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Segovia et al., Sci. Adv. 2020; 6 : eaaz5373 6 May 2020
SCIENCE ADVANCES | RESEARCH ARTICLE
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EVOLUTIONARY BIOLOGY
Freezing and water availability structure the
evolutionary diversity of trees across the Americas
Ricardo A. Segovia1,2*, R. Toby Pennington3,4, Tim R. Baker5, Fernanda Coelho de Souza5,6,
Danilo M. Neves7, Charles C. Davis8, Juan J. Armesto2,9,10, Ary T. Olivera-Filho7, Kyle G. Dexter1,3
The historical course of evolutionary diversification shapes the current distribution of biodiversity, but the main
forces constraining diversification are still a subject of debate. We unveil the evolutionary structure of tree species
assemblages across the Americas to assess whether an inability to move or an inability to evolve is the predominant
constraint in plant diversification and biogeography. We find a fundamental divide in tree lineage composition
between tropical and extratropical environments, defined by the absence versus presence of freezing temperatures.
Within the Neotropics, we uncover a further evolutionary split between moist and dry forests. Our results demon-
strate that American tree lineages tend to retain their ancestral environmental relationships and that phylogenetic
niche conservatism is the primary force structuring the distribution of tree biodiversity. Our study establishes the
pervasive importance of niche conservatism to community assembly even at intercontinental scales.
INTRODUCTION
A central challenge in biogeography and macroevolution is to un-
derstand the primary forces that drove the diversification of life and
the assemblage of ecological communities. Was diversification con-
fined within continents and characterized by adaptation of lineages to
different major environments (i.e., biome switching), or did lineages
tend to disperse across great distances but retain their ancestral envi-
ronmental niche (i.e., phylogenetic niche conservatism)? Classically,
the attempts to define biogeographic regions based on shared plant
and animal distributions lend support to the first hypothesis, that large-
scale patterns may be explained by regionally confined evolutionary
diversification, rather than long-distance dispersal (1–3). However,
recent studies of the distribution of plant lineages at global scales have
documented high levels of intercontinental dispersal [e.g., (4–8)] and
revealed that lineages tend to retain their ancestral biomes when
dispersing (9,10). These recent findings suggest that environmental
associations of lineages may be the primary force organizing the course
of diversification, but a key knowledge gap is in studies comparing
the degree of evolutionary similarity among species assemblages at
large geographic scales. Taking advantage of recent advances in the
availability of broadscale biodiversity and genomic data and appro-
priate analytical methods (11), we unveil the evolutionary structure
of tree assemblage diversity at an intercontinental scale.
With high mountain chains running north to south across latitudes
and a mosaic of contrasting environments, the Americas represent
a natural laboratory to investigate the evolutionary forces behind
community assembly and the modern distribution of biodiversity.
Here, we examine the phylogenetic composition of angiosperm tree
assemblages across the Americas as a means to determine whether
dispersal limitation or phylogenetic niche conservatism had a greater
impact on the present-day evolutionary composition of tree assem-
blages. If lineages tend to retain their environmental niche as they
diversify across space, then we would expect major evolutionary groups
to be restricted to specific environmental regimes. This leads to the
prediction that lineage composition of assemblages from extratropical
regions in both hemispheres should be more similar to each other
than to assemblages that occur in intervening tropical regions. In ad-
dition, we would predict that assemblages from dry tropical environ-
ments should show greater similarity in tree lineage composition to
each other than to assemblages from moist environments with which
they may be spatially contiguous (12). Alternatively, if diversification
is spatially restricted and biome switching is common, then the major
evolutionary grouping of assemblages should be segregated geo-
graphically. Thus, we would predict assemblages from South America
(which was physically isolated through the Cenozoic) to constitute one
group and assemblages from North and Central America to constitute
another.
To test the relative importance of phylogenetic niche conservatism
versus dispersal limitation, we analyzed data from ~10,000 tree
assemblages with a new, temporally calibrated genus-level phylogeny
that includes 1358 genera (~90% of tree genera sampled per assem-
blage). We assessed similarity in lineage composition among assem-
blages using clustering analyses and ordinations based on shared
phylogenetic branch length. Next, we identified the indicator lineages
for each major group in the clustering analysis and explored the geo-
graphic and environmental correlates of the distribution of the main
evolutionary clusters. We further assessed the degree to which climatic
variables versus geographic position could classify sites into different
evolutionary groups. If climatic variables provide a better means of
distinguishing groups than geographic variables, then this would sup-
port the idea that phylogenetic conservatism is more important than
dispersal limitation in determining the distribution of evolutionary
lineages, while the converse would hold if geographic variables per-
form better. Last, we estimated the unique evolutionary diversity (i.e.,
sum of phylogenetic branches of lineages restricted to individual groups)
versus shared evolutionary diversity (i.e., sum of shared phylogenetic
branches) across evolutionary groups (for details, see Materials and
Methods section).
1School of GeoSciences, University of Edinburgh, Edinburgh, UK. 2Instituto de
Ecología y Biodiversidad, Santiago, Chile. 3Tropical Diversity Section, Royal Botanic
Garden Edinburgh, Edinburgh, UK. 4Department of Geography, University of Exeter,
Exeter, UK. 5School of Geography, University of Leeds, Leeds, UK. 6Departamento
de Engenharia Florestal, Universidade de Brasília (UNB), Campus Universitário Darcy
Ribeiro, Asa Norte, Brasília 70910-900, Brazil. 7Department of Botany, Federal
University of Minas Gerais, Belo Horizonte, Brazil. 8Department of Organismic and
Evolutionary Biology, Harvard University, Cambridge, MA, USA. 9Departamento de
Ecología, Universidad Católica de Chile, Santiago, Chile. 10Facultad de Ciencias Naturales y
Oceanográficas, Universidad de Concepción, Concepción, Chile.
*Corresponding author. Email: segoviacortes@gmail.com
Copyright © 2020
The Authors, some
rights reserved;
exclusive licensee
American Association
for the Advancement
of Science. No claim to
original U.S. Government
Works. Distributed
under a Creative
Commons Attribution
License 4.0 (CC BY).
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RESULTS
We show that the evolutionary lineage composition of American
tree assemblages is structured primarily by phylogenetic niche conser-
vatism. The two principal groups (K=2) have a tropics-extratropics
structure (Fig.1). The extratropical group is not geographically re-
stricted, but includes temperate tree assemblages from North America
and southern South America, connected by a high-elevation corridor
in low latitudes (Fig.1,AandB). The tropics-extratropics structure
of tree evolutionary diversity shows a strong correspondence (97%
match, fig. S1) with the absence versus occurrence of freezing tem-
peratures within a typical year (see Fig.1,CandD). We observe that
most evolutionary diversity, measured as summed phylogenetic branch
length, occurs within the tropics, but that there is unique evolutionary
diversity restricted to the extratropics (~10% of the total; Fig.2B
and fig. S3A). Ordination and indicator clade analyses revealed that
the tropics-extratropics segregation is associated with the distribution
of specific clades, such as the Fagales, which includes the oaks (Quercus),
beeches (Fagus), coihues (Nothofagus), and their relatives (Fig.3 and
tables S1 and S2).
On the basis of two different analyses (Elbow and Silhouette
methods; see Materials and Methods for discussion of selecting op-
timal K), clusters of K=3 and K=4 groups are also supported as
additional informative splits (fig. S2), and each of their major groups
capture substantial unique evolutionary diversity (Fig.2B, fig. S3,
and table S2). In K=3, the main extratropical cluster grouped as-
semblages from North America and extreme southern South America,
while the remaining assemblages from temperate southern South
America and the Andean tropics grouped with assemblages from the
arid or semiarid tropics and subtropics (fig. S4). The third group was
formed by the moist tropics (fig. S4). For K=4, the extratropics were
split into a largely temperate North American group and a second
group that joins subtropical sites in South and Central America with
southern temperate forests and high elevation sites in the Andes (Fig.
2A). In the tropics, there is one group uniting assemblages found in
ever-moist and warm conditions, and a second group of assemblages
that extend into drier and subtropical areas (Fig.2C and fig. S5A),
including most tropical dry forest assemblages (Fig.2A and Table S3).
We refer to the four groups of assemblages in K=4 as the northern
extratropical, southern extratropical, tropical moist, and tropical dry
groups.
Focusing on the K= 4 analyses, we found that climatic variables
perform markedly better than geographic variables in classifying in-
dividual assemblages into evolutionary groups, supporting the preem-
inence of phylogenetic niche conservatism as opposed to dispersal
limitation in structuring the distribution of biodiversity in tree as-
semblages. A simple climatic model with mean annual precipitation
(MAP), mean annual temperature (MAT), maximum climatological
water deficit (CWD), and temperature seasonality (TS) succeeded in
classifying 86.4% of assemblages, on average, into the correct evolu-
tionary group. A simple geographic model, that South American as-
semblages should fall into a separate group from North and Central
American assemblages, and with latitude and longitude as input
−120 −100 −80 −60 −40
−40−20 02040
Tropical assemblages
Extratropical assemblages
K= 2
A
−40 −20 02
04
0
0
1000 2000 3000 4000
Latitude
Elevation (masl)
B
−0.6 −0.4 −0.2 0.0 0.2
−0.4 −0.2 0.0 0.2 0.4
Evolutionary ordination axis 1
Evolutionary ordination axis 2
C
−0.6 −0.4 −0.2 0.0 0.2
−0.4 −0.2 0.0 0.2 0.4
Evolutionary ordination axis 1
Evolutionary ordination axis 2
Freezing
Nonfreezing
D
Fig. 1. The geographic, evolutionary, and environmental relationships of the two principal evolutionary groups (from K = 2 clustering analysis). (A) Geographic
distribution of angiosperm tree assemblages and their affiliation with either the tropical (n = 7145) or extratropical (n = 2792) evolutionary group. (B) Distribution of as-
semblages over elevation and latitude, showing that the extratropical group is largely restricted to high elevations at low latitudes. (C and D) Distribution of assemblages
over the first two axes of an ordination based on evolutionary composition with assemblages in (C) colored according to group affiliation and in (D) as to whether or not
they experience freezing temperatures in a regular year [from (50)]. masl, meters above sea level.
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−120 −100 −80 −60 −40
−40 −20 02040
Tropical moist
Tropical dry
Southern extratropical
Northern extratropical
K= 4
A
−20 −10 01
02
0
−2000 −1000 0
Minimum temperature of coldest month (°C)
Maximum climatological
water deficit (CWD)
C
B
Northern
extratropical
Southern
extratropical
Tropical dry
Tropical moist
12,586 Ma
4914 Ma
3992 Ma
5835 Ma
5715 Ma
1284 Ma
11,954 Ma
1942 Ma
Fig. 2. The geographic, evolutionary, and environmental relationships among four evolutionary groups (from K = 4 clustering analysis). (A) Geographic distribu-
tion of angiosperm tree assemblages and their affiliation with one of the four evolutionary groups. (B) Euler diagram representing the amount of evolutionary history,
quantified as phylogenetic diversity (PD) (in millions of years), restricted to each cluster versus that shared between clusters. (C) Distribution of assemblages over ex-
tremes of temperature (minimum temperature of coldest month) and water availability [maximum climatological water deficit (CWD)]. Lines represent the 95th quantile
of the density of points for each group.
Evolutionary ordination axis 1 (9.6%)
Evolutionary ordination axis 2 (6.7%)
Moist lowland tropics (evergreen
and semideciduous forest)
Tropical savanna
Tropical dry forests
Northern temperate
Tropical high elevation (>2000 masl)
Chaco
Southern South America
−0.4 −0.2 0.0 0.2 0.4
−0.50.0
Fig. 3. Phylogenetic ordination of tree assemblages based on their evolutionary lineage composition. Colors in the main plot represent the groups from K = 4
clustering analyses and the different symbols represent major vegetation formations. The subset plot shows the clades most strongly associated with the first two axes
of the evolutionary ordination.
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variables, classified 76.0% of assemblages correctly on average. Add-
ing latitude and longitude may even overemphasize the importance
of geography given that latitude and longitude are correlated with cli-
matic variation. In the climatic classification for K= 4 groups, tem-
perature variables surpass precipitation variables as the most im-
portant classificatory variables [mean decrease in Gini index when
excluded (13); for TS, 2728; MAT, 1565; MAP, 1064; and CWD, 936].
When focusing only on the tropics, these climatic variables correctly
classify sites 83.6% of the time, with the most important variable being
CWD (mean decrease in a Gini index of 792), followed by MAT
(722), TS (643), and MAP (642). When focusing only on the extra-
tropics, these climatic variables correctly classify sites 98.4% of the
time. TS was by far the most important variable (mean decrease in a
Gini index of 719), which is in line with previous research showing
that Southern Hemisphere temperate areas are less seasonal than
Northern Hemisphere temperate areas (14,15). TS was followed in
importance by CWD (157), MAP (92), and MAT (75). Analyses
with generalized linear models suggest that MAP is the most im-
portant climatic variable to distinguish assemblages in the tropical
moist from tropical dry groups and that TS is the most important to
distinguish the two extratropical groups (fig. S6).
DISCUSSION
Our results demonstrate that the tropics-extratropics evolutionary
structure of tree diversity is principally associated with the environmen-
tal threshold of the presence versus absence of freezing temperatures
(Fig.1,AandB, and fig. S1). This pattern is consistent with evidence
documenting that only angiosperm lineages that were able to evolve
traits to avoid freezing-induced embolism radiated into high latitudes
(16). In addition, we determined that a unique, sizeable portion of
the total evolutionary diversity of angiosperm trees is restricted to
extratropical assemblages, as the fossil record corroborates (17,18).
Collectively, this evidence suggests that the phylogenetic conserva-
tism of lineages from the extratropics has a major relevance for the
diversification of angiosperm trees in the Americas. Kerkhoff etal.
(19) estimated that in the extratropical region (defined by them as
areas north of 23°N and south of 23°S), angiosperm lineages produced
extratropical descendants at least 90% of the time. Considering that
some areas subjected to regular freezing at high elevations in equatorial
latitudes may be better classified as extratropical, as demonstrated
here by our results (Fig.1), extratropical phylogenetic conservatism
could even be greater than found by Kerkhoff etal. (19).
We suggest that extratropical conservatism has a major impor-
tance in the biogeography of the Americas. The relatively recent
uplift of the Andes would have created novel environments, with reg-
ular freezing temperatures, at low latitudes. Freezing temperatures
would have filtered dispersal into this new habitat, allowing extra-
tropical lineages to move from both north and south to equatorial
latitudes (20,21), but constraining the immigration of lineages from
lowland, frost-free environments. Fossil pollen demonstrates the ar-
rival in the northern Andes of tree genera from temperate forests in
the Northern Hemisphere, including Juglans (Juglandaceae), Alnus
(Betulaceae), and Quercus (Fagaceae), at about 2.2million years (Ma),
1.0 Ma, and 300,000 years, respectively, and the arrival of southern
genera, including Weinmannia (Cunoniaceae) and Drymis (Wintera-
ceae), during the late Pliocene and Pleistocene (1.5–3.2 Ma) (20,22).
Likewise, phylogenetic evidence shows recent diversification in the
Andes of lineages that seem to have originated in the extratropics,
including Lupinus (Fabaceae) (23), Adoxaceae/Valerianceae (24,25),
and Gunnera (Gunneraceae) (26).
Our results also point to a moist versus dry evolutionary divide
within the Neotropics. Tropical moist group assemblages hold the
greatest amount of evolutionary diversity, both overall and unique
to them, despite occupying the most restricted extent of climatic space
of any of the K=4 groups (Fig.2,BandC). Tropical dry group
assemblages, in contrast, extend across a broader climatic space, but
hold less evolutionary diversity overall (Fig.2,BandC). This asym-
metry in the accumulation of diversity may reflect phylogenetic con-
servatism for a putatively moist and hot ancestral angiosperm niche
(27), or could result from a favorable environment in tropical moist
regions that can be occupied by any angiosperm lineage, even those
that also occur in cooler or drier conditions (28,29). Regardless, the
similarity in the lineage composition of the extensive but discontin-
uously distributed tropical dry forests (12) indicates their separate
evolutionary history. Tropical dry forests have been described as dis-
persal limited (e.g., 12), but this refers to the ability of constituent
taxa to persist locally over evolutionary time scales, thereby inhibiting
immigration. However, even a low rate of dispersal and immigration
among American tropical dry forest regions suffices to maintain flo-
ristic cohesion. Such evolutionary isolation of the dry forest flora has
previously been suggested by studies in Leguminosae (12,30), and is
shown here to be evident at the evolutionary scale of all angiosperm
tree species.
Our results also help to clarify the contentious evolutionary sta-
tus of savanna and Chaco regions in the Neotropics. We find that
the southern savannas (the Cerrado region of Brazil) are more evolu-
tionary related to tropical moist forests than dry forests (Fig.2A, and
fig. S4), as previously suggested for specific clades (30,31). However,
northern tropical savannas (i.e., Llanos of Venezuela and Colombia
and those in Central America) are split in their evolutionary linkages
between the tropical moist and tropical dry groups (Fig.3 and table
S3). This may reflect the distinct ecology of many northern savannas
[e.g., the Llanos are hydrological savannas (32)] and suggest a diver-
gent evolutionary history for northern and southern savannas. Our
results may also help to resolve the debates around the evolutionary
affinities of the Chaco [e.g., (33,34)], by showing that this geograph-
ically defined region houses a mix of extratropical and tropical
lineages (Fig.2).
More broadly, our analyses consistently point to evolutionary links
between assemblages in seasonally dry and seasonally cold areas
(Fig. 2 and fig. S4). For example, when we consider K=3 evolutionary
groups, a single “dry and cool” group coalesces, including southern
South American extratropics, seasonally tropical dry forests, and
Mexican pine-oak forests, with the other two groups being the trop-
ical moist forest group and a largely northern, extratropical group
(fig. S4). Along the same lines, the southern extratropical group from
the K=4 clustering also includes subtropical forests in arid and semi-
arid regions of Chile, Mexico, and elsewhere (Fig.2), while the tropical
dry group includes tree assemblages occurring in cool areas at high
elevation, largely in the southern Atlantic Forest of Brazil (Fig.2).
When we consider K=5 evolutionary groups, these cool sites, which
are also moister than the rest of the tropical dry group, split off to
form a fifth group that also takes in sites at higher elevation in the
Andes, the Guianan Highlands, Central America, and the Caribbean
(fig. S5).
We show that the evolutionary composition of tree assemblages
in the Americas is determined primarily by the presence versus
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absence of freezing temperatures, dividing tropical from extratropical
regions. Within the tropics, we find further evolutionary subdivision
among assemblages experiencing moist versus seasonally dry con-
ditions. These findings demonstrate that phylogenetic niche conserva-
tism is the primary force organizing the diversification, community
assembly, and, therefore, the biogeography of angiosperm trees. Tree
species that can inhabit areas experiencing freezing temperatures
and/or environments subjected to seasonal water stress belong to a
restricted set of phylogenetic lineages, which gives a unique evolu-
tionary identity to extratropical forests and tropical dry forests in the
Americas. While our study is restricted to New World trees, we suggest
that plant biodiversity globally may be evolutionarily structured fol-
lowing a tropics-extratropics pattern, while diversity within the tropics
may be structured primarily around a moist-dry pattern. These find-
ings advocate strongly for integrating the concepts of extratropical con-
servatism and tropical-dry conservatism into our understanding of
global macroevolutionary trends and biogeographic patterns.
MATERIALS AND METHODS
Tree assemblage dataset
Our tree assemblage dataset was derived by combining the NeoTropTree
(NTT) database (35) with selected plots from the Forest Inventory
and Analysis (FIA) Program of the U.S. Forest Service (36), accessed
on 17 July 2018 via the BIEN package (37). Sites in the NTT database
are defined by a single vegetation type within a circular area of 5-km
radius and contain records of tree and tree-like species, i.e., free-
standing plants with stems that can reach over 3m in height [see
www.neotroptree.info and (38) for details]. Each FIA plot samples
trees that are ≥12.7-cm diameter at breast height in four subplots
(each being 168.3m2) that are 36.6m apart. We aggregated plots from
the FIA dataset within 10-km-diameter areas, to parallel the spatial
structure of the NTT database. We excluded any sites that had less
than five angiosperm genera, as preliminary analyses suggested that
these sites lacked sufficient information to be confidently placed in
evolutionary ordinations and clustering described below. Therefore,
the FIA dataset was reduced considerably, and some regions with a
low diversity of angiosperms have no samples in our study. This pro-
cedure produced a total dataset of 9937 tree assemblages distributed
across major environmental and geographic gradients in the Americas.
Genus-level phylogenetic tree
We obtained sequences of the rbcL and matK plastid gene for 1358
angiosperm tree genera, from GenBank (www.ncbi.nlm.nih.gov/
genbank/), building on previous large-scale phylogenetic efforts for
angiosperm trees in the Neotropics (39,40). Sequences were aligned
using the MAFFT software (41). “Ragged ends” of sequences that
were missing data for most genera were manually deleted from the
alignment.
We estimated a maximum likelihood phylogeny for the genera
in the RAxML v8.0.0 software (42) on the CIPRES web server (www.
phylo.org). We constrained order-level relationships in the tree, fol-
lowing the phylogeny in Gastauer etal. (43), which is based on the
topology proposed by the Angiosperm Phylogeny Group IV. We
concatenated the two chloroplast markers following a general time
reversible+gamma model of sequence evolution. We included se-
quences of Nymphaea alba (Nymphaeaceae) as an outgroup. We used
a maximum likelihood bootstrap analysis to assess support for rela-
tionships in the phylogeny. Most deeper relationships in the phylogeny
had high support values (>70 bootstrap support), which is expected
given that ordinal relationships were fixed. More recent nodes in the
phylogeny had lower support with the relationships of genera within
families having mean bootstrap support values of ~60. However, we
confirmed that relationships of families within orders and genera within
families generally matched those in more detailed phylogenetic analyses
(with more variable genetic markers), specifically those studies listed
in table S4. The low support values are likely attributable to the rela-
tively low variability of the matK and rbcL markers within angiosperm
families.
We temporally calibrated the maximum likelihood phylogeny
using the software treePL (44). We implemented age constraints for
320 internal nodes [family level or higher, from (45)] and for 123 gen-
era stem nodes (based on ages from a literature survey; table S4). The
rate smoothing parameter (lambda) was set to 10 based on a cross-
validation procedure. The final dated phylogeny can be found in the
Supplementary Materials.
Phylogenetic distance analysis and clustering
We used the one complement of the Phylosor index (i.e., 1 − Phylo-
Sorensen) to build a matrix of phylogenetic dissimilarities between
plots based on genera presence-absence data. The Phylosor index
sums the total branch length of shared clades between sites (46) rel-
ative to the sum of branch lengths of both sites
Complement of Phylo − Sorensenij = 1 − BLij / 0.5 * (BLi + BLj)
where BLij is the sum of shared phylogenetic branch length between
sites i and j, and BLi and BLj are the sum of branch length of phylog-
enies comprising solely genera within sites i and j, respectively.
Thus, if all branches are shared between two plots, then the dissim-
ilarity measure takes on a value of 0. If no branches are shared
between plots (i.e., the plots comprise two reciprocally monophyletic
clades), then the dissimilarity measure will take on a value of 1.
This metric was estimated using the phylosor.query() function in the
PhyloMeasures (47) package for R. Analyses with the one complement
of the Unifrac phylogenetic similarity measure gave highly similar
results and are not presented here.
We used K-means clustering to explore the main groups, in terms
of (dis)similarity in the tree assemblage dataset, according to the
Phylosor dissimilarity measures. Preliminary analyses using hierarchical
clustering approaches did not produce coherent groupings. The K-
means clustering algorithm requires the number of groups/clusters
(K) to be specified in advance. To estimate the best value for K, the
optimal number of clusters to parsimoniously explain the variance
in the dataset, we used the Elbow method and an approach based on
the average Silhouette width (fig. S2). The Elbow method assesses
how the total within-cluster sum of squares (TSS) changes as a function
of the number of clusters. Each additional cluster lowers the TSS,
and the elbow of the curve is formed when adding another cluster
fails to lower the TSS substantially compared to previous increases
in cluster number. On the other hand, the Silhouette width analysis
determines how well each assemblage fits within its assigned evolu-
tionary group/cluster, with higher values indicating that the site is
closer compositionally to the “median” composition (i.e., centroid)
of its assigned group relative to its proximity to the “median” com-
position of the other groups. The higher the average silhouette width
across all assemblages, the better the clustering. The Elbow analyses
suggest anything from K=3 to K=5 to be the best clustering, and
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the Silhouette width analysis point to K=2 to be the best clustering.
On the basis of these results, we selected K=2 (Fig.1), K= 3 (fig.
S4), K=4 (Fig.2), and K=5 (fig. S5) for further analysis and inter-
pretation. No geographic or environmental data were used to in-
form the clustering analyses (48). The K-means clustering was carried
out with the kmeans() function in base R (R Core Development
Team, 2016).
In addition, we performed an evolutionary ordination of tree as-
semblages based on their phylogenetic lineage composition, following
protocols developed by Pavoine (49). We specifically used an evolu-
tionary principal components analysis, implemented with the evopca()
function in the “adiv” package (49), with a Hellinger transformation
of the genus by site matrix, as this is a powerful approach to detect
phylogenetic patterns along gradients, while also allowing positioning
of sites and clades in an ordination space (11). The first two axes ex-
plained 9.6 and 6.7% of the variation in the data, with subsequent
axes each explaining <5.5%.
Correspondence between clustering results
and environmental variables
We tested the correlation between our K= 2 clustering result and
eight different delimitations of the tropics, as per Feeley and Stroud
(50). These delimitations were as follows: (C1) all areas between 23.4°S
and 23.4°N; (C2) all areas with a net positive energy balance; (C3)
all areas where MAT does not co-vary with latitude; (C4) all areas
where temperatures do not go below freezing in a typical year; (C5) all
areas where the mean monthly temperature is never less than 18°C;
(C6) all areas where the mean annual “biotemperature”≥24°C; (C7)
all areas where the annual range of temperature is less than the average
daily temperature range; and (C8) all areas where precipitation sea-
sonality exceeds TS. We calculated the correspondence between our
binary clustering (i.e., tropical versus extratropical) and each of these
delimitations as the proportion of sites where the delimitations matched.
To assess whether the K= 4 clustering is mainly influenced by
climate or by geography, we determined the proportion of assem-
blages that can be correctly categorized into their evolutionary group
by environmental variables versus spatial variables, using a random
forest classification tree approach (13). The explanatory variables
for the environmental model were MAT, MAP, and TS from the
Worldclim dataset (51) and maximum CWD from Chave etal. (52).
For the geographic model, we used a basic division between South
America versus North and Central America together, as this reflects
the historic geographic isolation of South America. We also included
latitude and longitude as explanatory variables in this basic geographic
model. We excluded sites in the Caribbean from both models as it
was not certain how to group them in the geographic model. Even
including them would not have changed the results substantially as
they only comprise 2.4% of sites in our total assemblage database.
These analyses were implemented with the randomForest() function in
the “randomForest” package (13).
To explore the best climatic variable to explain the divisions be-
tween groups within the tropics and the extratropics, we used a mixed
model with a binomial response (tropical dry versus tropical moist
for the tropics and extratropical north versus extratropical south for
the extratropics). To account for spatial autocorrelation, we grouped
assemblages in 1° × 1° grid cells and incorporated the many-level grid
cell factor as a random effect. We implemented the mixed model with
the function glmer() from the lme4 package (53). To determine the best
climatic variable, we compared the models based on the Akaike in-
formation criterion (AIC). As candidate variables, we focused on
the same variables as in the random forest analysis, MAT, MAP, TS,
and CWD.
Shared versus unique PD
As the Phylosor estimation of evolutionary (dis)similarity cannot
distinguish variation associated to differences in total PD, or phy-
logenetic richness, versus variation associated to phylogenetic turn-
over per se, we measured the shared and unique PD associated with
each group for the K=2, K=3, and K=4 clustering analyses. First,
we estimated the association of genera with each group by an indi-
cator species analysis following de Caceres etal. (54). Specifically,
we used the multipatt() function in the R Package indicspecies (55)
to allow genera to be associated with more than one group (when
K>2). The output of the multipatt function includes the stat index,
which is a function of the specificity (the probability that a surveyed
site belongs to the target site group given the fact that the genus has
been found) and fidelity (the probability of finding the genus in sites
belonging to the given site group). We constructed pruned phylog-
enies excluding those genera with specificity greater than 0.6 for a
group, or combination of groups, to estimate the total PD found in
each group or combination of groups without their specific indicators.
Then, we subtracted these totals from the entire total for the com-
plete, unpruned phylogeny to determine the amount of phylogenetic
diversity restricted to each group or combination of groups. Last, we
estimated the PD shared across all groups as that which was not
restricted to any particular group or any combination of groups.
We fit these different PD totals as areas in a Euler diagram with the
euler() function in the “eulerr” package (56) for the K=2 and K=3
clustering and with the Venn() fuction in the “venn” package (57)
for the K=4 clustering.
Indicator lineages for clusters
To further characterize the composition of the evolutionary groups,
we conducted an indicator analysis to determine the evolutionary
clades most strongly associated with each group. We created a site ×
node matrix, which consists of a presence/absence matrix for each
internal node in the phylogeny and ran an indicator analysis for the
nodes. We selected the highest-level, independent (i.e., non-nested)
nodes with the highest stat values to present in tables S1 and S2. The
indicator node analysis was carried out with function multipatt() in
the R Package indicspecies (55).
SUPPLEMENTARY MATERIALS
Supplementary material for this article is available at http://advances.sciencemag.org/cgi/
content/full/6/19/eaaz5373/DC1
View/request a protocol for this paper from Bio-protocol.
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Acknowledgments: We thank E. Manson, D. Coenen, and C. Pertusi for help in the mining of
genetic sequences from GenBank. Funding: CONICYT PIA APOYO CCTE AFB170008 and a
Leverhulme Trust Research Fellowship RF-2015-653. R.A.S. was supported by a Newton
International Fellowship from The Royal Society and by Conicyt PFCHA/Postdoctorado Becas
Chile/2017 No. 3140189; K.G.D. and T.R.B. were both supported by Leverhulme International
Academic Fellowships. R.T.P., T.R.B., K.G.D., and D.M.N. were supported by NERC Grant NE/
I028122/1. Author contributions: R.A.S. and K.G.D. designed the study and carried out the
analyses. R.A.S., K.G.D., F.C.d.S., and D.M.N. built the phylogeny. A.T.O.-F. compiled the NTT
dataset. R.A.S., K.G.D., and R.T.P. wrote the manuscript with input from all the coauthors.
Competing interests: The authors declare that they have no competing interests. Data and
materials availability: All data needed to evaluate the conclusions in the paper are present in
the paper and/or the Supplementary Materials. Additional data related to this paper may be
requested from the authors.
Submitted 17 September 2019
Accepted 19 February 2020
Published 6 May 2020
10.1126/sciadv.aaz5373
Citation: R. A. Segovia, R. T. Pennington, T. R. Baker, F. Coelho de Souza, D. M. Neves, C. C. Davis,
J. J. Armesto, A. T. Olivera-Filho, K. G. Dexter, Freezing and water availability structure the
evolutionary diversity of trees across the Americas. Sci. Adv. 6, eaaz5373 (2020).
on May 6, 2020http://advances.sciencemag.org/Downloaded from
Americas
Freezing and water availability structure the evolutionary diversity of trees across the
J. Armesto, Ary T. Olivera-Filho and Kyle G. Dexter
Ricardo A. Segovia, R. Toby Pennington, Tim R. Baker, Fernanda Coelho de Souza, Danilo M. Neves, Charles C. Davis, Juan
DOI: 10.1126/sciadv.aaz5373
(19), eaaz5373.6Sci Adv
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