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Article type: Original Article

Geographic variation in the evolutionary diversity of tree communities

across southern South America

Vanessa L Rezende1,2; Kyle G. Dexter2,3; R. Toby Pennington2; Ary T Oliveira-Filho1

1Department of Plant Biology, University of Minas Gerais. Belo Horizonte, MG 31270-901, Brazil.

2Royal Botanic Garden Edinburgh, Edinburgh EH3 5LR, UK. 3School of GeoSciences, University of Edinburgh, Edinburgh EH9 3FF, UK.

Correspondence author: Vanessa Leite Rezende, University of Minas Gerais, Belo Horizonte, MG 31270-901,

Brazil. Email: vanessa.leite.rezende@gmail.com

Running head: Phylogenetic patterns across southern South America

Word count: 6,960

Journal pages for figures and table: 5

ABSTRACT

Aim: To determine the principal drivers of variation in the evolutionary diversity of forest tree

communities, with a focus on the temperate forests of South America.

Location: Forests across southern South America, extending from tropical forests in southern Brazil, to

the temperate forests of southern Chile and Argentina.

Methods: We compiled a database of 742 forest tree community inventories spread over six countries

and 12 biomes, or major vegetation types. In total, these inventories covered 3075 species of shrubs and

trees. We combined this dataset with a temporally calibrated phylogeny that included all species. For

each community we evaluated multiple measures of evolutionary diversity, including phylogenetic

diversity sensu stricto (PD), which is the sum of the branch lengths of a phylogeny that includes all

species in a community, and its equivalent standardised for variation in species richness (ses.PD), which

we refer to as lineage diversity.

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Results: We found that biome affiliation is the most important determinant of the evolutionary diversity

of woody plant communities, with climate also showing a significant influence. Communities in wet

evergreen tropical forest have the highest species richness and the highest PD, but the lowest lineage

diversity, while temperate forests in southern South America show the lowest species richness and PD,

but the highest lineage diversity.

Main conclusions: Our results contradict the idea that temperate floras represent recently derived,

evolutionarily poor subsets of tropical floras. Rather, the high lineage diversity we find in temperate

forest communities supports the Austral Conservatism Hypothesis, which states that the flora of

southern South America has evolved independently from the Neotropical Domain over tens of millions

of years. Our identification of the evolutionary distinctness and richness of this flora suggests that it

deserves as much conservation attention as the more species-rich tropical forests of South America and

that southern South American forests should not be lumped into the Neotropical Floristic Province.

Key words: Temperate Forest, Tropical Forest, Biome, Phylogenetic Diversity, Lineage Diversity,

Tropical Conservatism Hypothesis, Austral Conservatism Hypothesis, Latitudinal Gradients, Species

Richness.

INTRODUCTION

The tropical conservatism hypothesis (TCH, Wiens&Donoghue, 2004) has been proposed to

underlie the present-day latitudinal diversity gradient, the pattern whereby species richness is currently

highest in equatorial regions and declines towards the poles. It suggests that species distribution patterns

at global scales, particularly for plants, are largely governed by evolutionarily conserved ancestral

preferences (Wiens & Graham, 2005; Kozak & Wiens, 2010; Romdal et al., 2013). It assumes that most

clades originated in tropical conditions that were widespread from the beginning of the Cretaceous to the

end of the Eocene (Davies et al., 2004; Ruddiman, 2006), and that most species in these clades have at

least partly retained their ancestral physiological tolerances (Ricklefs & Schluter, 1993; Wiens &

Donoghue 2004; Wiens et al., 2010; Jansson et al., 2013). An important component of this hypothesis is

the inability of many lineages to adapt to freezing environments (Condamine et al., 2012), limiting

dispersal and evolution from tropical to temperate regions (Crispet al., 2009). Thus, according to the

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TCH, species richness, evolutionary diversity and lineage age will be high in regions characterized by

warm, non-freezing temperatures, because these conditions match the ancestral niches of many extant

clades, while temperate regions will be occupied by fewer, younger and less diverse clades, because the

transitions to cold, temperate environments have been relatively infrequent and recent (Wiens &

Donoghue 2004).

In support of the TCH, two recent studies have shown that the mean age of angiosperm families

declines away from the equator (Hawkins et al., 2011; Romdal et al., 2013). Focusing on the New

World, Kerkhoff et al. (2014) used a different approach to test the TCH, which consisted of examining

the evolutionary diversity of latitudinal bands (estimated using various metrics of phylogenetic

diversity). Their results supported the TCH in finding that latitudinal bands further away from the

equator have less lineage diversity. In contrast, Boucher-Lalonde et al. (2015) found that once positive

relationships between species richness and current climate are taken into account, the temperature, and

presumably latitude, at which a clade originates has little influence on its species richness, which the

authors take as evidence against the TCH. Other studies have also found results that are contradictory to

patterns expected under the TCH, both at a global scale (Jansson et al., 2013) and in South America

(Segovia et al., 2013; Qian, 2014; Tiede et al., 2016). However, most previous studies have largely

focused on the northern hemisphere when interpreting results (Segovia & Armesto, 2015). Furthermore,

the patterns used to argue for the TCH, for example a decline in family age and evolutionary diversity

away from the equator, are not particularly evident in the southern hemisphere , at least for woody

angiosperm families (see Fig. 4b in Hawkins et al., 2011, and Fig. 1a in Kerkhoff et al., 2014). Here, we

aim to test the TCH in the southern hemisphere, by examining evolutionary diversity in woody plant

communities across southern South America, where support for the TCH has been mixed and uncertain.

The present-day South American flora has complex origins (Pennington & Dick, 2004) and

includes a group of lineages with southern temperate affinities, which have been suggested to have

evolved during and after the breakup of Gondwana, and a group of Neotropical elements which are

largely found in northern South America (Romero, 1986; Villagran & Hinojosa, 1997; Eisenlohr &

Oliveira-filho, 2015). Based on this, Segovia & Armesto (2015) proposed the idea of the Austral

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Conservatism Hypothesis (ACH), that the floras of temperate South America are not simply an

evolutionarily poor subset of tropical clades, but contain many lineages that have diversified outside of

the tropics and retained their ancestral preference for temperate conditions. In order to support the ACH,

Segovia & Armesto (2015) reviewed data showing that the mean age of angiosperm families increases

with altitude and as one moves southward in South America. However, Boucher-Lalonde et al. (2015)

have shown that analyses of mean family ages may be insufficient to test hypotheses around niche

conservatism. As an alternative, studies of the evolutionary diversity of ecological communities can be

used to test the potential role for niche conservatism in determining spatial patterns of biodiversity (c.f.

Kerkhoff et al., 2014) and to distinguish the relative merit of the TCH and the ACH in shaping the South

American flora.

Many metrics have been developed to measure the evolutionary diversity of communities, with

most quantitative metrics being derived from phylogenies (Cadotte et al., 2010). The most basic metric

is to sum the branch lengths of a phylogeny that covers all species in a given community, which we refer

to as phylogenetic diversity sensu stricto (PD). In most empirical datasets, PD is strongly positively

correlated with species richness (SR) (e.g. Forest et al., 2007, Honorio-Coronado et al., 2015). As

species richness is strongly influenced by current climate (Kreft & Jetz, 2007, Boucher-Lalonde et al.,

2015), it is often of interest to assess whether communities show more or less PD than expected given

their SR. One particularly common metric to measure this departure from expectation is the standardised

effect size of PD (ses.PD), which we refer to as lineage diversity (sensu Honorio-Coronado et al., 2015).

Here, in our analyses of the evolutionary diversity of forest tree communities across southern South

America, we focus on measuring phylogenetic diversity sensu stricto and lineage diversity as well as

other commonly employed metrics of phylogenetic diversity.

Most prior studies have used data from herbarium collections, which have many sources of

potential bias when it comes to estimating SR or other metrics of diversity, particularly those that are

strongly correlated with species richness, e.g. PD (Droissart et al., 2012). Previous large-scale studies in

South America have therefore often been restricted to estimating SR, PD or lineage diversity for large

latitudinal bins (e.g. Romdal et al., 2013; Kerkhof et al., 2014), rather than for local communities. By

not analysing local communities, these studies have been unable to adequately assess the potential

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influence of environmental factors on SR, PD or lineage diversity (c.f. Boucher-Lalonde et al., 2015).

Those studies that have taken a community approach have had sparse sampling across the southern

hemisphere, particularly in South America (e.g. Kreft & Jetz, 2007; Qian, 2014).

Previous large-scale studies of latitudinal diversity patterns in plants have also focused largely

on angiosperms (e.g. Hawkins et al., 2011, Kerkhoff et al., 2014).Although angiosperms dominate the

majority of terrestrial ecosystems (Lidgard & Crane, 1988; Willis & McElwain, 2002; Crisp & Cook,

2011), in some forests, mainly located at high latitudes or altitudes, gymnosperms dominate (Aerts,

1995; Augusto et al., 2014). Likewise, tree ferns can be another important component of tree

communities, particularly in tropical, wet forests (Smale et al., 1997; Chacón-Labellaet al., 2014). Thus,

to have a comprehensive understanding of PD and lineage diversity in tree communities, it is critical to

include gymnosperm and tree fern lineages, which, being early diverging lineages, may have a large

impact on phylogenetic diversity metrics.

Finally, none of these previous studies in South America have incorporated biome identity into

analyses, which is potentially important as different biomes may have different biogeographic histories

and show different patterns of variation in species richness or phylogenetic diversity (Pennington et al.,

2009; Hughes et al., 2013). For example, the Neotropical seasonally dry tropical forest (SDTF) biome

may not even show the typical latitudinal diversity gradient. Rather, the opposite may hold, as species

richness seems to increase away from the equator (Gentry, 1995; DRYFLOR, 2016).

In this study, we examine spatial patterns of species richness and evolutionary diversity across

the 12 principal woody biomes of southern South America and across a large latitudinal gradient from

15°S to 54°S. We take a community approach, based on 742 species inventories of forest tree

communities, and combine this with a phylogenetic hypothesis for all non-climbing woody plants in

these communities, including gymnosperms and tree ferns. We assess how SR, PD and lineage diversity

vary across climatic environments and biomes. If a tropical origin and phylogenetic conservatism for

tropical environments were the dominant forces shaping large-scale patterns, we would expect tropical

biomes to show higher lineage diversity. Conversely, if the austral conservatism hypothesis holds, then

we should expect comparable or even higher lineage diversity in temperate biomes compared to tropical

ones.

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MATERIALS AND METHODS

Study Area

Our study area spans portions of six countries, Paraguay, Chile, Argentina, Uruguay, Brazil and

Bolivia (Fig. 1), with a latitudinal range from 15° 32’ S to 54° 50’ S and a longitudinal range from 41°

02’ W to 78° 50’ W. We focused on sampling the 12 major forest types, or biomes, in temperate South

America and adjacent subtropical and tropical regions. The biomes were defined following the

classification proposed by Rezende et al. (2016) and comprise: (1) Seasonally Dry Tropical Forest, with

>60% leaf deciduousness in the dry season; (2) Tropical Semideciduous Forest, characterized by 30-

60% leaf deciduousness in the dry season; (3) Wet Evergreen Tropical Forest, with <30% leaf

deciduousness, generally hot and wet climates and associated with the Atlantic coast; (4) Subtropical

Semideciduous Forest, which is similar to Tropical Semideduous, but experiences frost; (5) Araucaria

Mixed Forest, which is similar to Wet Evergreen Tropical Forest, but cooler and characterized by the

presence of Araucaria angustifolia (Araucariaceae); (6) Cloud Dwarf-forest, characteristic of high

altitude areas (above 1500m) with a low canopy (between 3 and 5m in height) and frequent cloud

immersion; (7) Southern Andean Forest, which occurs along the eastern foothills of the Andes in

northern Argentina and southern Bolivia and includes communities variously designated as Tucumano-

Boliviano, Yungas and Chaco Serrano; (8) Gran Chaco, a dry biome which experiences frost and which

encompasses the dry and wet Chaco; (9) Western Pampa Forest, consisting of deciduous or

semideciduous forest with a seasonally cold climatic regime and found along rivers; (10) Eastern Pampa

Forest, which is similar to Western Pampa Forest, but experiences a more maritime climatic regime and

is not specifically associated with rivers; (11) Semi-Arid and Arid Patagonian Forest, which consists of

the Patagonian Temperate Steppe, the Monte Subtropical Semi-deserts and the Espinal region; and (12)

Pacific Forest, that encompasses Mediterranean Chile and Temperate Pacific forests. We combined

these latter two as one biome due to their high floristic similarity to each other relative to other biomes

and the low number of sampling sites in Mediterranean Chilean forests (see Fig. 4 in Rezende et al.,

2016).

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Database

We obtained floristic data from the NeoTropTree database (Oliveira-Filho, 2015), which is a

compilation of tree species checklists gathered from the literature with additional occurrence records

obtained from verified herbarium specimens. At present, NeoTropTree contains information on the

composition of tree species for >5,000 georeferenced locations spread across South America. Each site

comprises a 5-km radius circle and contains records of tree species that can be found within this area. In

addition to the presence and absence data on tree species, each site contains descriptive and

environmental data such as biome, altitude, geo-edaphic and climatic variables (see description, history

and NeoTropTree protocol at http://www.icb.ufmg.br/treeatlan). NeoTropTree defines trees as

freestanding plants with stems that can reach over 3m in height. Thus, the NeoTropTree database

includes, for example, palms, tree ferns and bamboos, when they fit the inclusion criteria.

Analysis of Phylogenetic Diversity

We generated an ultrametric, temporally calibrated phylogeny for all genera in the dataset, using

Phylocom (ver 4.2), starting with the following reference tree: R20120829.new (from

http://phylodiversity.net/phylomatic/). We incorporated gymnosperms and tree ferns into this starting

tree based on relationships in Lu et al. (2014) and Quiroga et al. (2015) for gymnosperms and Silvestro

et al. (2015) for tree ferns. All taxa (i.e. species) are first assigned to the clade to which they belong

taxonomically. To temporally calibrate this phylogeny, we assigned fixed ages to 125 of the 820 nodes

in the phylogeny and used the bladj algorithm to constrain the remaining node ages (n= 695). This

algorithm spaces the remaining nodes evenly in time between the nodes with fixed ages, based on their

hierarchical position with respect to each other. We began with a set of ages from Gastauer & Meira-

Neto (2013), and manually modified clade ages based on Magallón et al. (2015) for angiosperms,

Quiroga et al. (2015) and Silvestro et al. (2015) for gymnosperms and Lu et al. (2014) for tree ferns.

For each floristic list, or tree community, in the dataset, we calculated a series of phylogenetic

diversity metrics (sensu Honorio-Coronado et al., 2015): phylogenetic diversity sensu stricto (PD),

which is the total sum of branch lengths in a phylogeny comprising species in the community; the mean

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pairwise phylogenetic distance between species in the community (MPD); the mean nearest taxon

distance (MNTD), which is the mean phylogenetic distance from each taxon to its closest relative in the

community; and their equivalents, standardized for species richness (ses.PD, ses.MPD, ses.MNTD). The

standardizations were accomplished by randomly drawing the same number of species from the

phylogeny as present in the community, repeating this 999 times, calculating PD, MPD and MNTD for

each randomization, taking the difference between the observed value and the mean of the random

values, and dividing this difference by the standard deviation of values across the randomizations.

We constructed linear models, using a generalized least squares (GLS) approach to account for

spatial autocorrelation, to test the relationship between the phylogenetic metrics and our explanatory

variables. The NeoTropTree database contains climatic data for each site, including the 19 BIOCLIM

variables (Hijmans et al., 2005) and measures of water deficit duration and severity, potential

evapotranspiration (PET), seasonality in water availability(sum of duration of the excess and water

deficit periods), aridity, days of frost and cloud interception (see Neves et al., 2015 for details). We

assessed correlations amongst these climatic variables, and for each statistical model, we included the

uncorrelated variables that had the most explanatory power. Preliminary analyses indicated that latitude

and longitude showed strong relationships with diversity metrics, and we therefore also included these

variables as proxies for climatic variation that may not have been captured by the measured climatic

variables. We ensured that all variance inflation factors (VIFs) were less than five for each explanatory

variable (Quinn & Keough, 2002). We included biome as a separate explanatory variable. Biome

covaries with climate, but we were interested in testing the role of biome alone and to assess if biomes

have explanatory power beyond the climate with which they are associated (and vice versa). Our GLS

approach allowed us to account for spatial autocorrelation when testing the relative influence of biome

versus climate on different diversity metrics. In preliminary analyses, we found an exponential spatial

autocorrelation structure to best fit the data, and we therefore used this structure when generating all

models. Models of the full set of explanatory variables (best climate variables + biome) were compared

to nested subsets where climate or biome were excluded. We used the Akaike Information Criterion

(AIC) to compare models. Lastly, for comparison with previous studies and to explore latitudinal

gradients, we visually explored how species richness and phylogenetic diversity metrics vary with

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latitude within and across biomes. We also conducted a principal component analysis to visualize the

relationships amongst climatic variables and with latitude (Fig. 2). All analyses were conducted in the R

Statistical Environment (R Core Working Team, 2015) using the picante (Kembel et al., 2016), vegan

(Oksanen et al., 2016), car (Fox et al., 2016) and nlme (Pinheiro et al., 2016) packages.

RESULTS

In the database, 98.87% of species are angiosperms, 0.69% are gymnosperms and 0.50% are

tree ferns. On average, the biome with the lowest proportion of angiosperms is the Pacific Forest, where

a mean of 92.73% of species per site belong to angiosperms, while the biome with the highest

proportion of angiosperms is the Wet Evergreen Tropical Forest, with a mean of 98.46% species per site

belong to angiosperms per plot (Table 1). When analysing species richness (SR), Wet Evergreen

Tropical Forest has the highest SR, with an average of 323 species per site, whereas the lowest SR was

found in the Pacific Forest (29 species per community; Table 1).

Across all sites, we found phylogenetic diversity sensu stricto (PD) to be strongly correlated

with SR, while the standardised measure of PD (ses.PD), termed lineage diversity, was positively

correlated with mean nearest taxon distance (MNTD) and its standardised equivalent (ses.MNTD) (Fig.

2; see Appendix S1 in Supporting Information). Mean pairwise distance (MPD) and its standardised

equivalent (ses.MPD) are strongly correlated with each other (Fig. 3). MPD and ses.MPD are strongly

influenced by branch lengths at the deepest nodes of the phylogeny, and as a result, these metrics are

often strongly driven by how evenly taxa are divided among major clades (Swenson, 2014). This is the

case in our dataset, where we found that the overwhelming influence on MPD and ses.MPD values was

how evenly taxa are divided amongst tree ferns, gymnosperms and angiosperms, and secondarily

amongst the three major clades of angiosperms: magnoliids, monocots and eudicots. The evenness with

which species in communities are divided amongst these clades explains 96% and 85% of the variation

in MPD and ses.MPD values respectively (see Appendix S2). Thus, following Honorio Coronado et al.

(2015), we focus our results and discussion on PD, lineage diversity, MNTD and ses.MNTD.

We observe similar patterns for PD as we found for SR, where the highest value was found for

communities in Wet Evergreen Tropical Forest (17820.43), while the lowest values were found for

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communities in Semi-Arid and Arid Patagonian Forest (2684.408) and the Pacific Forest (3058.268; see

Appendix S3; Fig. 3). MNTD showed an opposite result to that found for PD and SR. The highest value

was found for the Pacific Forest communities (154.2256), while the Wet Evergreen Tropical Forest had

the lowest value (90.27885). For the standardized metrics (ses.PD and ses.MNTD), the highest values

were also found in the Temperate Pacific Forest communities (0.975112 and -0.21606 respectively).

The best models for all metrics were the full models, including biome and climatic variables

(Table 2). Interestingly though, for all metrics except MNTD, the pure biome model explained the data

better than a model with just climatic data. The best climatic model for PD included the same climatic

variables as the model for SR, which is unsurprising given how tightly correlated it is with SR (see Fig.

S1; Table 2). For the standardised metrics, ses.PD and ses.MNTD, adding the climatic data increased

model performance less than it did for the raw diversity metrics. The high importance found for

temperature-related variables, such as days of frost, relative to precipitation-related variables

corroborates other studies in the extratropical portion of southern South America (Rezende et al., 2015;

Oliveira-Filho et al., 2013; Gonçalves & Souza, 2014).

We then visualized how these different phylogenetic diversity metrics vary with latitude (Fig.3).

As ses.PD and ses.MNTD are strongly correlated (r= 0.844, p<0.001) and thus show similar patterns, the

results for ses.MNTD are not shown. The direction of trends with latitude were similar across biomes,

with a few exceptions. In Cloud Forest and Tropical Semideciduous Forest, ses.PD increased towards

the equator. In all other biomes, ses.PD values increased away from the equator in a southerly direction.

DISCUSSION

In agreement with previous studies (Hawkins, 2001; Turner, 2004; Oliveira-Filho et al., 2013),

we found that the species richness (SR) of tree communities in the southern hemisphere declines as one

moves southwards, away from the equator (Fig. 3A). Similarly, phylogenetic diversity, measured as the

total sum of phylogenetic branch lengths in a community (PD), declines away from the equator (Fig.

3B), which is expected given the tight correlation of SR and PD (see Fig. S1). In contrast, once we

control for the effect of species richness on PD and evaluate phylogenetic, or lineage, diversity in

communities using a standardized metric (ses.PD), we found that lineage diversity increases as one

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moves away from the equator (Fig. 3D). Thus temperate tree communities of southern South America

show greater lineage diversity than expected given their species richness. We found similar results in

analyses restricted to angiosperms (see Appendix S3), which indicates that this result is not due solely to

the increased frequency of gymnosperms in these far southern communities. Rather, in general, the tree

species in these southern communities, both angiosperms and gymnosperms, tend to come from older

lineages (see also Segovia et al., 2013). Overall, our results provide strong support for the Austral

Conservatism Hypothesis (ACH). Our results do not support the idea that southern hemisphere

temperate floras are recently derived, evolutionarily poor subsets of tropical floras, which is an

implication of the Tropical Conservatism Hypothesis (TCH) as it is often interpreted (e.g. Kerkhoff et

al., 2014).

In our analyses, biome was the variable that best explained variation in the phylogenetic

diversity metrics. However, climate is a major factor determining the distribution of terrestrial biomes

(Whittaker, 1975, Lyra et al., 2016), which could suggest that climate is in fact the major driver of

variation in phylogenetic diversity, not biomes per se. Climatic gradients and energetic constraints are

often invoked to explain variation in species richness, with which phylogenetic diversity sensu stricto is

strongly correlated. However, we found higher lineage diversity in colder places, while a hypothesis

based on energetic constraints would predict higher lineage diversity in warmer places. Therefore, we

suggest that the high lineage diversity values found in southern, temperate communities reflects

accumulated lineage diversity, with many deep phylogenetic branches for communities in these southern

biomes, relative to their species richness (Swenson, 2009). Kerkhoff et al. (2014) noted an increase in

lineage diversity from subtropical areas to the poles, but they related this to latitudinal extent patterns,

stating that temperate and boreal areas occupy a larger area than subtropical areas. While this may be the

case in the northern hemisphere, it cannot be an explanation for South America, where tropical and sub-

tropical biomes occupy a much larger area than temperate biomes, and a boreal zone is lacking.

One reason for higher lineage diversity in temperate regions is that close relatives in temperate

forest communities diverged longer ago than close relatives in tropical forest communities, which is

indicated by the higher mean nearest taxon distance (MNTD) values in more southern, colder areas (Fig.

3C). This result may be because the temperate flora has high richness at the family level with low

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generic and species richness, as well as a high proportion of monotypic genera, with several of these

genera even representing monogeneric families (e.g., Aextoxicaceae, Gomortegaceae, Desfontainiaceae

and Eucryphiaceae; Vilagran & Hinojosa, 1997). Whilst family richness in the tropical biomes is high,

there is also high richness at the genus and species levels.

Variation in diversification rates across biomes could contribute to the observed variation in

evolutionary diversity metrics. Our finding of lower lineage diversity in present-day tropical tree

communities could be due to higher recent diversification rates in the tropics, which could be caused in

turn by higher recent speciation rates in tropical regions relative to temperate regions or higher recent

extinction rates in temperate regions relative to tropical regions. For example, among conifers, total

diversity was higher in South America in the Eocene, with a number of lineages present that are now

restricted to Australasia (Agathis, Papuacedrus, Dacrycarpus) (Wilf et al., 2009; Wilf, 2012; Wilf et al.,

2014), and their extinction may be affecting lineage diversity estimates. However, as with most

phylogenies derived using the Phylocom software (Webb et al., 2008), our phylogeny lacks resolution

amongst species within genera and often lacks resolution amongst genera within families, which

prevents us from being able to use it to estimate diversification, speciation or extinction rates. In

addition, our community surveys do not contain all species in the clades we are sampling and thus our

phylogeny, even if fully resolved, would have real missing data issues when it comes to estimating these

rates. Meanwhile, some recent studies have shown exceptional diversification rates in temperate plant

clades (e.g. Valente et al., 2010), although comparative studies across latitudes have tended to show

higher diversification rates in plants at tropical latitudes (Jansson & Davies, 2008; Svenning et al.,

2008). Diversification and age estimates derived from molecular phylogenies must be interpreted with

caution however, as rates of genetic substitution also vary with latitude (Gillman & Wright, 2014). In

any case, there have been no synthetic studies of diversification rates for tree clades of southern South

America to allow us to assess the importance of variation in diversification rates to the observed

patterns. Instead, we have shown how a community phylogenetic approach can be used to try and

understand variation in the evolutionary diversity of tree communities.

The results for the phylogenetic diversity metrics we evaluated in tree communities are

explicable by the biogeographic history of the flora of southern South America. Overall, our findings

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show that the floras of South America’s extratropical biomes are not a narrow, cold-adapted subset of

that of tropical regions, but, as suggested by Segovia & Armesto (2015), they also include diverse

lineages that have a temperature southern hemisphere origin and a history of diversification outside of

the tropics. Southern South American floras comprise considerable numbers of southern temperate

genera such as Nothofagus (~80ma), Podocarpus (~63ma), Aextoxicon, Gomortega (~78ma), Pitavia,

Legrandia, Laureliopsis, Laurelia, Citronella, Cryptocarya, Persea and Drimys that give this vegetation

a markedly different floristic composition from the rest of South America (Zuloaga et al., 2008). There

are also numerous families that are rare in the tropics but much more abundant in southern temperate

latitudes (e.g. Proteaceae, Casuarinaceae, Cunoniaceae, Atherospermataceae and Akaniaceae). Another

conspicuous aspect of these southern floras is the absence of major Neotropical clades (e.g. Meliaceae,

Anacardiaceae, Sapotaceae, Moraceae and Annonaceae). The Pacific forests in this study which show

particularly high lineage diversity are currently isolated from other forests in South America by the

Andes. However, the lineages that are contributing to this lineage diversity predate the rise of the Andes.

Furthermore, other studies beyond South America (Kooyman et al., 2012; Kooyman et al., 2014; Lee et

al., 2016) suggest that high lineage diversity may be a phenomenon common to temperate forests of the

southern hemisphere, e.g.. in Australia and New Zealand, although the exact lineage composition may

differ across continents and islands (Lee et al., 2016). In the northern hemisphere lineage diversity

patterns may differ from those we found in South America; for example, Qian & Ricklefs (2016) found

that in North America, temperate plant communities seem to have been assembled from tropical lowland

floras.

Our results suggest that the distinctive ecology and biogeographical history of each biome could

be a key to understanding the distribution of tree species in southern South America. We have shown

that the forests of southern temperate biomes in South America have a unique and diverse evolutionary

history, which has important implications for biological conservation and in delimiting major floristic

provinces. All of South America is usually included in the Neotropical floristic province (Cox et al.,

2001), but clearly the temperate forests of southern South America should be regarded as distinct. In

terms of conservation, it is imperative to preserve the temperate forests of South America, as well as

tropical forests, given their unexpectedly high and exceptional lineage diversity. Should these temperate

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forests be lost, we stand to lose a significant amount of evolutionary history that is not found anywhere

else in South America and perhaps in the world.

ACKNOWLEDGEMENTS

VLR thanks CNPq for supporting a 9-month study period at the Royal Botanic Garden Edinburgh (grant

SWE- 205162/2014-2) and CAPES for the PHD scholarship in UFMG. VLR also thanks the Royal

Botanic Garden Edinburgh for support during the time this research was conducted.

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SUPPORTING INFORMATION

Additional Supporting Information may be found in the online version of this article:

Appendix S1 Pairwise correlations between species richness and all phylogenetic diversity metrics.

Appendix S2 MPD and ses.MPD correlations with lineage composition.

Appendix S3 Phylogenetic results for angiosperm.

BIOSKETCH

Vanessa L Rezende is a Brazilian Research Fellow at the University of Minas Gerais, Brazil. She is

interested in subtropical ecology and evolutionary biology of plants, with an emphasis on niche

evolution of southern South America.

Author contributions: V.L.R., K.G.D., R.T.P. and A.O.F. designed the paper; V.L.R., A.O.F. and K.G.D.

assembled the database; V.L.R. and K.G.D. analysed the data; V.L.R., K.G.D., R.T.P. and A.O.F. led

the writing. All authors read and approved the final manuscript.

TABLES

Table 1. Sampling and community composition across biomes, showing proportional representation of

major clades and values of species richness (SR)

Biome No. of

sites

Mean (and

range) for no. of

species per site

Mean(and range)

for no. of

angiosperm

species per site

Mean(and

range) for no. of

gymnosperm

species per site

Mean(and

range) for no. of

tree fern species

per site

Tropical

Semid.* Forest

155 201 (38 – 507) 199 (38-505) 0 2 (0-8)

Seasonally Dry 74 96 (59 – 141) 96 (59-141) 0 0

562

563

564

565

566

567

568

569

570

571

572

573

574

575

576

577

578

23

Tropical Forest

Wet Evergreen

Tropical Forest

95 323 (49 – 746) 318 (49-736) 1 (0-2) 4 (0-12)

Cloud Forest 20 233 (79 – 376) 225 (74-365) 2 (0-3) 6 (0-11)

Subtropical

Semid.* Forest

41 179 (60 – 343) 178 (60-343) 0 1 (0-4)

Araucaria

Mixed Forest

43 210 (102 – 408) 204 (99-399) 2 (0-3) 3 (1-6)

Southern

Andean Forest

37 106 (36 – 226) 104 (36-223) 1 (0-3) 1 (0-4)

Gran Chaco 81 53 (21 – 236) 53 (21-236) 0 0

Western Pampa

Forest

68 75 (23 – 197) 75 (23-196) 0 0

Eastern Pampa

Forest

63 84 (20 – 194) 83 (20-192) 0.3 (0-2) 0.8 (0-4)

Semi-Arid and

Arid Patagonian

Forest

15 34 (9 – 64) 34 (9-64) 0 0

Pacific Forest 50 30 (10 – 46) 28 (10-43) 2 (0-5) 0

*Semid. = Semideciduous

Table 2. delta AIC values for different models to explain variation in species richness and phylogenetic

diversity metrics. All delta AIC values are scaled with respect to the best model for a given metric.

Potential.ET: Potential Evapotranspiration; PrecWetP: Precipitation of wettest month; PrecAnn: Annual

precipitation; TempSeas: Temperature seasonality; TempAnn: Annual mean temperature. TempMin:

Minimum Temperature of coldest month; Isotherm: Isothermality; DaysFrost: Days of frost.

Metrics SR PD MNTD ses.PD ses.MNTD

Biome and Climate 0 0 0 0 0

579

580

581

582

583

584

585

24

Just Biome, no Climate -189 -188 -115 -18 -21

Just Climate, no Biome -218 -262 -83 -107 -93

Climatic variables included TempMin/

Isotherm/

TempSeas/

PrecAnn

TempMin/

Isotherm/

TempSeas/

PrecAnn

TempMin/

TempSeas

DaysFrost TempAnn/

PrecWetP/

PET

LIST OF FIGURE LEGENDS

Figure 1. Tree communities extracted from the NeotropTree database and used in this study. The

symbols correspond to the biomes. Each tree community represents an inventory of non-climbing woody

plants that reach ≥3 m in height and are derived from published and unpublished (grey) literature as well

as herbarium records. See main text for further details.

Figure 2. First two principal components from a principal component analysis of all climatic variables.

Potential.ET: Potential Evapotranspiration; PrecWetP: Precipitation of wettest month; PrecAnn: Annual

precipitation; TempSeas: Temperature seasonality; TempAnnRng: Temperature annual range.

HyperSeas: Seasonality in water availability; TempDayRng: Temperature day range; PrecDryP:

Precipitation of driest month; TempMax: Max temperature of warmest month; WaterDefSev: Water

deficit severity; WaterDefDur: Water deficit duration; TempMin: Minimum Temperature of coldest

month; Isotherm: Isothermality; CloudItcp: Cloud interception; DaysFrost: Days of frost. The

relationship of latitude to these first two principal components is shown with contour (red) lines.

Figure 3. Variation with latitudinal across southern South America for (a) species richness, (b)

phylogenetic diversity sensu stricto, (c) mean nearest taxon distance and (d) phylogenetic diversity

sensu stricto standardised for variation in species richness (ses.PD). Each point represents the estimated

value for a single tree community. See the legend in Figure 1 for explanation of colour codes for biomes.

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Figure 1. Tree communities extracted from the NeotropTree database and used in this study. The

symbols correspond to the biomes. Each tree community represents an inventory of non-climbing woody

plants that reach ≥3 m in height and are derived from published and unpublished (grey) literature as well

as herbarium records. See main text for further details.

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Figure 2. First two principal components from a principal component analysis of all climatic variables.

Potential.ET: Potential Evapotranspiration; PrecWetP: Precipitation of wettest month; PrecAnn: Annual

precipitation; TempSeas: Temperature seasonality; TempAnnRng: Temperature annual range.

HyperSeas: Seasonality in water availability; TempDayRng: Temperature day range; PrecDryP:

Precipitation of driest month; TempMax: Max temperature of warmest month; WaterDefSev: Water

deficit severity; WaterDefDur: Water deficit duration; TempMin: Minimum Temperature of coldest

month; Isotherm: Isothermality; CloudItcp: Cloud interception; DaysFrost: Days of frost. The

relationship of latitude to these first two principal components is shown with contour (red) lines.

Figure 3. Variation with latitudinal across southern South America for (a) species richness, (b)

phylogenetic diversity sensu stricto, (c) mean nearest taxon distance and (d) phylogenetic diversity

sensu stricto standardised for variation in species richness (ses.PD). Each point represents the estimated

value for a single tree community. See the legend in Figure 1 for explanation of colour codes for biomes.

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