Africa and South America, we used a principal
component analysis (PCA) on gridded climatic variables for
each of our sites. The ﬁrst axis of the PCA collated
precipitation-related information and explained ∼36% of the
variance in the climatic data (Fig. 2E). The second axis encom-
passed temperature-related information and explained ∼33% of
the variance. By following the mean score of each vegetation
type along the precipitation gradient, we divided the vegetation
clusters into two categories, moist and dry vegetation clusters
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(SI Appendix, Fig. S2 Aand B), which would place the mean
annual precipitation threshold dividing these two categories
between 1,150 mm y
(5% quantile of the moist group) and
1,786 mm y
(95% quantile of the dry group).
African and South American Tree Species Diversity and
Floristic Relatedness. Both continents are strikingly similar in
how their ﬂoras are organized (Table 1, Fig. 3, and SI
Appendix, Fig. S3). If a given family is species rich on one con-
tinent, it will most likely be species rich on the other continent
as well (Fig. 3), a pattern that does not change when focusing
only on moist or dry formations. However, vegetation clusters
within the same continent are more similar among themselves
with regard to tree species richness per genus and family than
they are with clusters present on the opposite continent (SI
Appendix, Fig. S4). Nevertheless, Africa and South America
share a total of 99 tree families in our dataset, while their moist
and dry vegetation clusters share 93 and 81 families, respec-
tively. On average, the families present on both continents
hold around 95% of the total observed tree species richness
(Table 1). Therefore, families found exclusively on one conti-
nent only account for ∼5% of the total tree species richness.
Importantly, ∼50% of the existing tree species richness in the
whole of Africa and South America across both moist and dry
vegetation clusters belongs to a group ranging from seven to
nine families (Fig. 4 and SI Appendix, Tables S1–S3). Fabaceae
is by far the most species rich and ecologically diversiﬁed family
across the two continents, with numerous species in each vege-
tation cluster, moist and dry (Fig. 4 and SI Appendix, Fig. S5).
Apart from a few families, such as Combretaceae, Phyllantha-
ceae, and Sapindaceae being relatively more important in Africa
and Lauraceae, Melastomataceae, and Myrtaceae being more
prevalent in South America, the most speciose families on each
continent are largely the same (SI Appendix,Fig.S5). Importantly,
most of the families shared by the two continents are younger than
the Gondwanan split and the K-Pg boundary extinction event
(crown node age younger than 90 and 65 Mya, respectively, SI
Appendix, Table S7). Only a few families, such as Annonaceae,
Arecaceae, and Lauraceae, are older than the Gondwanan split
(SI Appendix,TableS7). Moreover, tree species richness per family
is not correlated with family age (SI Appendix,Fig.S6).
The difference in tree species richness between the two conti-
nents is substantial (Table 1). While our dataset for Africa
contains 3,048 species distributed across 816 genera and 131
families over 722 sites, the South American dataset holds 8,842
tree species across 1,083 genera and 152 families for the same
number of sites (we subset the larger South American dataset
by using spatially stratiﬁed random sampling to enable a fair
comparison with Africa; see Materials and Methods). Interconti-
nental ranked correlations of tree species richness per family
between the two continents’entire tree ﬂoras and moist and
dry ﬂoras separately yielded correlation coefﬁcients around 0.62
(all highly signiﬁcant, P<0.0001, Fig. 3). However, the moist
and dry ﬂoras of each continent are still more correlated to one
another than they are to their intercontinental counterparts.
African moist and dry vegetation formations at the family level
(93 families in common) are highly correlated in terms of
number of species per family (r
Fig. 3C), and this correlation is even more striking between
South America moist and dry vegetation formations (123 fami-
lies shared, r
=0.92, P<0.0001, Fig. 3D). On both
continents, families present in both moist and dry clusters tend
to be more species rich in moist vegetation than in dry vegeta-
tion. At the genus level, intercontinental comparisons are lim-
ited due to the relatively low number of genera shared between
the two continents (SI Appendix, Fig. S4). Among the shared
genera, Africa and South America’s dry vegetation are more
correlated in species richness (94 shared genera, r
0.43, P<0.0001, SI Appendix, Fig. S4C) than the moist vege-
tation clusters (111 shared genera, r
SI Appendix, Fig. S4B). Once again, moist and dry vegetation
formations of the same continent are more correlated to one
another than to their intercontinental counterparts (SI Appendix,
Fig. S4D, Africa: 358 shared genera, r
0.0001; SI Appendix,Fig.S4E, South America: 664 shared gen-
Fig. 1. Map of Africa and South America indicating the main vegetation clusters present in each continent identiﬁed via a hierarchical clustering analysis
(UPGMA) based on tree species turnover (Simpson beta-diversity index). Each point corresponds to a georeferenced tree species checklist (n=722 per
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Differences in tree species richness between Africa and
South America. Contrary to our expectation that differences in
tree species richness between Africa and South America would
be driven by families restricted or almost restricted to South
America, we found that tree species richness differences are
driven by a few families that are speciose on both continents
but exceptionally more speciose in South America. While other
families have detectable species richness differences (42 families
are signiﬁcantly more species rich in South America than
Africa; only 3 families are signiﬁcantly more species rich in
Africa), relatively few families drive the large difference in over-
all species richness totals (Fig. 4 A–Cand SI Appendix, Tables
S1–S3). The families that are restricted (or nearly so) to South
America account for a small proportion of the total species rich-
ness in South America (5%) and of the diversity difference
(∼0.08%). Null model simulations show that if South America
and Africa had the same taxonomic diversity proﬁles, the much
higher species richness in South America should be linked to
having more families than observed. South America has 11
fewer families than expected given its very high species richness
(P<0.003), indicating that the diversity difference is driven
not by having more families per se (SI Appendix,SI Materials
and Methods) but by having more species in a key group of
families. When considering the observed proportion of overall
tree species richness in South America (SA) relative to Africa
(AF) as the baseline expectation in binomial tests (AF 0.26/SA
0.74), it is possible to see that both Africa and South America
have a similar number of families that are more speciose than
expected (SI Appendix, Table S1, AF 18/SA 19). However, 3 of
the top 5 and 6 of the top 20 most speciose families are signiﬁ-
cantly more speciose in South America, while only 1 of the top
5 and 3 of the top 20 are signiﬁcantly more speciose in Africa.
It is overall less speciose families (with fewer than 100 species
in both continents combined) that tend to be more speciose in
PC1 (36.3%) PC1 (36.3%) WetterDrier
Fig. 2. Climatic space of all clusters identiﬁed in Africa (Aand B, 722 checklists in total) and South America (Cand D, 722 checklists in total) represented by
the ﬁrst two axes of a PCA. (A) Africa, moist clusters; (B) Africa, dry clusters; (C) South America, moist clusters; and (D) South America, dry clusters, generated
via the same PCA, which was then subdivided into four panels as the means to show the four main climatic clusters encountered in Africa and South Amer-
ica. (E) Variable correlation circle generated via the same PCA. Climatic variables included in the PCA are the 19 variables provided by CHELSA plus climatic
water deﬁcit (89). The larger points represent the mean of each group. For vegetation cluster names, see Fig. 1. Climatic variables’names are as follows:
MAT, mean annual temperature; MDR, mean diurnal range; Tiso, isothermality; Tsea, temperature seasonality; Tmwm, maximum temperature of warmest
month; Tmcm, minimum temperature of coldest month; Tar, temperature annual range; Tmweq, mean temperature of wettest quarter; Tmdq, mean tem-
perature of driest quarter; Tmwaq, mean temperature of warmest quarter; Tmcq, mean temperature of coldest quarter; MAP, annual precipitation; Pwm,
precipitation of wettest month; Pdm, precipitation of driest month; Psea, precipitation seasonality; Pweq, precipitation of wettest quarter; Pdq, precipitation
of driest quarter; Pwaq, precipitation of warmest quarter; Pcq, precipitation of coldest quarter; CWD, climatic water deﬁcit. PC, Principal Component.
4of10 https://doi.org/10.1073/pnas.2112336119 pnas.org
Africa relative to a 0.26/0.74 baseline expectation. Interestingly,
the three families that are among the top 20 most speciose fam-
ilies overall and are more speciose in Africa than in South
America, given a baseline 0.26/0.74 expectation, are Fabaceae,
Malvaceae, and Sapindaceae, families that have successfully
radiated in moist and dry environments (52–54).
Our intercontinental comparison among diversity proﬁles of
moist and dry vegetation clusters, along with binomial tests,
shows that the high number of tree species in South America is
mainly due to high richness in moist vegetation clusters
(Amazon forest +moist Atlantic forest clusters, Fig. 4Band SI
Appendix, Table S2). Out of the 93 families shared by the
moist formations of the two continents, 41 hold signiﬁcantly
more species in South America than in Africa, while only
Putranjivaceae holds signiﬁcantly more species in Africa than in
South America (Fig. 4 and SI Appendix, Table S2). When
taking the observed differences in tree species richness between
moist forests on the two continents as the baseline (SI
Appendix, Table S2, AF 0.21/SA 0.79), 19 families hold more
tree species than expected in Africa, while 13 families hold
more tree species than expected in South America. Meanwhile,
concerning the dry vegetation, out of the 81 shared families, 22
hold signiﬁcantly more species in South America than in Africa,
whereas three families present the opposite pattern (Fig. 4C
and SI Appendix, Table S3). When considering the difference
in tree species richness between dry clusters (SI Appendix, Table
S3, baseline expectation =AF 0.33/SA 0.67), both continents
have nine families that are more speciose than expected. Simi-
lar results were obtained via post hoc χ
tests (SI Appendix,
Tables S4–S6). In total, the families which are signiﬁcantly
for a total of 5,422 more tree species (61% of South Ameri-
ca’s tree species pool in 42 families), 4,739 (59% in 41
families) when only moist vegetation is taken into account,
and 1,161 (33% in 22 families) when comparing the
two continents’dry ﬂoras. Importantly, Fabaceae, Lauraceae,
Melastomataceae, and Myrtaceae are the main families driv-
ing the tree species difference, as they alone account for
2,837 tree species in South America while only having 657
tree species in Africa, in our dataset subsampled for South
Our ﬁndings conﬁrm the meaningful difference in tree species
richness between Africa and South America, which helped con-
fer Africa the title of odd man out (18) and has been docu-
mented to a limited degree in other research efforts (4, 15, 20).
Here, we were able to demonstrate that such intercontinental
differences in tree species richness are clearly driven by variation
in the species richness of moist vegetation clusters. We show
that South America’s moist vegetation holds most of the tree
species accounting for intercontinental differences (four times
more species in South America than in Africa), even though
South America’s dry formations also hold more tree species
overall than their African counterparts (two times more species
in South America than in Africa). Concerning whether South
America’s high tree species richness could be linked to speciﬁc
families, we were able to identify a restricted group of families
that have more species in South America’s moist forests than
anywhere else. Importantly, these families are species rich in
Africa as well, just less so there. Moreover, 9 of these families
account for around 50% of the tree ﬂoras within both conti-
nents, totaling 16 families across all diversity proﬁles (SI
Appendix, Fig. S5), with Fabaceae, Rubiaceae, and Malvaceae
being among the most species rich overall. Importantly, when
overall differences in tree species richness between the two con-
tinents are accounted for, it is possible to see that Africa, which
has proportionally more dry geographic area, also holds highly
diversiﬁed plant families, such as Anacardiaceae, Combretaceae,
Fabaceae, and Malvaceae, families which are notable for radiat-
ing in both moist and dry environments.
Table 1. Summary of the total number of botanical families and tree species present in lowland tropical South
America and Africa
No. of families
present in both
No. of species
belonging to the
No. of families
only found in
No. of species
belonging to the
South America, all
152 8,842 99 8,393 (95%) 53 449 (5%)
Africa, all vegetation
clusters (722 sites)
131 3,048 99 2,954 (97%) 32 94 (3%)
clusters (407 sites)
151 7,979 93 7,501 (94%) 58 478 (6%)
116 2,148 93 2,092 (97%) 23 56 (3%)
South America, dry
125 3,498 81 3,032 (86%) 44 466 (14%)
109 1,570 81 1,505 (96%) 38 65 (4%)
In parentheses, we report the relative proportion of species present in each fraction of families according to the total tree species pool. Numbers given for South America refer to the
subsampled dataset. Percentages given in columns 4 and 6 refer to the total species richness values reported in column 2.
PNAS 2022 Vol. 119 No. 14 e2112336119 https://doi.org/10.1073/pnas.2112336119 5of10
South America’s Moist Vegetation Clusters Account For Most
of the Difference in Tree Species Richness between the Two
Continents. Numerous hypotheses have been proposed to
explain why the Amazon and the Atlantic forests possess such
high tree species richness. The diversity of environments in the
Amazon, spanning such a broad area and ranging from terra
ﬁrme, to seasonally ﬂooded forests, to forests growing on white
sands, has been put forward as one of the reasons why this for-
est is so diverse (55–58). Climatic stability and high water
availability have also been considered as possible drivers of this
high biodiversity (4, 10, 59, 60). With regard to the Atlantic
forest’s tree species diversity, it has been hypothesized that its
high species richness is linked, at least in part, to its broad ele-
vational (0 to ∼2,000 m) and latitudinal ranges (61). More-
over, a recent study has shown the high tree species diversity of
the Atlantic forest (at the regional level) is linked to the pleth-
ora of environments, giving a diversity of habitats (62).
Even though the two continents share a common geological
past, the African ﬂora has been subjected to different environ-
mental pressures (e.g., increased aridity, forest cover reduction,
and fragmentation due to glaciation cycles), which may hold
the answer as to why the African continent holds fewer species
than South America. At present, South America has a greater
forest cover than Africa (63) and about 1.5 times more individ-
ual trees (64). Over evolutionary time, the African moist forest
ﬂora has been subjected to stronger contraction and expansion
events due to climatic variation during the Pleistocene and
Miocene than the moist vegetation in South America, which
has been sheltered, to some degree, from drier climatic condi-
tions by the Andes (19, 40, 65). Also, during forest contraction
events, Africa may have provided fewer and less extensive refu-
gia for its moist forest ﬂora due to fewer mountain ranges,
although the exact location of forest refugia in Africa (66) is
still in debate (67). In our spatially and environmentally com-
prehensive dataset, South America has nearly triple the number
of tree species as Africa (SA/AF =2.9). We suggest that the
current differences in forest cover and number of trees and the
historical differences in contraction/expansion dynamics may
be sufﬁcient to explain current differences in tree species rich-
ness (15) without the need to invoke differences in lineage
speciation rates between the two continents. However, plant
families such as Combretaceae, Ebenaceae, Fabaceae, Phyllan-
thaceae, and Rubiaceae in Africa and Arecaceae, Chrysobalana-
ceae, Lauraceae, Malpighiaceae, Melastomataceae, and Myrtaceae
in South America challenge this perspective, given that they are
surprisingly speciose in one of the two continents, even when
accounting for the overall difference in species richness between
Ranked Family Richness Is Conserved between Africa and
South America Despite Differences in Tree Species Richness.
Africa and South America, during most of Earth’s geological
history, were joined together and formed the bulk of a conti-
nent known as Gondwana, a fact that led past botanical
P < 0.0001
Fig. 3. Correlation plots among African and South American tree ﬂoras concerning number of species per family. (A) All vegetation clusters are included.
(B) Only moist vegetation clusters. (C) Only dry vegetation clusters. (D) African moist and dry vegetation clusters are compared. (E) South American moist
and dry vegetation clusters are compared. Spearman's rank correlation coefﬁcients (r
) and signiﬁcance levels (P) are given within each panel. For informa-
tion on which vegetation clusters were classiﬁed as moist or dry, see Fig. 2. AFR - Africa, SA - South America.
6of10 https://doi.org/10.1073/pnas.2112336119 pnas.org
researchers to associate the two continent’sﬂoristic similarities
(at family and genus levels) to their shared geological past (18,
68). However, during the past ∼90 My, these two continents
split and drifted away from one another, so observed similari-
ties are unlikely to be linked to a shared geological past.
Though some of the families shared by the two continents,
such as Annonaceae (69), have had their origins dated to times
prior to the Gondwanan split, the majority of both African and
South American tree ﬂoras is composed of families that origi-
nated after the Gondwanan split, with most of them only
appearing and diversifying after the K-Pg extinction event (SI
Appendix, Table S7). Therefore, the tree community assembly
of Africa and South America is the outcome of both long-
distance dispersal, via transoceanic dispersal, and ancient land
bridges and speciation events intrinsic to each continent and
their vegetation clusters (36). The correlated species richness
within families and genera across the two continents is most
likely related to climatic niches and diversiﬁcation rates being
relatively well conserved at the family level (70), although fur-
ther studies are needed in order to understand and test
It is surprising to observe that tree species richness across
families on the two continents is remarkably conserved, regard-
less of the overall richness difference between them. Our ﬁnd-
ings indicate ∼50% of each continent’s tree species richness is
formed by a restricted group of families that are mostly present
on both continents, a pattern also found at the global level
(49). Given that how plant families have been circumscribed
has been well established over the years [e.g., Angiosperm Phy-
logeny Group (APG) III (71) and APG IV (72)], it is unlikely
that this ﬁnding will change in the future or that it is a direct
bias of how the classiﬁcation system is structured. When inves-
tigating the taxonomic structure of several sites in moist forests
in Africa, Asia, and South America as the means to test the role
of neutral processes in community assembly on different conti-
nents, the same pattern that we highlight here—families that
are species rich on one continent are most likely species rich on
the other continent—was observed as well (14). The striking
result that a set of 16 families accumulates 50% of each conti-
nent’s total tree species richness across both moist and dry vege-
tation clusters results from each family’s biogeographic history,
along with features that would ensure adaptive advantages over
South America: Fabaceae (1253 spp.), Myrtaceae (674), Rubiaceae (607), Melastomataceae (474),
Lauraceae (436), Annonaceae (352), Euphorbiaceae (254), Chrysobalanaceae (249), Malvaceae (245)
South America: Fabaceae (1061), Myrtaceae (600), Rubiaceae (580), Melastomataceae (451),
Lauraceae (405), Annonaceae (337), Chrysobalanaceae (249)
South America: Fabaceae (569), Myrtaceae (246), Rubiaceae (178), Melastomataceae (166),
Lauraceae (155), Euphorbiaceae (116), Annonaceae (98 spp.), Asteraceae (92), Malvaceae (92)
All Vegetaon Clusters Moist Vegetaon Clusters Dry Vegetaon Clusters
50% of total
Significantly richer families
Africa: Fabaceae (581), Rubiaceae (272), Malvaceae (190),
Euphorbiaceae (135), Annonaceae (109), Anacardiaceae (84),
Sapindaceae (91), Phylantaceae (82), Sapotaceae (79)
Africa: Fabaceae (420), Rubiaceae (169), Malvaceae (126),
Annonaceae (97), Euphorbiaceae (95), Sapindaceae (80),
Sapotaceae (72), Phylantaceae (65), Moraceae (58)
Africa: Fabaceae (273), Rubiaceae (152), Malvaceae (102),
Euphorbiaceae (77), Anacardiaceae (59), Combretaceae (50),
* Endemic Families to
South America (= 44)
* Endemic Families
to Africa (= 38)
* Endemic Families to
South America (= 58)
* Endemic Families
to Africa (= 23)
* Endemic Families to
South America (= 53)
* Endemic Families
to Africa (= 32)
Fig. 4. Families ranked in decreasing order of species richness (log10) in both Africa (circles) and South America (triangles). (A) All vegetation clusters
combined. (B) Only the moist clusters. (C) Only the dry clusters. Families in black hold 50% of the total species pool in each continent. Families in gray hold a
signiﬁcantly higher number of species in relation to that same family in the opposing continent. Asterisks represent families that can only be found on the
continent they are in. Text boxes in each panel lists the families represented by the black symbols and shows the number of tree species they hold in each
PNAS 2022 Vol. 119 No. 14 e2112336119 https://doi.org/10.1073/pnas.2112336119 7of10
continental scales (12, 13). For example, most clades from the
Fabaceae family can ﬁx nitrogen (73), enabling this group to
adapt to a variety of harsh environmental conditions, particu-
larly high seasonality (52). Meanwhile, most Rubiaceae clades
have a complex biogeographic history, and their high diversity
in South America seems to be linked to the rise of the Andes
(74). Families like Myrtaceae and Lauraceae are more com-
monly found in moist environments and, in South America,
have acquired adaptations to colder temperatures, enabling
them to diversify in higher elevations (75), which could explain
their high diversity in South America and low diversity in
Africa. In contrast, Ebenaceae, particularly the genus Diospyros,
is known for its morphological and species diversity in Africa,
coupled with a geographically wide distribution (76, 77).
Future studies unveiling the biogeographic and evolutionary
history of key clades encompassing multiple growth habits
(e.g., herbs and lianas) will provide more information on the
comparative evolution of African and South American ﬂoras.
Here, we show that the previously observed difference in tree
species richness between Africa and South America is the result
of species richness anomalies in a restricted group of families
that are exceptionally diverse in South American moist forests.
Surprisingly, these same families are also species rich in African
moist vegetation and in African and South American dry vege-
tation; they are just much more speciose in South American
moist forests. We also show that both African and South Amer-
ican tree ﬂoras have similar taxonomic organizations regardless
of differences in tree species richness: families that are speciose
on one continent are speciose on the opposite continent as
well. However, our ﬁndings also point to each continent having
its own ﬂoristic identity and intrinsic patterns of tree species
richness and distribution, evidenced by strong within-continent
correlations in richness between moist and dry vegetation for-
mations. Therefore, intracontinental dynamics seem to have a
more prominent role in biome assembly than intercontinental
lineage dispersal or migration.
Materials and Methods
Tree Species Inventories. We analyzed two datasets: one for Africa and one
for South America. The African dataset (AfroTropTree) is the union of the datasets
employed for the biogeography of forest (78) and savanna (23) trees and was
ﬁrst jointly analyzed by Aleman et al. (44), while the South American dataset
(NeoTropTree, http://www.neotroptree.info)wasﬁnished in 2018 and has been
fully available online ever since. Both are collections of georeferenced tree spe-
cies checklists compiled from published (e.g., scientiﬁc articles) and unpublished
(e.g., master’s and PhD theses) sources that have been carefully compiled,
checked, and incorporated over the years. In both AfroTropTree and NeoTropTree,
we deﬁne trees as woody plants capable of growing 3 m in height and that are
freestanding. Importantly, the compilation of these resources was made by con-
stantly verifying species identiﬁcations via contacting taxonomists and specialists
and by performing yearly taxonomic updates. Only valid and accepted species
names are included in both datasets; we checked name validity by consulting
Tropicos (https://tropicos.org/), the African Plant Database (curated by the Conser-
vatoire et Jardin Botanique de la Ville de Gen
eve), and the Lista de Esp
Flora do Brasil (Brazil only). Moreover, when possible, species inclusion in the
dataset was veriﬁed by evaluating herbaria vouchers. Both African (23, 44, 78)
and South American (79–81) datasets have been explored and validated in previ-
ous research aiming to investigate macroecological, biogeographic, and evolu-
tionary research questions within continents. Further details on how both
datasets were assembled can be found in the references (23, 44, 78–81) and in
the SI Appendix,SI Materials and Methods. Here, we only included checklists of
frost-free areas [fourth criterion of (82)] and below 1,750 m of elevation. In the
case of South America, we also excluded inventories from the Andes and from
Delimiting Vegetation Clusters. Asthemeanstocreateaframework
enabling tree species diversity comparisons between the two continents for anal-
ogous vegetation clusters, we employed a hierarchical clustering approach based
on species turnover in order to delimit the main vegetation clusters in lowland
tropical Africa and South America. By working with species assemblages of vege-
tation clusters instead of collections of individual checklists, we reduce the pseu-
doreplication effect generated by species cooccurrence over broad geographic
spaces (83). We conducted two clustering analyses—one for Africa and one for
South America—since the two continents share only a small fraction of species
(only 31 shared species in the combined dataset). The ﬁnal African matrix
included 3,048 tree species (816 genera and 131 families) distributed along
722 sites. The ﬁnal South American matrix included 10,268 tree species (1,197
genera and 158 families) distributed along 4,980 sites. These occurrence tables
were then used to build pairwise ﬂoristic-distance matrices showing how similar
or dissimilar each site is to the other sites in relation to their tree species compo-
sition. To this end, we employed the Simpson index of dissimilarity [Betasim
(84), available on the R package recluster (85)]. This index has been shown to
produce unbiased results even when the data holds 1) differences in sampling
effort (uneven sampling) and 2) meaningful differences in species richness.
We then grouped the sites according to their pairwise ﬂoristic distances by
employing the unweighted pair group method with arithmetic mean (UPGMA)
clustering algorithm, as recommended by Kreft and Jetz (86), as it was proven
to consistently have the best performance among other algorithm options for
biogeographic delimitation purposes when analyzing occurrence data (presence/
absence). We repeated this procedure 100 times by randomizing the order of
rows in the community matrix and assimilated the resulting dendrograms into a
ﬁnal dendrogram by following the majority-rule consensus approach. Therefore,
the two ﬁnal dendrograms only portray groups/branches present in a majority of
dendrograms. In order to obtain fully resolved dendrograms (all nodes are bifur-
cations), we employed the RogueNaRok algorithm, a tool commonly used to
build fully resolved phylogenies (87). Here, we used this algorithm to detect
sites across the dendrograms with high instability in placement, which prevent
the determination of a fully resolved ﬁnal solution. This led to the removal of 40
sites in Africa and 80 sites in South America. We built the pairwise distance
matrices and the ﬁnal dendrograms using functions in the recluster package
(88) in R software. We compiled and ran the RogueNaRok algorithm in C lan-
guage on a Linux (Ubuntu) machine.
We inspected the two ﬁnal dendrograms for Africa and South America and
manually delimited their vegetation clusters by observing the following criteria:
1) overall branching pattern of each dendrogram and 2) main vegetation types
present on each branch. We then investigated how these vegetation clusters
were distributed in multivariate, compositional, and geographic spaces. For the
former, we performed a nonmetric multidimensional scaling (NMDS) ordination
and plotted the sites according to their scores on the ﬁrst and second axes. For
the latter, we plotted the sites onto maps and investigated the limits of their
geographic distribution. We performed the NMDS analyses by applying the
metaMDS function from the vegan package in the R software. Importantly, prior
to performing further analysis and due to differences in dataset size, we selected
722 sites from South America in a geographically stratiﬁed, but otherwise ran-
dom, fashion to maintain the proportion of sites per vegetation type present in
the South American dataset and to guarantee full geographic coverage of sam-
pling. The combined dataset for all analyses described in the following sections
contained 1,444 sites (722 for each continent).
Environmental Affinities. To investigate the climatic space occupied by the
delimited vegetation clusters and compare overlaps/partitions within and
between continents, we performed a PCA for all sites in Africa and the sub-
sampled sites for South America, based on their values for climatic variables. We
retrieved all 19 climatic variables available from Climatologies at High Resolu-
tion for the Earth’s Land Surface (CHELSA), which portrays yearly variation
patterns in precipitation and temperature. We also included the climatic water
deﬁcit from Chave et al. (89). We then compared the average PCA scores per
vegetation cluster on the ﬁrst two axes of the combined climatic PCA. Based on
8of10 https://doi.org/10.1073/pnas.2112336119 pnas.org
these results, we categorized all vegetation clusters into two broad categories:
moist climate versus dry climate vegetation clusters. We conducted the PCA with
the ade4 package (90). PCA biplots were built with the factorextra package (91),
also in R.
Comparing Diversity Profiles. Here, we compared the taxonomic organiza-
tion of the tree ﬂoras of Africa and South America. Firstly, we counted the num-
ber of families and genera present on the two continents and in their moist and
dry clusters. We then proceeded to calculate the proportion of the total species
pool the shared families and genera hold (between the whole continents and
between moist and dry vegetation clusters). Secondly, to assess the extent of
congruence in the taxonomic composition of the two continents, we performed
a series of Spearman rank correlations, where high correlation values are
obtained when families are ranked in the same position according to their tree
species richness. We did the following correlations: 1) African and South Ameri-
can whole ﬂoras, 2) African and South American moist ﬂoras, and 3) African and
South American dry ﬂoras. We also investigated intracontinental correlations
between moist and dry ﬂoras at the family level 4) for African moist and dry ﬂo-
ras and 5) for South American moist and dry ﬂoras. Following the same protocol,
we also did Spearman rank correlations at the genus level (number of species
To compare African and South American diversity proﬁles, we built ranked-
richness curves, ordering families according to their species richness in decreas-
ing order and therefore following the same logic applied to the construction of
ranked-abundance plots in community ecology [e.g., (41)]. To this end, we used
the same subsampled dataset we employed to build the PCA and built diversity
proﬁles for Africa and South America in three different ways: 1) including all veg-
etation clusters, 2) including only moist vegetation clusters, and 3) including
only dry vegetation clusters. In each proﬁle, we identiﬁed 1) the most species-
rich families that make up ∼50% of the total tree species richness of each curve,
following the logic used to identify species that are hyperdominant in terms of
abundance (41); 2) the families only present in one continent; and 3) the
families with statistically higher species richness in one continent in comparison
to the other. As the means to detect the latter families, we applied two comple-
mentary rounds of binomial tests to the species richness per family in each
diversity proﬁle (whole continent, moist vegetation clusters, and dry vegetation
clusters). Only familiespresent in the two continents were considered. In the ﬁrst
round, we set an equal null expectation of a family having the same number of
tree species on both continents (AF 0.50/SA 0.50), allowing for detection of
meaningful differences in species richness between the two continents. In the
second round, expected species richness per family was conditioned by the exist-
ing overall richness proportions of the two continents (whole continent, AF 0.26/
SA 0.74; moist vegetation clusters, AF 0.21/SA 0.79; and dry vegetation clusters,
AF 0.33/SA 0.67), therefore allowing the detection of families that are speciose
even when accounting for the chief trend of South America being more species
rich than Africa. We conﬁrmed the results obtained via binomial tests with χ
tests (followed by post hoc χ
tests) to identify families that were more or less
speciose than expected. We obtained signiﬁcance measures in the χ
applying a Monte Carlo simulation procedure, as not all assumptions of the test
were met (no expected values are lower than 1 and at least 80% of expected val-
ues are higher than 5). We applied Bonferroni correction to determine thresholds
for signiﬁcance due to multiple testing on both binomial and χ
post hoc tests.
Data Availability. Previously published data were used for this work [NeoTrop-
Tree, http://www.neotroptree.info/; (44, 92)]. All other study data are included in
the article and/or SI Appendix.
ACKNOWLEDGMENTS. P.L.S.d.M. thanks the University of Liege for providing
funding under the IPD-STEMA scheme. A.F. thanks BELSPO for the funding of
the HERBAXYLAREDD project (Grant BR/143/A3/HERBAXYLAREDD), and O.J.H.
thanks FNRS for funding the AFRITIMB project. K.G.D. thanks the UK Natural
Environment Research Council (Grant NE/I028122/1) for providing funding.
A.T.d.O.-F. thanks CNPq for a productivity fellowship (301644/88-8). We thank
Samuel Quevauvillers forthe Microsoft Access automated check routine.
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