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The concept of the biome has a long history dating back to Carl Ludwig Willdenow and Alexander von Humboldt. However, while the association between climate and the structure and diversity of vegetation has a long history, scientists have only recently begun to develop a more synthetic understanding of biomes based on the evolution of plant diversity, function, and community assembly. At the broadest scales, climate filters species based on their functional attributes, and the resulting functional differences in dominant vegetation among biomes are important to modeling the global carbon cycle and the functioning of the Earth system. Nevertheless, across biomes, plant species have been shown to occupy a common set of global functional “spectra”, reflecting variation in overall plant size, leaf economics, and hydraulics. Still, comprehensive measures of functional diversity and assessments of functional similarity have not been compared across biomes at continental to global scales. Here, we examine distributions of functional diversity of plant species across the biomes of North and South America, based on distributional information for > 80,000 vascular plant species and functional trait data for ca. 8,000 of those species. First, we show that despite progress in data integration and synthesis, significant knowledge shortfalls persist that limit our ability to quantify the functional biodiversity of biomes. Second, our analyses of the available data show that all the biomes in North and South America share a common pattern–most geographically common, widespread species in any biome tend to be functionally similar whereas the most functionally distinctive species are restricted in their distribution. Third, when only the widespread and functionally similar species in each biome are considered, biomes can be more readily distinguished functionally, and patterns of dissimilarity between biomes appear to reflect a correspondence between climate and functional niche space. Taken together, our results suggest that while the study of the functional diversity of biomes is still in its formative stages, further development of the field will yield insights linking evolution, biogeography, community assembly, and ecosystem function.
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ORIGINAL RESEARCH
published: 18 December 2018
doi: 10.3389/fevo.2018.00219
Frontiers in Ecology and Evolution | www.frontiersin.org 1December 2018 | Volume 6 | Article 219
Edited by:
Daniel M. Griffith,
Oregon State University, United States
Reviewed by:
Joaquín Hortal,
Museo Nacional de Ciencias
Naturales (MNCN), Spain
Mark E. Olson,
National Autonomous University of
Mexico, Mexico
*Correspondence:
Susy Echeverría-Londoño
susyelo@gmail.com
Specialty section:
This article was submitted to
Biogeography and Macroecology,
a section of the journal
Frontiers in Ecology and Evolution
Received: 02 June 2018
Accepted: 03 December 2018
Published: 18 December 2018
Citation:
Echeverría-Londoño S, Enquist BJ,
Neves DM, Violle C, Boyle B,
Kraft NJB, Maitner BS, McGill B,
Peet RK, Sandel B, Smith SA,
Svenning J-C, Wiser SK and
Kerkhoff AJ (2018) Plant Functional
Diversity and the Biogeography of
Biomes in North and South America.
Front. Ecol. Evol. 6:219.
doi: 10.3389/fevo.2018.00219
Plant Functional Diversity and the
Biogeography of Biomes in North
and South America
Susy Echeverría-Londoño 1
*, Brian J. Enquist 2, Danilo M. Neves 2,3 , Cyrille Violle 4,
Brad Boyle 2, Nathan J. B. Kraft 5, Brian S. Maitner 2, Brian McGill 6, Robert K. Peet 7,
Brody Sandel 8, Stephen A. Smith 9, Jens-Christian Svenning 10,11 , Susan K. Wiser 12 and
Andrew J. Kerkhoff 1
1Department of Biology, Kenyon College, Gambier, OH, United States, 2Department of Ecology and Evolutionary Biology,
University of Arizona, Tucson, AZ, United States, 3Department of Botany, Federal University of Minas Gerais, Belo Horizonte,
Brazil, 4Centre d’Ecologie Fonctionnelle et Evolutive (UMR 5175), CNRS, Université de Montpellier, Université Paul Valéry,
Montpellier, France, 5Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles,
CA, United States, 6School of Biology and Ecology, University of Maine, Orono, ME, United States, 7Department of Biology,
University of North Carolina, Chapel Hill, NC, United States, 8Department of Biology, Santa Clara University, Santa Clara, CA,
United States, 9Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, United States,
10 Department of Bioscience, Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Aarhus University,
Aarhus, Denmark, 11 Section for Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Aarhus,
Denmark, 12 Landcare Research New Zealand, Lincoln, New Zealand
The concept of the biome has a long history dating back to Carl Ludwig Willdenow
and Alexander von Humboldt. However, while the association between climate and the
structure and diversity of vegetation has a long history, scientists have only recently
begun to develop a more synthetic understanding of biomes based on the evolution of
plant diversity, function, and community assembly. At the broadest scales, climate filters
species based on their functional attributes, and the resulting functional differences in
dominant vegetation among biomes are important to modeling the global carbon cycle
and the functioning of the Earth system. Nevertheless, across biomes, plant species
have been shown to occupy a common set of global functional “spectra”, reflecting
variation in overall plant size, leaf economics, and hydraulics. Still, comprehensive
measures of functional diversity and assessments of functional similarity have not been
compared across biomes at continental to global scales. Here, we examine distributions
of functional diversity of plant species across the biomes of North and South America,
based on distributional information for >80,000 vascular plant species and functional
trait data for ca. 8,000 of those species. First, we show that despite progress in data
integration and synthesis, significant knowledge shortfalls persist that limit our ability to
quantify the functional biodiversity of biomes. Second, our analyses of the available data
show that all the biomes in North and South America share a common pattern–most
geographically common, widespread species in any biome tend to be functionally similar
whereas the most functionally distinctive species are restricted in their distribution.
Third, when only the widespread and functionally similar species in each biome are
considered, biomes can be more readily distinguished functionally, and patterns of
dissimilarity between biomes appear to reflect a correspondence between climate and
Echeverría-Londoño et al. New World Functional Diversity
functional niche space. Taken together, our results suggest that while the study of the
functional diversity of biomes is still in its formative stages, further development of the field
will yield insights linking evolution, biogeography, community assembly, and ecosystem
function.
Keywords: biogeography, biomes, functional traits, hypervolumes, macroecology, plant functional diversity
INTRODUCTION
Ecologists and biogeographers organize land plant
biodiversity into climatically-determined biomes, with
physiognomies characterized by the growth forms and
functional traits of the dominant species (Moncrieff et al.,
2016). Indeed, the biome concept has a long history dating
back to Carl Ludwig Willdenow and Alexander von Humboldt.
Willdenow recognized that similar climates support similar
vegetation forms, and Humboldt observed the widespread
association between plant distribution, physiognomy, and
environmental factors. Overall, the biome concept reflects the
assumption that similar environmental pressures select for
species with similar functional attributes, independent of their
evolutionary history. At the same time, Earth’s extant biomes
are to some extent phylogenetically distinct, with many/most
of the characteristic species being drawn from specific lineages
exhibiting key adaptations not just to climatic selection but to
additional pressures like fire or megaherbivores (Woodward
et al., 2004; Pennington et al., 2006; Donoghue and Edwards,
2014). Because biomes represent broad-scale regularities in
Earth’s vegetation, understanding functional differences among
biomes is critically important to modeling the global carbon cycle
and the functioning of the Earth system, including responses to
anthropogenic global change (Bonan et al., 2012; van Bodegom
et al., 2014; Xia et al., 2015).
The past two decades has seen rapid growth in understanding
the functional dimension of plant biodiversity across continental
scales (Swenson et al., 2012; Lamanna et al., 2014; Šímová
et al., 2018). Extensive data synthesis and analysis efforts
have defined a limited functional trait space incorporating
variation in overall plant size, leaf economics, and hydraulics,
known as functional trait spectra (Wright et al., 2004; Díaz
et al., 2016). Functional trait spectra define physiological
and ecological trade-offs that determine plant life-history
strategies (Westoby, 1998; Reich et al., 2003; Craine, 2009)
and their influence on community assembly (Kraft et al.,
2008), ecosystem function (Lavorel and Garnier, 2002; Garnier
et al., 2004; Kerkhoff et al., 2005; Cornwell et al., 2008),
and even rates of evolution (Smith and Donoghue, 2008;
Smith and Beaulieu, 2009). The generality and utility of plant
functional trait spectra has hastened their incorporation into
models of the global distribution of vegetation (van Bodegom
et al., 2014), biogeochemical cycling (Bonan et al., 2012), and
ecosystem services (Díaz et al., 2007; Cadotte et al., 2011;
Lavorel et al., 2011). However, few studies have examined
comprehensive measures of functional diversity at the biome
scale across both dominant and subordinate species and life
forms.
There are two contrasting sets of predictions about
how functional diversity varies among climatically and
physiognomically distinct biomes. On the one hand, if the
biodiversity of biomes reflects variation in the available ecological
niche space, less taxonomically diverse biomes should represent
a smaller, largely nested subset of the functional space occupied
by more diverse biomes. On the other hand, due to the global
nature of fundamental trade-offs in plant structure and function,
and similar selection pressures acting similarly across species,
assemblages occupying different environments may in fact share
similar areas of trait space (Reich et al., 2003; Wright et al., 2004;
Díaz et al., 2016). Recent studies confirm that the relationships
between climate and functional and taxonomic diversity (i.e.,
species richness) are complex and scale-dependent. In some
cases, functional diversity closely tracks climatic gradients,
with lower functional diversity in more variable and extreme
conditions (Swenson et al., 2012; de la Riva et al., 2018), and the
volume of functional space in local assemblages expands with
increasing taxonomic richness (Lamanna et al., 2014; Li et al.,
2018). However, analyses of regional-scale species pools suggest
that large changes in species richness may be associated with
minimal impacts on functional diversity (Lamanna et al., 2014;
Šímová et al., 2015). Moreover, the responses of taxonomic and
functional diversity to climate may differ among major plant
growth forms (Šímová et al., 2018), and the relative diversity
of different growth forms may change substantially along the
climate gradients that define different biomes (Engemann et al.,
2016).
Progress in analyzing functional diversity on continental
to global scales has been limited in part by data shortfalls
in cataloging the taxonomic, distributional, phylogenetic,
and functional aspects of biodiversity (Hortal et al., 2015).
Furthermore, even given the limited data available, significant
informatics challenges are associated with standardizing and
integrating large, disparate datasets describing the geographic
distributions, functional traits, and phylogenetic relationships
of species (Violle et al., 2014). Here we examine the distribution
of functional diversity of plant species across the biomes of
North and South America using the Botanical Information and
Ecology Network database (BIEN; Enquist et al., 2016; Maitner
et al., 2018), which assembles distributional and functional trait
information on >100,000 species of land plants. Specifically, we
examine variation in the functional diversity and distinctiveness
of biomes, based on land plant species distribution maps at a
scale of 100 ×100 km grid cells and a comprehensive dataset
of six functional traits that reflect the major axes of variation in
ecological strategies.
Our goals in this study are 3-fold. First, in order to highlight
persistent data shortfalls, we document the extent of the available
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Echeverría-Londoño et al. New World Functional Diversity
data characterizing the functional diversity and distinctiveness
of biomes. Second, given the data available, we characterize the
distribution of functional diversity within biomes across both
dominant and subordinate growth forms. These analyses allow
us to better quantify the functional distinctiveness of a biome
by identifying the most common functional strategies of the
most widespread species within it. Third, we ask whether biomes
are in fact characterized by functionally distinct collections of
species, based on the overlap of multidimensional hypervolumes
in functional trait space.
METHODS
Distribution Data and Biome Classification
To reduce the effects of sampling bias characteristic of occurrence
datasets compiled from multiple resources, we used the BIEN
2.0 range maps for 88,417 of plant species distributed in
North and South America (Goldsmith et al., 2016). The BIEN
database integrates standardized plant observations stemming
from herbarium specimens and vegetation plot inventories.
Species range maps in the BIEN databases were estimated using
one of three approaches, depending on the occurrences available
for each species. For species with only one or two occurrences
(c. 35% of the species), the geographic range was defined as
a square 75,000 km2area surrounding each data point. The
geographic ranges for species with three or four occurrences
were identified using a convex hull (c. 15% of the species).
Finally, the range maps for species with at least five occurrences
were obtained using the Maxent species distribution modeling
algorithm, using 19 climatic layers as predictor variables and 19
spatial eigenvectors as filters to constrain over predictions by the
models (see Goldsmith et al., 2016 for further details on range
map methodology).
We overlaid the BIEN 2.0 plant species maps on a 100
×100 km grid map with a Lambert Azimuthal Equal Area
projection to obtain a presence/absence matrix of species
for each grid cell. Based on the Olson et al. (2001) biome
classification, we assigned each matrix grid cell to one of the
biomes categories. Because of computational limitations for the
subsequent analyses, we joined some biomes based on their
similarities in climate and vegetation and literature to obtain
a broad classification as described in Table 1 (excluding Inland
Water, Rock and Ice and Mangroves). The Chaco and Caatinga
ecoregions were classified as Xeric Woodlands and Dry forest,
respectively, following Prado and Gibbs (1993),Pennington et al.
(2000),Banda et al. (2016),Silva de Miranda et al. (2018).
Species Composition Among Biomes
To understand the variation in functional trait space among
biomes, we first explored the differences in plant species
composition among them. Based on the species list for each grid
cell and biome, we defined each biome’s characteristic species
as those that have the maximum proportion of their range in
that biome. These lists of geographically predominant species
in a given biome were compared to the list of species in other
biomes. This pairwise comparison provides a simple way to
infer a directional taxonomic overlap among biomes (i.e., the
TABLE 1 | Overview of the biome classification adopted in this study and the
equivalent (Olson et al., 2001) biomes classification (excluding Inland Water, Rock
and Ice, and Mangroves).
Biomes used in this
study
Original (Olson et al., 2001) biomes
Moist Forests Tropical and Subtropical Moist Broadleaf Forests
Dry Forests Tropical and Subtropical Coniferous Forests
Tropical and Subtropical Dry Broadleaf Forests
Caatinga ecoregion
Savannas Flooded Grasslands and Savannas
Tropical and Subtropical Grasslands, Savannas and
Shrublands
Tropical Grasslands Montane Grasslands and Shrublands
Xeric Woodlands Deserts and Xeric Shrublands
Chaco ecoregion
Mediterranean
Woodlands
Mediterranean Forests, Woodlands and Scrub
Temperate Grasslands Temperate Grasslands, Savannas and Shrublands
Temperate Mixed
Forests
Temperate Broadleaf and Mixed Forests
Coniferous Forests Temperate Conifer Forests
Taiga Boreal Forests/Taiga
Tundra Tundra
Because of computer limitations, some biomes were joined based on their climatic and
vegetation similarities. The Chaco and Caatinga ecoregions were classified as Xeric
Woodlands and Dry forest, respectively, following Prado and Gibbs (1993),Pennington
et al. (2000),Banda et al. (2016),Silva de Miranda et al. (2018).
proportion of predominant species of a biome shared with
another biome). Of the 88,417 species with available range maps,
44,899 species have ranges spanning more than one biome, and
43,518 species are endemic to a specific biome.
Trait Data
We extracted all the trait information for plant species in the
New World available in the BIEN 3.0 dataset (retrieved on
7 February 2018) giving a total of 80,405 species levels trait
observations. We then filtered the information for six functional
traits: maximum plant height (m), seed mass (mg), wood density
(mg/cm3), specific-leaf-area SLA (cm2/g) and leaf phosphorus
and leaf nitrogen concentration per unit mass (mg/g). A total
of 18,192 species-level observations were left after filtering. From
these, the subset of 8,820 species with both range maps and trait
information was used for further analyses.
To estimate the functional trait space for each biome, we
required complete trait data. For this reason, we phylogenetically
imputed missing trait data (Bruggeman et al., 2009; Penone et al.,
2014; Swenson, 2014; Swenson et al., 2017) using the R package
“Rphylopars” v 0.2.9 (Goolsby et al., 2017) and the recently
published phylogeny of seed plants by Smith and Brown (2018)
as a baseline. Phylogenetic imputation is a tool for predicting
missing data in functional traits datasets based on the assumption
that closely related species tend to have similar trait values
(Swenson, 2014). We used the ALLBM tree (i.e., gene bank and
Open Tree of life taxa with a backbone provided by Magallón
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Echeverría-Londoño et al. New World Functional Diversity
et al., 2015) because it maximized the overlap between species
with available trait and distributional information. After the
trait imputation, a total of 7,842 species with complete trait
information and range maps remained for further analysis.
Trait Hypervolumes Measurement
We measured the relative functional diversity of biomes by
calculating trait hypervolumes from species pools within biomes
cells. Due to computational limitations, we constructed the trait
hypervolumes using a random sample of 20% of the cells in
each biome. The hypervolumes for each grid cell were estimated
using the extracted six functional traits and the R package
“hypervolume” (Blonder et al., 2014, 2018), using the Gaussian
KDE method with the default Silverman bandwidth estimator.
Seed mass, height and wood density were log-transformed,
whereas SLA was squared-root transformed. All traits were scaled
and centered before the analysis. Hypervolumes are reported in
units of standard deviations (sd) to the power to the number of
traits used (i.e., sd6).
Functional Distinctiveness and
Widespreadness
Because biomes are characterized by their dominant vegetation,
we also examined the geographic commonness and functional
distinctiveness of species within biomes. Using species range
maps and functional trait information, we estimated the
functional distinctiveness and widespreadness of each species in
each biome, following the conceptual framework of functional
rarity by Violle et al. (2017). Using the whole set of (measured
and imputed) traits, we first measured the Euclidean distance
in standardized trait space between all pair of species. We then
calculated the functional distinctiveness (Di) for each species
in each biome as the average functional distance of a species
to the N other species within the biome species pool. Di was
scaled between 0 and 1 within each biome with lower values
representing species that are functionally common (redundant)
and higher values representing species that are functionally
distinctive, compared to the other species in the biome. We
also estimate the geographic widespreadness (Wi) of a species
in a biome, measured as the number of grid cells occupied
by the species within a biome over the total number of cells
in that biome. A value of 1 indicates that the focal species is
present in all grid cells covered by the biome. Both functional
distinctiveness and geographic widespreadness were calculated
using the R package “funrar” (Grenié et al., 2017).
Because we lack comprehensive measures of dominance
based on local abundance or biomass, we used the measures
Di and Wi to identify for each biome the most “common”
species as those that are both geographically widespread (Wi >
0.5) and functionally similar (Di <0.25). This last threshold
was used since the third quantile of functional distinctiveness
values among biomes ranged from 0.2 to 0.3. To discriminate
functionally distinct species vs. functionally similar species in
subsequent analyses, we, therefore, used a value of 0.25 as a
cut-off (i.e., species with distinctiveness values <0.25 were
considered functional common or redundant within a specific
biome).
Functional Space and Biome Similarity
To estimate the overlap among biomes’ hypervolumes we
employed the Sørensen similarity index using (i) the total
number of species and (ii) the list of species considered as
functionally common and geographically widespread for each
biome. Functional trait space similarity was calculated as the
pairwise fractional overlap of hypervolumes among biomes. The
fractional overlap was calculated by dividing twice the volume
of the intersection of two hypervolumes by the volume of their
unions. All hypervolumes were estimated using the R package
“hypervolume” (Blonder et al., 2014, 2018), using the Gaussian
KDE method with the default Silverman bandwidth estimator.
RESULTS
We found substantial overlap in plant species composition across
biomes, based on the intersection of modeled species ranges
(see Figure 1, and Supplementary Table 1). This taxonomic
overlap is greater within tropical and temperate biomes, with
relatively few species being shared between these two climatic
zones. Interestingly, xeric woodlands share species with both
tropical and temperate biomes. Despite the high proportion
of species characteristic of tropical moist forest (83%), this
biome also shares large numbers of species with other tropical
biomes such as dry forests, savannas, xeric woodlands and
tropical grasslands. The high taxonomic overlap of temperate
biomes such as temperate grasslands, Mediterranean woodlands,
taiga and tundra suggests the potential for low functional
distinctiveness, with some temperate biomes representing a
poorer subset of the more species-rich, functionally-diverse
tropical biomes.
With fewer than 10% of the mapped species represented,
the trait data were quite sparse for our biome-scale species
assemblages (Figure 2A). Moreover, the available trait data
varied substantially across traits, plant clades, and biomes.
Phylogenetically, leaf P and wood density were particularly
poorly represented with whole clades lacking any available data.
As a result, of the approximately 2/3 of the trait values for our
7,842 species that had to be imputed, many had to be assigned
in the absence of any closely related taxa. Geographically, SLA,
height, and seed mass are undersampled in the tropics and
temperate South America, while leaf N and wood density are
more evenly sampled among regions. Leaf P is poorly sampled
across all biomes. Trait hypervolumes created from species
pools of a random selection of 20% of cells for each biome
mainly show differences between tropical and temperate/cold
biomes (Figure 2B). Trait hypervolumes tend to be larger and
more variable in tropical biomes, with the highest variation in
moist and dry tropical forests. Among temperate/cold biomes,
coniferous and temperate mixed forest support the largest
trait hypervolumes. Interestingly, xeric shrublands exhibit a
distribution of hypervolumes more similar to tropical than to
temperate biomes.
The relationship between functional distinctiveness and
geographic distribution is remarkably similar among biomes
(Figure 3). In every biome, the vast majority of species are
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Echeverría-Londoño et al. New World Functional Diversity
FIGURE 1 | Overlap of plant species among biomes of the New World. Percentage values express the fraction of species occurring in a biome that have the greatest
proportion of their geographic range in that biome, N=84,413. The base of each branched arrow is positioned to show the biome that includes the greatest
proportion of a species range, while the width represents the number of species shared with the biomes at the tips of the arrow. See Supplementary Table 1 for the
underlying matrix.
both geographically restricted and functionally similar. At the
same time, the most functionally distinctive species within every
biome were generally geographically restricted as well, and the
most geographically widespread species were almost always
functionally similar.
We found considerable variation in the proportional
distribution of growth forms within and among biomes. Woody
species represent the dominant growth forms in tropical
biomes in terms of species numbers, whereas herbaceous
species dominate in temperate environments (Figure 4). When
we considered only those species that are widespread and
functionally common in each biome, the distribution of growth
forms across biomes changed, especially in the proportion of
trees, herbs and grasses. For instance, in tropical biomes, the
proportion of trees decreased in each biome except for moist
forest. In temperate biomes, the proportion of grasses increased,
especially toward the polar regions. Interestingly, the distribution
of growth forms in xeric woodlands more closely resembles the
distribution in temperate biomes when only widespread and
functionally common species are considered.
Pairwise comparisons of species composition among biomes
reveal three main clusters representing the tropical, temperate
and polar climatic zones (Figure 5A), reflecting the high
taxonomic overlap within, but not between, these regions
(Figure 1). Pairwise comparisons of trait hypervolumes among
biomes show a less clear clustering of climatic zones (Figure 5B).
In this case, the functional space of xeric woodlands overlaps
significantly with temperate biomes. This analysis also reveals
the overlap in functional space of taigas with temperate
grasslands and mixed forests. The pairwise comparison of trait
hypervolumes among biomes using only those species considered
as functionally common and widespread shows less overlap
in trait spaces among and within climatic zones (Figure 5C).
However, even though xeric woodlands are now clustered
with the rest of tropical biomes, these habitats along with
tropical grassland exhibit great overlap in functional space
with temperate biomes such as Mediterranean woodlands and
temperate grasslands.
DISCUSSION
Our analyses yield three important insights for understanding
terrestrial biomes through a functional lens. First, we show that
despite progress in the compilation and synthesis of primary
biodiversity data, significant knowledge shortfalls persist that
may limit our ability to quantify the functional biodiversity of
biomes on continental to global scales. Second, our analyses of
the available data nevertheless show that all of the biomes in
North and South America share a remarkable common pattern
in which the most geographically widespread species in any
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Echeverría-Londoño et al. New World Functional Diversity
FIGURE 2 | (A) Proportion of species in the BIEN 3.0 database with known (gray) or missing (black) trait values. Phylogeny at the left corresponds to the seed plants
ALLBM tree from Smith and Brown (2018) (i.e., GenBank and Open Tree of life taxa with a backbone provided by Magallón et al., 2015). Maps represent the
proportion of species with trait information relative to the total number of species in the BIEN 2.0 database. (B) Distribution of trait hypervolumes of 20% of randomly
selected 100 ×100 km cells in each biome. Hypervolumes are reported in units of standard deviations to the power of the number of traits used.
biome tend to share common functional traits while the most
functionally distinctive species are invariably restricted in their
distribution. Third, when only the widespread and functionally
common species are considered, biomes can be more readily
distinguished functionally, and patterns of dissimilarity between
biomes appear to reflect a correspondence between climate and
plant functional niche space. Taken together, our results suggest
that while the study of the functional diversity of biomes is
still in its formative stages, further development of the field will
likely yield insights linking evolution, biogeography, community
assembly, and ecosystem function.
KNOWLEDGE SHORTFALLS
The BIEN database is specifically designed to close gaps in
our knowledge of plant biodiversity, yet as Hortal et al. (2015)
point out, interacting knowledge shortfalls lead to uncertainty
in quantifying biodiversity at the largest scales. For example,
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Echeverría-Londoño et al. New World Functional Diversity
FIGURE 3 | Patterns of functional distinctiveness across biomes. Distinctiveness represents how species are functionally distant from each other within a biome (i.e.,
the mean pairwise phenotypic distance from a focal species to all the others). The larger the value, the more distant a species is to the centroid of the biome’s
functional space. Widespreadness measures how geographically common a species is within a biome. A value of 0 indicates that a species is present in a single
biome cell. Bin values are the number of species on a logescale. Rectangles represent the species that are considered functionally similar and widespread in each
biome using cut-off values of 0.25 and 0.5 of distinctiveness and widespreadness, respectively.
not only did fewer than 10% of our mapped species have
both trait data and phylogenetic information available, but
those missing trait data (66% of species’ trait values) were
quite structured, both phylogenetically and geographically.
Thus, the Raunkiaerian shortfall in functional trait data (sensu
Hortal et al., 2015) interacts with the Wallacean shortfall
in distributional information and the Darwinian shortfall in
phylogenetic understanding. And while we can use phylogenetic
knowledge to reasonably impute those missing values (Swenson
et al., 2017), several aspects of the resulting patterns that
are important to biome classification remain uncertain. For
example, the existing growth form data suggest that woody
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Echeverría-Londoño et al. New World Functional Diversity
FIGURE 4 | Distribution of growth forms in each biome (left) using the total number of species, and (right) using only those species that are functionally similar and
widespread within the biome (see Figure 3).
species dominate in all tropical biomes, whereas the proportional
diversity of herbaceous growth forms is much higher in
temperate and polar biomes (see also Engemann et al., 2016;
Zanne et al., 2018). Does this latitudinal increase in relative
diversity of herbaceous plants reflect sampling biases and a
lack of taxonomic knowledge about tropical herbaceous plants,
or does it reflect the differing evolutionary and biogeographic
histories in the Nearctic and Neotropical realms? Dominant
growth forms are one of the key distinguishing features of
biomes, so systematic changes in the most diverse growth
forms (whether dominant or not) will necessarily influence our
predictions about how functional diversity might change across
biomes, and how those changes will affect ecosystem function and
services.
We used species range maps as input data mainly to
overcome the undeniable issue of sampling bias that is
characteristic of datasets compiled from multiple sources (see
Supplementary Figure 1). However, range maps drawn from
species distribution models could represent an additional
element of uncertainty in our results. For example, given the
geographic resolution of this study and the spatial complexity
of certain biomes, these models could have overestimated
the geographical extent of some species from cells of a
single biome to cells of nearby and interdigitated ones.
Using occurrence data did not change the general results
of this study (see Supplementary Figures 26); however, a
slight decrease in the functional overlap among biomes
could indeed reveal an overestimation of some species ranges
(see Supplementary Figures 2,5, and 6). Using occurrence
information also changed the general relationships between
functional distinctiveness and widespreadness in our results, due
to the relative oversampling of temperate vs. tropical regions
(see Supplementary Figure 4). In this case, our measure of
widespreadness is limited by the extremely limited sampling
of most species in tropical biomes. As datasets and sampling
improve, there is likely to be scope to reduce these uncertainties
in the future.
The other data gap that needs to be addressed to understand
the functional diversity of biomes is the Prestonian shortfall in
abundance information. Abundance is particularly important
in studies of functional diversity because the traits that matter
most for community assembly, ecosystem functioning, and
biogeochemical cycling are those of the most dominant
species. Because we based our assemblages on range maps
derived from species distribution models, we could only
address the geographic component of commonness, but the
positive relationship between local abundance and geographic
range, the so-called occupancy-abundance relationship,
suggests that the most widespread species in each biome may
frequently be among the more abundant as well (Borregaard
and Rahbek, 2010; Novosolov et al., 2017). Because biomes
are generally characterized by the dominant growth forms
in the region, integrating abundance information might
result in biomes showing less functional overlap. However,
even though BIEN has compiled voluminous plot data
that allow estimates of local abundance, making reasonable
comparisons across different regions and growth forms
is hampered by uneven sampling, regional differences in
gamma diversity, and incommensurate methods of quantifying
abundance.
Frontiers in Ecology and Evolution | www.frontiersin.org 8December 2018 | Volume 6 | Article 219
Echeverría-Londoño et al. New World Functional Diversity
FIGURE 5 | (A) Pairwise dissimilarity in species composition among biomes.
(B) Pairwise dissimilarity in trait hypervolumes (1-Sørensen similarity) among
biomes using the total number of species. (C) Pairwise dissimilarity in trait
hypervolumes (1-Sørensen similarity) among biomes using only those species
that are considered as functionally similar and widespread. The lighter the cell
the greater the dissimilarity.
COMMON PATTERNS WITHIN BIOMES
Despite the persistent gaps in the available data, our analyses
uncovered a previously undocumented relationship common to
all the biomes of the Western Hemisphere: in any biome, the
most widespread species also tend to exhibit low functional
distinctiveness, whereas the most functionally distinctive species
are almost invariably restricted in their distribution (Figure 3).
This “occupancy-redundancy” relationship may suggest that the
climatic conditions prevalent within a biome select for a set
of common characteristics, with more functionally distinctive
species being restricted to a rarer subset of habitats within the
biome. The overall prevalence of functionally similar species
in all biomes and the “occupancy-redundancy” relationship are
both consistent with a recent global analysis of community level
functional diversity that suggests that habitat filtering leads to
the coexistence of functionally similar species (Li et al., 2018)
as well as studies showing that functional redundancies increase
community stability (e.g., Walker et al., 1999; Pillar et al., 2013).
Moreover, together with the high degree of both taxonomic and
functional overlap among biomes (Figures 1,5), the fact that
common, widespread species are functionally similar reinforces
the notion that land plants across a wide range of environmental
conditions share common characteristics near the core of the
functional trait spectrum (Wright et al., 2004; Díaz et al.,
2016). Unlike Umaña et al. (2017), our results show that rare,
geographically restricted species may or may not be functionally
distinct from more widespread and common species. Thus, the
question remains open whether more functionally distinctive
species are specialists in particular environments or whether
their trait combinations result in demographic or physiological
trade-offs that limit their geographic distribution.
COMPARISONS BETWEEN BIOMES
Our comparison of trait hypervolume distributions across
biomes (Figure 2B) is consistent with the observation that more
species-rich environments are also more functionally diverse
(Swenson et al., 2012; Lamanna et al., 2014; Li et al., 2018;
Šímová et al., 2018). Our results are more equivocal concerning
the hypothesis that seasonal and extreme climatic environments
consistently limit the functional diversity of species (de la Riva
et al., 2018). All tropical biomes display higher average functional
diversity than all temperate biomes, and the polar biomes do
display the smallest hypervolumes. However, within each group,
drier or more seasonally variable biomes do not always display
smaller hypervolumes (e.g., dry forests, xeric woodlands), as
we would have expected following the tolerance hypothesis
by Currie et al. (2004), whereas optimal climatic conditions
support more combinations of physiological parameters. From
these results alone we cannot determine whether temperate
and polar biomes are less taxonomically diverse because of
limits on functional niche space, or whether their functional
hypervolumes are small because they are not taxonomically
diverse. Null-modeling approaches could potentially help to
disentangle taxonomic and functional diversity (Swenson et al.,
2012; Lamanna et al., 2014; Šímová et al., 2018), but such an
Frontiers in Ecology and Evolution | www.frontiersin.org 9December 2018 | Volume 6 | Article 219
Echeverría-Londoño et al. New World Functional Diversity
analysis was beyond the scope of this study. More importantly,
our results reinforce the importance of understanding how
evolutionary and biogeographic history shape the functional
diversity of biomes (Woodward et al., 2004; Pennington et al.,
2006; Donoghue and Edwards, 2014; Moncrieff et al., 2016). The
extensive sharing of species (and higher lineages) across biomes
within, but largely not between, different biogeographic realms
could serve both to homogenize functional diversity within
realms and to provide clues about the characteristic traits that are
selected for, or against, by different environments (Douma et al.,
2012; Zanne et al., 2014, 2018).
Despite substantial hypervolume overlap among all the
biomes (Supplementary Figure 2), tropical, temperate, and cold
biomes all appear to occupy distinguishable regions of functional
space (Figures 5B,C). The main traits differentiating biomes
appear to be traits related to overall plant size, including both
mature height and seed mass (Supplementary Figures 710),
rather than leaf economics traits, as observed in more local,
plot-based analyses (e.g., Douma et al., 2012). The exception is
leaf P, which displayed substantial differences between tropical
and temperate/polar biomes (Supplementary Figures 7–10), a
pattern that has been observed in other analyses based on
both species-specific values and whole ecosystem measurements
(Kerkhoff et al., 2005; Swenson et al., 2012). Because leaf P was
our most sparsely sampled trait, the differences between tropical
and temperate/polar realms might be subject to biases from the
imputation procedure. However, Leaf P does exhibit a significant
phylogenetic signal (Kerkhoff et al., 2006), which suggests that
the imputations should be unbiased (Swenson et al., 2017).
Leaf P is also significantly higher in herbaceous growth forms
(Kerkhoff et al., 2006), so the latitudinal shift from predominantly
woody to herbaceous diversity (Figure 4) may also influence this
pattern.
When we limited hypervolume analyses to only the most
widespread and functionally common species in each biome, the
individual biomes within each biogeographic realm overlapped
less in functional trait space (compare Figures 5B,C), suggesting
that these species may reflect phenotypes better adapted to
particular environments. In this context, the xeric woodland
biome is particularly interesting. In part due to the inclusion
of the Chaco ecoregion, xeric woodlands cluster with the
tropical biomes taxonomically (Figure 5A). But when the
functional hypervolumes of all of the species are considered,
they show much stronger similarity to the temperate biomes
(Figure 5B). Finally, when only the most widespread and
functionally common species are analyzed, xeric woodlands
again show increased similarity to tropical biomes, but also
they maintain high similarity with temperate grassland and
Mediterranean biomes (Figure 5C). Transitions from warm,
mesic environments to colder, drier, and more seasonal
environments are facilitated by similar traits, e.g., herbaceous
habit (Douma et al., 2012; Zanne et al., 2014, 2018), and like
colder environments, communities in dry environments also
tend to be more phylogenetically clustered (Qian and Sandel,
2017). Furthermore, the position of xeric zones at the boundary
of the inter-tropical convergence zone makes them a geographical
transition between the tropical and temperate realms. The fact
that xeric woodlands are intermediate between the tropical
and temperate realms both functionally and biogeographically
further reinforces the idea that to better understand the
functional diversity of biomes we must take into account their
biogeographic and phylogenetic histories (Pennington et al.,
2006; Donoghue and Edwards, 2014; Moncrieff et al., 2016).
CONCLUSIONS
Any classification of terrestrial biomes imposes a small number
of discrete categories on continuous gradients in climate and
species distributions, and thus represents a gross simplification
of the complex ecological landscape (Moncrieff et al., 2016, but
see Silva de Miranda et al., 2018). Yet despite their potential for
oversimplification, biomes are useful constructs for organizing
and understanding the biodiversity and functioning of Earth’s
major terrestrial ecosystems, and trait-based approaches have
high potential to help dynamically model global vegetation
distributions.
In this study we have shown that much of the taxonomic
diversity of all biomes represents species that are both narrowly
distributed and functionally similar. Further, within biomes the
most functionally distinctive species in each biome also tend to be
geographically rare, while widespread species uniformly display
low functional distinctiveness. Despite extensive taxonomic
and functional overlap among biomes, they do cluster into
distinguishable, biogeographically and climatically distinct units,
especially when the functional clustering is based on the most
widespread and functionally common species in each biome.
However, advancing a functional understanding of biomes will
require not just a better characterization of trait variation within
and between vegetation types, but also information on the
biogeographic and phylogenetic history of species assemblages
and the relative abundance of species within biomes.
DATA AVAILABILITY
Trait datasets and species range maps analyzed for this study can
be download through the R package BIEN (Maitner et al., 2018).
See http://bien.nceas.ucsb.edu/bien/ for more details about the
BIEN database.
AUTHOR CONTRIBUTIONS
SE-L, AK, BJE, DMN, and CV designed the study; SE-L and AK
analyzed the data; SE-L and AK wrote the first version of the
manuscript; CV, BB, NK, BSM, BM, RKP, BS, SS, J-CS, and SKW
contributed to the collation and creation of the traits and range
maps database. All authors contributed to the development and
writing of the manuscript.
FUNDING
SE-L, DMN, and AK were supported by a collaborative research
grant from the US National Science Foundation (DEB-1556651).
BJE was supported by National Science Foundation award
Frontiers in Ecology and Evolution | www.frontiersin.org 10 December 2018 | Volume 6 | Article 219
Echeverría-Londoño et al. New World Functional Diversity
DEB-1457812 and Macrosystems-1065861.CV was supported
by the European Research Council (Grant ERC-StG-2014-
639706-CONSTRAINTS) and by the French Foundation for
Research on Biodiversity (FRB; www.fondationbiodiversite.fr)
in the context of the CESAB project Causes and consequences
of functional rarity from local to global scales. J-CS considers
this work a contribution to his VILLUM Investigator project
Biodiversity Dynamics in a Changing World funded by VILLUM
FONDEN (grant 16549). SKW was supported by the Strategic
Science Investment Fund of the New Zealand Ministry of
Business, Innovation and Employment’s Science and Innovation
Group.
ACKNOWLEDGMENTS
We thank Dan Griffith and two reviewers for their constructive
criticism which greatly improved this manuscript. We also thank
all BIEN data contributors (see http://bien.nceas.ucsb.edu/bien/
data-contributors/ for a full list).
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fevo.
2018.00219/full#supplementary-material
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Conflict of Interest Statement: The authors declare that the research was
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Frontiers in Ecology and Evolution | www.frontiersin.org 12 December 2018 | Volume 6 | Article 219
... Niche-based theory offers an adaptive explanation for the variability in trait integration through the environmental selection hypothesis (Lamanna et al. 2014). Under this hypothesis, climatic and edaphic gradients are the major controls of trait integration, niche space size, and magnitude of functional diversity within and across communities (Wright et al. 2006;Boucher et al. 2013;Lamanna et al. 2014;Echeverría-Londoño et al. 2018). From benign to stressful environments, or from high to low productivity ecosystems, resources become scarcer and abiotic conditions become more severe or variable, constraining the community's viable niche space size. ...
... Studies in population ecology also have found that populations located at the edge of the species' niche exhibit high trait integration due to energetic and biophysical constraints in response to environmental stress (Damián et al. 2019;Carvalho et al. 2020). This would explain the negative relationship between niche space size and trait integration, as well as why in more constrained niche spaces the number of species is reduced (Lamanna et al. 2014;Echeverría-Londoño et al. 2018). It has been therefore hypothesized that the effects of abiotic gradients on species richness may occur indirectly through effects on the strength of trait integration because species richness is first conditioned by the community's niche space size and trait integration and ultimately by the environment gradient (Dwyer and Laughlin 2017;He et al. 2021). ...
... Macroecological studies have revealed that the size of niche space and the magnitude of trait diversity are usually higher in benign humid biomes and tend to decrease in more stressful Mediterranean and temperate/cold biomes (Echeverría-Londoño et al. 2018;Li et al. 2018). This broad-scale pattern remains at regional scales if the studied region encompasses a gradient long enough to characterize different climatic zones (de la Riva et al. 2018;Costa-Saura et al. 2019). ...
Article
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Environmental gradients are known to drive changes in mean trait values, but changes in the trait integration strength across local communities are less well understood, particularly with regard to possible links with species richness variation. Here, we tested if climate, soil, and topography gradients drive species richness indirectly via constraints on trait integration in the Atlantic Forest of South America. We evaluated seven traits (from leaf, wood, seed, and plant size) of 1456 species occurring across 84 local communities. Generalized least square models and a path model were applied to test direct and indirect relationships. Correlations were higher between leaf traits (average r = 0.28) and lower when other traits were included (average r = 0.16). In line with this result, species richness was related to a multivariate index of interspecific trait integration (ITI) computed for leaf traits, but not to the ITI for all the seven traits. Abiotic gradients influenced species richness both directly and indirectly through the leaf trait integration. A total of 33% and 26% of the variation in species richness and ITI, respectively, were explained by the models, with climatic conditions showing higher contribution than topographic and edaphic factors. These results support a significant but reduced environmental selection role behind the trait-based community assembly and may suggest that other processes are involved in the constrain of trait integration at larger spatial scales. In addition, different directional trends in trait–trait relationships across local communities suggest that global trait relationships may not necessarily hold at local contexts.
... The majority of studies on taxonomic, phylogenetic and functional diversities focus on the differences among them and their relationships with environmental conditions, such as in vertebrates (Lamoreux et al., 2006), birds (Safi et al., 2011;Mazel et al., 2014;Sobral et al., 2014), and freshwater fish communities (Strecker et al., 2011), but see one example for plants Echeverría-Londoño et al. (2018). From an evolutionary viewpoint, the spatial mismatch among the facets of biodiversity is related to the way the ecological niches of species evolve. ...
... On the other hand, areas such as in the transition between Amazonia, the Cerrado, and the Caatinga showed low functional diversity, but high phylogenetic diversity considering ancient relationships (MPD; see Figures 1B,D), and recent relationships in the Guiana Shield (MNTD; Figures 1C,E). These opposing results do not support our expectations, as taxonomic and functional plant diversity was found to be highly congruent in space (Echeverría-Londoño et al., 2018). We suggest the lower level of functional diversity compared with both taxonomic and phylogenetic found here is linked to the fact that natural transition areas among ecosystems are more prone to ecological selection, filtering certain traits unfit for these higher level of stress (e.g., drought, increased solar radiation; Metcalfe et al., 2020). ...
Article
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Biodiversity can be quantified by taxonomic, phylogenetic, and functional diversity. Current evidence points to a lack of congruence between the spatial distribution of these facets due to evolutionary and ecological constraints. A lack of congruence is especially evident between phylogenetic and taxonomic diversity since the name and number of species are an artificial, yet commonly used, way to measure biodiversity. Here we hypothesize that due to evolutionary constraints that link phylogenetic and functional diversity, areas with higher phylogenetic and functional diversity will be spatially congruent in Neotropical cocosoid palms, but neither will be congruent with areas of high taxonomic diversity. Also, we hypothesize that any congruent pattern differs between rainforests and seasonally dry forests, since these palms recently colonized and diversified in seasonally dry ecosystems. We use ecological niche modeling, a phylogenetic tree and a trait database to test the spatial congruence of the three facets of biodiversity. Taxonomic and phylogenetic diversity were negatively correlated. Phylogenetic and functional diversity were positively correlated, even though their spatial congruence was lower than expected at random. Taken together, our results suggest that studies focusing solely on large-scale patterns of taxonomic diversity are missing a wealth of information on diversification potential and ecosystem functioning.
... Describing and explaining distributions of species' traits is crucial for understanding how ecosystem characteristics vary in space-functional biogeography is the study of the geographic distribution of trait diversity across organisational levels (sensu Violle et al. 2014). Plants play a central role in driving ecosystem functions, and there is an increasing interest in mapping functional traits of plant assemblies (Reichstein et al. 2014, Newbold et al. 2015, Violle et al. 2015, Funk et al. 2017, Bruelheide et al. 2018, Echeverría-Londoño et al. 2018. ...
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Traditionally, biogeography has described the distribution of species. But as plant functional traits and functional diversity underpin ecosystem dynamics, understanding drivers of functional diversity at biogeographical scales is essential to understand spatial variation in ecosystem characteristics, particularly in light of ongoing environmental changes. Here we investigate geographic patterns of functional diversity and ‐traits of the Norwegian flora. We explore whether climate, land‐use or glacial history are important drivers of functional diversity. We combine species occurrence records and assemblage‐means of functional traits to assess the spatial distribution of functional traits and ‐diversity of native vascular plants in Norway in a 20 × 20 km grid. We use multiple‐model inference to identify which environmental factors contribute the most in explaining the spatial patterns of trait distributions and functional diversity. Additionally, we use the constructed models to predict potential changes in distributions of traits and functional diversity given different climate change scenarios. Both individual traits and functional diversity display clear geographic patterns, predictable by climate, landscape and glacial history. Traits related to plant size and growth peak in warmer areas and are predicted to increase in the future, as is functional richness and dispersion. In contrast, functional evenness peaks in northern regions and is predicted to decrease in the future. The different environmental drivers vary in degree of importance, effect sizes and ‐directions on the assemblage‐averaged functional traits and ‐diversity. This underlines the importance of multiple drivers in determining plant assemblage functionality. In the face of climate‐ and land‐use change, Norway is expected to become warmer, wetter and experience a substantial increase in anthropogenic land‐uses, such as increased urbanisation. In turn, the functional composition of the Norwegian flora is predicted to shift towards tall, woody, fast‐growing species.
... These biomes are often seen as independent evolutionary arenas (Nürk et al., 2020;Ringelberg et al., 2020). This biome concept reflects that environmental pressures select for species with similar functional attributes (Echeverría-Londoño et al., 2018), further implying that colonisation of contrasting biomes can promote speciation (Pennington & Dick, 2010). For example many genera with species typical of seasonally dry tropical forest and savanna also contain species from rainforest (Pennington et al., 2006;Pennington et al., 2000), suggesting that biome-switching has driven ecological speciation. ...
Article
Phenotypes promoting dispersal over ecological timescales may have macroevolutionary consequences, such as long‐distance dispersal and diversification. However, whether dispersal traits explain the distribution of pantropical plant groups remains unclear. Here we reconstruct the biogeographical history of a tree clade to assess whether seed dispersal traits and biome‐switching explain the clade’s pantropical distribution. Pantropical. The Pterocarpus clade (Leguminosae/Fabaceae). We sequenced 303 nuclear loci using target capture and generated a time‐calibrated phylogenomic tree. We also generated a corroborative time‐calibrated phylogenetic tree from data‐mined Sanger‐sequencing data. We then collated distribution data and seed dispersal morphology traits to compare trait‐dependent and trait‐independent biogeographical models, allowing us to infer whether dispersal traits influenced Pterocarpus’ spatio‐temporal evolution. Finally, using the results of these model tests, we estimated the ancestral ranges and biomes of Pterocarpus species to better understand their biogeographical history, and assessed the degree and direction of biome‐switching over the course of their diversification. We recovered well‐supported phylogenetic relationships within Pterocarpus, within which there were two subclades – one neotropical and the other palaeotropical. Our divergence date estimates suggested that Pterocarpus diversified from around 12 Ma, during the Miocene. Trait‐dependent biogeographical models were rejected for both range and biome evolution within Pterocarpus, but models including dispersal were supported. Pterocarpus’ ancestral node shared a range across the new‐world and old‐world tropics, followed by divergence into palaeotropical and neotropical clades. Biome‐switching occurred most frequently into rainforest and grassland. Our analyses suggest that Pterocarpus underwent infrequent cross‐continental dispersal and establishment into novel biomes. While this was minimally impacted by seed dispersal traits, biome‐switching following long‐distance dispersal and climate change have played an important role in diversification within Pterocarpus since the Miocene. Indeed, rare events of long‐distance dispersal likely explain the wide distributions of many pantropical plant species.
... In contrast, forests have deeper roots to access water in deeper layers and are more resilient to extreme droughts, resulting in relatively weaker asymmetries (Jackson et al., 1996;Stuart-Haëntjens et al., 2018). In the meantime, a higher functional diversity in humid tropical and temperate forests (Echeverría-Londoño et al., 2018;Stevens et al., 2003) could alleviate drought effects by a "compensatory effect" where reducing productivity in one functional group increases the growth in another (Flach et al., 2018;Hao et al., 2013). Therefore, ENF and EBF could be more resistant to dry extremes, showing less negative AI values than deciduous forests. ...
Article
Understanding gross primary productivity (GPP) response to precipitation (PPT) changes is essential for predicting land carbon uptake under increasing PPT variability and extremes. Previous studies found that ecosystem GPP may have an asymmetric response to PPT changes, leading to the inconsistency of GPP gains in wet years compared to GPP declines in dry years. However, it is unclear how the asymmetric responses vary among vegetation types and under different PPT variabilities. This study evaluated the global patterns of asymmetries of GPP response to different PPT changes using two state-of-science global GPP datasets. The result shows that under mild PPT changes (|ΔPPT| ≤ 25%), grasslands, savannas, shrublands, and tundra show positive asymmetric responses (i.e., larger GPP gains in wet years than GPP losses in dry years), while other vegetation types show negative asymmetric responses (i.e., larger GPP losses in dry years than GPP gains in wet years). Conversely, all vegetation types show negative GPP asymmetric responses to moderate (25% < |ΔPPT| ≤ 50%) and extreme (|ΔPPT| > 50%) PPT changes. Thus, we propose a new non-linear asymmetric GPP-PPT model that incorporates three modes with regards to vegetation types. Meanwhile, we found that the spatial patterns of asymmetry were mainly driven by PPT amount and variability. Stronger and negative asymmetries were found in areas with smaller PPT amount and variability, while positive asymmetries were found in areas with higher PPT variability. These findings promote our understanding of carbon dynamics under increased PPT variability and extremes and provide new insights for land models to better predict future carbon uptake and its feedback to climate change.
... We classified species distribution in ten areas: southern Africa deserts and xeric scrublands (F), Argentinean Monte (O), Atacama Desert and neighboring Chilean xeric scrublands (T), Sechura desert in the Peruvian coast (S), Andean dry forests (D), Chiquitano dry forests in Bolivia (C), Mesoamerican dry forests (M), dry forests in the Caribbean coast of Colombia (B), Caatinga dry forest in Brazil (I), and the Galapagos Islands (G) (Figure 2). Most of these areas are clearly delimited by geographic barriers such as oceans or mountain ranges, or correspond to well-recognized ecoregions or phytogeographic units [37,47]. ...
Article
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Event-based biogeographic methods, such as dispersal-extinction-cladogenesis, have become increasingly popular for attempting to reconstruct the biogeographic history of organisms. Such methods employ distributional data of sampled species and a dated phylogenetic tree to estimate ancestral distribution ranges. Because the input tree is often a single consensus tree, uncertainty in topology and age estimates are rarely accounted for, even when they may affect the outcome of biogeographic estimates. Even when such uncertainties are taken into account for estimates of ancestral ranges, they are usually ignored when researchers compare competing biogeographic hypotheses. We explore the effect of incorporating this uncertainty in a biogeographic analysis of the 21 species of sand spiders (Sicariidae: Sicarius) from Neotropical xeric biomes, based on a total-evidence phylogeny including a complete sampling of the genus. Using a custom R script, we account for uncertainty in ages and topology by estimating ancestral ranges over a sample of trees from the posterior distribution of a Bayesian analysis, and for uncertainty in biogeographic estimates by using stochastic maps. This approach allows for counting biogeographic events such as dispersal among areas, counting lineages through time per area, and testing biogeographic hypotheses, while not overestimating the confidence in a single topology. Including uncertainty in ages indicates that Sicarius dispersed to the Galapagos Islands when the archipelago was formed by paleo-islands that are now submerged; model comparison strongly favors a scenario where dispersal took place before the current islands emerged. We also investigated past connections among currently disjunct Neotropical dry forests; failing to account for topological uncertainty underestimates possible connections among the Caatinga and Andean dry forests in favor of connections among Caatinga and Caribbean + Mesoamerican dry forests. Additionally, we find that biogeographic models including a founder-event speciation parameter (“+J”) are more prone to suffer from the overconfidence effects of estimating ancestral ranges using a single topology. This effect is alleviated by incorporating topological and age uncertainty while estimating stochastic maps, increasing the similarity in the inference of biogeographic events between models with or without a founder-event speciation parameter. We argue that incorporating phylogenetic uncertainty in biogeographic hypothesis-testing is valuable and should be a commonplace approach in the presence of rogue taxa or wide confidence intervals in age estimates, and especially when using models including founder-event speciation.
... Variation in these niche-based processes may lead to functional differences among the local communities at larger spatial scale if the environment is filtering groups of species that are functionally similar (Hérault 2007). Thereby, environmental filtering through climate and habitat characteristics may select for a set of discrete common characteristics that differ between biogeographical regions (Echeverría-Londoño et al. 2018;Li et al. 2018). ...
Article
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Species co-occurrences in local communities can arise independent or dependent on species’ niches. However, the role of niche-dependent processes has not been thoroughly deciphered when generalized to biogeographical scales, probably due to combined shortcomings of data and methodology. Here, we explored the influence of environmental filtering and limiting similarity, as well as biogeographical processes that relate to the assembly of species’ communities and co-occurrences. We modelled jointly the occurrences and co-occurrences of 1016 tropical tree species with abundance data from inventories of 574 localities in eastern South America. We estimated species co-occurrences as raw and residual associations with models that excluded and included the environmental effects on the species’ co-occurrences, respectively. Raw associations indicate co-occurrence of species, whereas residual associations indicate co-occurrence of species after accounting for shared responses to environment. Generally, the influence of environmental filtering exceeded that of limiting similarity in shaping species’ co-occurrences. The number of raw associations was generally higher than that of the residual associations due to the shared responses of tree species to the environmental covariates. Contrary to what was expected from assuming limiting similarity, phylogenetic relatedness or functional similarity did not limit tree co-occurrences. The proportions of positive and negative residual associations varied greatly across the study area, and we found a significant tendency of some biogeographical regions having higher proportions of negative associations between them, suggesting that large-scale biogeographical processes limit the establishment of trees and consequently their co-occurrences.
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The knowledge of biomes as large-scale ecosystem units has benefited from advances in the ecological and evolutionary sciences. Despite this, a universal biome classification system that also allows a standardized nomenclature has not yet been achieved. We propose a comprehensive and hierarchical classification method and nomenclature to define biomes based on a set of bioclimatic variables and their corresponding vegetation structure and ecological functionality. This method uses three hierarchical biome levels: Zonal biome (Macrobiome), Biome and Regional biome. Biome nomenclature incorporates both bioclimatic and vegetation characterization (i.e. formation). Bioclimate characterization basically includes precipitation rate and thermicity. The description of plant formations encompasses vegetation structure, physiognomy and foliage phenology. Since the available systems tend to underestimate the complexity and diversity of tropical ecosystems, we have tested our approach in the biogeographical area of the Neotropics. Our proposal includes a bioclimatic characterization of the main 16 Neotropical plant formations identified. This method provides a framework that (1) enables biome distribution and changes to be projected from bioclimatic data; (2) allows all biomes to be named according to a globally standardized scheme; and (3) integrates various ecological biome approaches with the contributions of the European and North American vegetation classification systems. Taxonomic reference : Jørgensen et al. (2014). Dedication : This work is dedicated to the memory of and in homage to Prof. Dr. Salvador Rivas-Martínez.
Thesis
Invasions by plant species are an increasing threat which is reducing species diversity across regions, changing community composition and altering ecosystems functioning. While most investigations on impacts of exotic plants are conducted in their areas of introduction, the study of the assembly of exotic species in their native areas is emerging as a framework to better understand their roles in the invaded communities. In this regard, functional traits reflect the ecological strategy of plants and their interactions with coexistent species and the environment, therefore plant traits are a key tool to understand the role of exotic plant species in the structure of their communities. One of the main objectives of this thesis is to identify the functional strategies of exotic species in invaded Mediterranean ecosystems and disentangle the rules that govern the assembly of invaded communities. For this, we analysed traits from several plant organs (i.e. leafs, seeds, roots) of 285 species from two vegetation types (woodlands and grasslands) at different spatial scales of resolution (i.e. Biome, environmental gradients, communities, plants).
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Nonlinear relationships between species and their environments are believed common in ecology and evolution, including during angiosperms’ rise to dominance. Early angiosperms are thought of as woody evergreens restricted to warm, wet habitats. They have since expanded into numerous cold and dry places. This expansion may have included transitions across important environmental thresholds. To understand linear and nonlinear relationships between angiosperm structure and biogeographic distributions, we integrated large datasets of growth habits, conduit sizes, leaf phenologies, evolutionary histories, and environmental limits. We consider current‐day patterns and develop a new evolutionary model to investigate processes that created them. The macroecological pattern was clear: herbs had lower minimum temperature and precipitation limits. In woody species, conduit sizes were smaller in evergreens and related to species’ minimum temperatures. Across evolutionary timescales, our new modeling approach found conduit sizes in deciduous species decreased linearly with minimum temperature limits. By contrast, evergreen species had a sigmoidal relationship with minimum temperature limits and an inflection overlapping freezing. These results suggest freezing represented an important threshold for evergreen but not deciduous woody angiosperms. Global success of angiosperms appears tied to a small set of alternative solutions when faced with a novel environmental threshold.
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Premise of the Study: Large phylogenies can help shed light on macroevolutionary patterns that inform our understanding of fundamental processes that shape the tree of life. These phylogenies also serve as tools that facilitate other systematic, evolutionary, and ecological analyses. Here we combine genetic data from public repositories (GenBank) with phylogenetic data (Open Tree of Life project) to construct a dated phylogeny for seed plants. Methods: We conducted a hierarchical clustering analysis of publicly available molecular data for major clades within the Spermatophyta. We constructed phylogenies of major clades, estimated divergence times, and incorporated data from the Open Tree of Life project, resulting in a seed plant phylogeny. We estimated diversification rates, excluding those taxa without molecular data. We also summarized topological uncertainty and data overlap for each major clade. Key Results: The trees constructed for Spermatophyta consisted of 79,881 and 353,185 terminal taxa; the latter included the Open Tree of Life taxa for which we could not include molecular data from GenBank. The diversification analyses demonstrated nested patterns of rate shifts throughout the phylogeny. Data overlap and inference uncertainty show significant variation throughout and demonstrate the continued need for data collection across seed plants. Conclusions: This study demonstrates a means for combining available resources to construct a dated phylogeny for plants. However, this approach is an early step and more developments are needed to add data, better incorporating underlying uncertainty, and improve resolution. The methods discussed here can also be applied to other major clades in the tree of life.
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Despite several recent efforts to map plant traits and to identify their climatic drivers, there are still major gaps. Global trait patterns for major functional groups, in particular, the differences between woody and herbaceous plants, have yet to be identified. Here, we take advantage of big data efforts to compile plant species occurrence and trait data to analyse the spatial patterns of assemblage means and variances of key plant traits. We tested whether these patterns and their climatic drivers are similar for woody and herbaceous plants. New World (North and South America). Using the largest currently available database of plant occurrences, we provide maps of 200 × 200 km grid-cell trait means and variances for both woody and herbaceous species and identify environmental drivers related to these patterns. We focus on six plant traits: maximum plant height, specific leaf area, seed mass, wood density, leaf nitrogen concentration and leaf phosphorus concentration. For woody assemblages, we found a strong climate signal for both means and variances of most of the studied traits, consistent with strong environmental filtering. In contrast, for herbaceous assemblages, spatial patterns of trait means and variances were more variable, the climate signal on trait means was often different and weaker. Trait variations for woody versus herbaceous assemblages appear to reflect alternative strategies and differing environmental constraints. Given that most large-scale trait studies are based on woody species, the strikingly different biogeographic patterns of herbaceous traits suggest that a more synthetic framework is needed that addresses how suites of traits within and across broad functional groups respond to climate.
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Phylogenetic structure of regional species assemblages is determined by environmental conditions and biogeographical history. Typically, assemblages are thought to become increasingly clustered at higher latitudes, because relatively few clades can tolerate low temperatures. However, numerous other patterns can produce phylogenetic structure. Here, we derive and test four hypotheses for phylogenetic structure of all angiosperms and five major angiosperm clades in North America. These are as follows: (a) angiosperms assemblages at higher latitudes are more phylogenetically clustered; (b) stronger phylogenetic clustering occurs in the drier climates of the west; (c) species are more closely related in the warm, dry southwest than in the cooler, wetter northwest; and (d) latitudinal patterns of phylogenetic structure in central North America are intermediate between those of the east and west.
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There is an urgent need for large-scale botanical data to improve our understanding of community assembly, coexistence, biogeography, evolution, and many other fundamental biological processes. Understanding these processes is critical for predicting and handling human-biodiversity interactions and global change dynamics such as food and energy security, ecosystem services, climate change, and species invasions. The Botanical Information and Ecology Network (BIEN) database comprises an unprecedented wealth of cleaned and standardised botanical data, containing roughly 81 million occurrence records from c. 375,000 species, c. 915,000 trait observations across 28 traits from c. 93,000 species, and co-occurrence records from 110,000 ecological plots globally, as well as 100,000 range maps and 100 replicated phylogenies (each containing 81,274 species) for New World species. Here, we describe an r package that provides easy access to these data. The bien r package allows users to access the multiple types of data in the BIEN database. Functions in this package query the BIEN database by turning user inputs into optimised PostgreSQL functions. Function names follow a convention designed to make it easy to understand what each function does. We have also developed a protocol for providing customised citations and herbarium acknowledgements for data downloaded through the bien r package. The development of the BIEN database represents a significant achievement in biological data integration, cleaning and standardization. Likewise, the bien r package represents an important tool for open science that makes the BIEN database freely and easily accessible to everyone. © 2017 The Authors. Methods in Ecology and Evolution
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The species population density–range size relationship posits that locally abundant species are widely distributed. However, this proposed pattern has been insufficiently tested. The few tests conducted were usually limited in scale and gave conflicting results. We tested the generality of the positive population density–range size relationship. We then studied whether similar environmental niche requirements are correlated with range size and with population density to search for mechanisms driving the hypothesized link between population density and range size. Worldwide. We collected data on population density, range size and environmental niche for a global dataset of 192 lizard, 893 bird and 350 mammal species. Assessing the relationship between population density and range size and environmental niche parameters, we corrected for phylogenetic relationships, body mass, diet and study area. Our findings reveal that density had a weak negative correlation with bird range size and was unrelated to lizard and mammal range size. These trends were consistent at the global scale and across the biogeographical realms. Range size was related to relatively similar environmental niche parameters in all groups. Population density, however, was explained by taxon-specific factors and was therefore unrelated to range size by common causation. We suggest that the positive relationship between population density and range size identified in previous studies might be an artefact arising through incomplete sampling of range sizes. Our results indicate that the mechanisms shaping population density and range size may be independent.
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Emphasis has been put in recent ecological research on investigating phylogenetic, functional and taxonomic facets of biological diversity. While a flourishing number of indices has been proposed for assessing functional diversity, surprisingly few options are available to characterize functional rarity. Functional rarity can play a key role in community and ecosystem dynamics. We introduce here the funrar R package to quantify functional rarity based on species trait differences and species frequencies at local and regional scales. Because of the increasing availability of big datasets in macroecology and biogeography, we optimized funrar to work with large datasets of thousands of species and sites. We illustrate the use of the package to investigate the functional rarity of North and Central American mammals. The package is available on CRAN: https://cran.r-project.org/web/packages/funrar/index.html