pollinator adaptation and the evolution of floral nectar ... · composition of nectar among plants...
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Pollinator adaptation and the evolution of floral nectar sugarcomposition
S. ABRAHAMCZYK*, M. KESSLER† , D . HANLEY‡ , D . N. KARGER† , M. P. J . M €ULLER† ,A . C. KNAUER† , F . KELLER§ , M. SCHWERDTFEGER¶ & A. M. HUMPHREYS**††*Nees Institute for Plant Biodiversity, University of Bonn, Bonn, Germany
†Institute of Systematic and Evolutionary Botany, University of Zurich, Zurich, Switzerland
‡Department of Biology, Long Island University - Post, Brookville, NY, USA
§Institute of Plant Science, University of Zurich, Zurich, Switzerland
¶Albrecht-v.-Haller Institute of Plant Science, University of Goettingen, Goettingen, Germany
**Department of Life Sciences, Imperial College London, Berkshire, UK
††Department of Ecology, Environment and Plant Sciences, University of Stockholm, Stockholm, Sweden
Keywords:
asterids;
fructose;
glucose;
phylogenetic conservatism;
phylogenetic constraint;
pollination syndrome;
sucrose.
Abstract
A long-standing debate concerns whether nectar sugar composition evolves
as an adaptation to pollinator dietary requirements or whether it is ‘phylo-
genetically constrained’. Here, we use a modelling approach to evaluate the
hypothesis that nectar sucrose proportion (NSP) is an adaptation to pollina-
tors. We analyse ~ 2100 species of asterids, spanning several plant families
and pollinator groups (PGs), and show that the hypothesis of adaptation
cannot be rejected: NSP evolves towards two optimal values, high NSP for
specialist-pollinated and low NSP for generalist-pollinated plants. However,
the inferred adaptive process is weak, suggesting that adaptation to PG only
provides a partial explanation for how nectar evolves. Additional factors are
therefore needed to fully explain nectar evolution, and we suggest that
future studies might incorporate floral shape and size and the abiotic envi-
ronment into the analytical framework. Further, we show that NSP and PG
evolution are correlated – in a manner dictated by pollinator behaviour.
This contrasts with the view that a plant necessarily has to adapt its nectar
composition to ensure pollination but rather suggests that pollinators adapt
their foraging behaviour or dietary requirements to the nectar sugar compo-
sition presented by the plants. Finally, we document unexpectedly sucrose-
poor nectar in some specialized nectarivorous bird-pollinated plants from
the Old World, which might represent an overlooked form of pollinator
deception. Thus, our broad study provides several new insights into how
nectar evolves and we conclude by discussing why maintaining the concep-
tual dichotomy between adaptation and constraint might be unhelpful for
advancing this field.
Introduction
Understanding the evolution of floral rewards is central
to understanding the evolution of plant–pollinator inter-actions. Nectar is the main floral reward provided by the
vast majority of modern angiosperms (70–80%,
extracted from Heywood et al., 2007), but despite coad-
aptation between plants and their animal pollinators
being thought to be one of the key mechanisms
Correspondence: Stefan Abrahamczyk, Nees Institute for Plant
Biodiversity, University of Bonn, Meckenheimer Allee 170, 53115
Bonn, Germany.
Tel.: +49 228 734649, fax:+49 228 733120; e-mail: stefan.
Aelys M. Humphreys, Department of Ecology, Environment and Plant
Sciences, University of Stockholm, SE–10691, Stockholm, Sweden.
Tel.: +46 (0)8 163 771; e-mail: [email protected]
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doi: 10.1111/jeb.12991
responsible for angiosperm evolution and floral diversifi-
cation (Stebbins, 1970; Harrison et al., 1999), our under-
standing of the evolution of floral nectar remains poor.
On the one hand, it has been suggested that the chemi-
cal composition of nectar, an aqueous solution compris-
ing primarily the monosaccharides glucose and fructose
and the disaccharide sucrose (Baker & Baker, 1982), is
as an adaptation to the nutritional constraints or prefer-
ences of a plant’s pollinator(s) as well as to flower mor-
phology (Baker & Baker, 1975, 1982, 1983a). On the
other hand, the sugar composition of floral nectar has
been found to be relatively invariable within plant
clades, with any interspecific differences being indepen-
dent of the plants’ main pollinators (e.g. van Wyk, 1993;
Galetto et al., 1998; Nicolson & van Wyk, 1998; Galetto
& Bernadello, 2003; Rodr�ıguez-Ria~no et al., 2014). These
seemingly contradictory perspectives call into question
our understanding of what drives the evolution of floral
rewards and, in particular, floral nectar.
Early studies documented convergence in the sugar
composition of nectar among plants pollinated by the
same pollinator group (PG; Baker & Baker, 1982,
1983a). Various groups of insects (bees, wasps, butter-
flies, moths and some groups of flies) and several
groups of vertebrates (e.g. hummingbirds, sunbirds,
honeyeaters, phyllostomid and pteropodid bats) are
obligate nectar feeders and, by visiting flowers regu-
larly, often also act as pollinators (referred to as special-
ists; Fleming & Muchhala, 2008). In addition, a
surprising variety of unspecialised vertebrates and
insects (songbirds, geckos, mice, kinkajous, short-ton-
gued flies and some groups of beetles) are known to
feed on nectar occasionally (referred to as generalists,
e.g. van Tets & Nicolson, 2007; Nicolson, 2002; Hansen
et al., 2006; Johnson & Nicolson, 2008). These animals
lack special morphological adaptations to feed on nec-
tar, but are still known to be effective pollinators. How-
ever, their nutritional requirements differ from those of
nectar-feeding specialists with respect to sugar concen-
tration (in solution) or composition (relative contribu-
tion of sucrose and the two hexoses, fructose and
glucose, to total sugar content). Although most special-
ist PGs, such as moths, bees or hummingbirds, prefer
nectar with a high sucrose proportion (Nicolson et al.,
2007; Johnson & Nicolson, 2008), nectar-feeding bats
prefer a low sucrose proportion (Baker et al., 1998).
Similarly, sucrose-rich nectar cannot be digested as effi-
ciently by, or is even toxic to, some generalists
(Mart�ınez del Rio, 1990; Mart�ınez del Rio et al., 1992).
Therefore, it has frequently been proposed that inter-
specific differences in nectar sugar composition and
concentration, especially in nectar sucrose proportion
(NSP), reflect adaptations to the dietary requirements
of different PGs (e.g. Heynemann, 1983; Mart�ınez del
Rio et al., 1992; Baker et al., 1998).
In addition, there is a long-recognized correlation
between floral shape and NSP, such that deep or
tubular flowers tend to have high NSP and shallow
flowers tend to have low NSP (high hexose proportion;
Percival, 1961). This correlation has been attributed to
the environment, because open flowers run greater risk
of nectar evaporation, rendering them useless to polli-
nators (Baker & Baker, 1983a). Hexose solutions have
higher osmolarity, and therefore lower evaporation
rates, than sucrose solutions, and this is thought to
explain the correlation between shallow flowers and
nectars with a high proportion of hexose (Nicolson
et al., 2007). However, high-hexose nectars also tend to
require more water. In Mediterranean regions, there is
a predominance of tubular flowers with high-sucrose
nectars, suggested to be the result of selection against
high-hexose nectars in a warm, dry climate (Petanidou,
2005; Nicolson et al., 2007). This correlation reflects the
physical constraints of sugar solutions themselves, but
it is also thought to constitute evidence for adaptation
to pollinators because a plant will only be regularly vis-
ited by efficient pollinators, whose requirements of suf-
ficiently dilute, easily accessible nectar are fulfilled
(Nicolson et al., 2007).
Given the obvious adaptive advantage of a good fit
between floral traits and animal pollinators, it is sur-
prising that more recent studies of plant species polli-
nated by different PGs have failed to find NSP values
characteristic of the individual PGs (e.g. van Wyk,
1993; Galetto et al., 1998; Nicolson & van Wyk, 1998;
Galetto & Bernadello, 2003). Instead, similar NSP has
been recorded for closely related species in the same
plant family (e.g. in Gesneriaceae, Proteaceae and Scro-
phulariaceae), and in aloes and relatives, NSP has been
found to be conserved within but not among genera,
irrespective of PG (e.g. van Wyk et al., 1993; Nicolson
& Thornburg, 2007; Rodr�ıguez-Ria~no et al., 2014).
These findings have led to the suggestion that there is a
‘phylogenetic constraint’ (sic) on the adaptation of NSP
to pollinators (Galetto & Bernadello, 2003; Thornburg,
2007; Rodr�ıguez-Ria~no et al., 2014). For example, it has
been suggested that the differences in NSP between
plants pollinated by hummingbirds and passerine birds
might be because they belong to different plant clades
rather than due to any innate differences in the
requirements of the pollinators themselves (Nicolson &
Thornburg, 2007).
Considerable attention has been paid to the question
of what causes interspecific differences in the relative
proportions of fructose, glucose and sucrose in nectar.
To date, the debate has generally been centred on a
perceived dichotomy between adaptation to pollinators
and phylogenetic constraints (e.g. Schmidt-Lebuhn
et al., 2006; Nicolson et al., 2007). We are not aware of
any explicit, biological mechanism generating the con-
straint being proposed and believe that focus on the
perceived dichotomy between adaptation and conser-
vatism may have hampered progress into understand-
ing of how floral nectar evolves. In general,
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Evolution of floral nectar sugar composition 113
phylogenetic conservatism or constraint1 is often
invoked to explain the lack of variation among close
relatives or the tendency of closely related species to
retain their ancestral state over time (e.g. Wiens & Gra-
ham, 2005; Cooper et al., 2010; Wiens et al., 2010; Crisp
& Cook, 2012). However, this conveys only that there
is limited trait variation among close relatives, not what
the causal explanation for the observed pattern might
be (Westoby et al., 1995; Blomberg & Garland, 2002;
Losos, 2011). In the case of nectar, documentation of
phylogenetic conservatism in sugar composition sug-
gests limited variation among closely related plant spe-
cies, irrespective of their pollinators, but provides no
insight into how floral nectar evolves, nor does it con-
stitute evidence for or against adaptation (Leroi et al.,
1994; Blomberg & Garland, 2002; Ackerly, 2003, 2004;
Crisp & Cook, 2012). Both stasis and change can result
from both adaptive and nonadaptive processes; for
example, stabilizing selection provides an adaptive
explanation for the pattern of stasis and retention of
the ancestral state does not mean that the trait in ques-
tion is not an adaptation to something (Westoby et al.,
1995; Ackerly, 2004; Losos, 2011; Hansen, 2014). For
instance, if a correlation between NSP and PG was
rejected, the hypothesis that NSP evolves as an adapta-
tion to PG might be rejected, but that would not pre-
clude that nectar sugar composition was an adaptation
to something else, say, corolla shape and size (Nicolson,
2002; Witt et al., 2013). Alternatively, a nonadaptive
hypothesis might be favoured if change in NSP was
found to be stochastic with respect to any environmen-
tal variable to which it was hypothesized to be an adap-
tation, for example if it were found to be drifting
according to the allometric constraints of floral shape
and size or the physical constraints of the environment.
Thus, mechanistic explanations do not require infer-
ence of conservatism and can be distinguished using
comparative methods, by setting up testable hypotheses
to be evaluated in a model comparison framework
(Hansen, 1997; Butler & King, 2004). Here, we use this
approach to evaluate the hypothesis that nectar sugar
composition, in particular NSP, is an adaptation to pol-
linator preferences. We compile a data set that is
unprecedented in scope for this purpose, with nectar
sugar composition, pollinator and phylogenetic data
broadly sampled for the asterids, a major angiosperm
clade of about 80 000 species (Bremer, 2009), including
the carrots, daisies, heathers and mints. We define the
sugar composition of nectar as the trait and PG as the
environment. We then test for a correlation between
the trait and the environment, such that there is con-
vergence of the trait in relation to the environment
(i.e. convergence of nectar sugar composition for plants
pollinated by the same PG; Leroi et al., 1994; Ackerly,
2004) and such that an adaptive shift in the trait is
associated with a shift in function (i.e. a new pollina-
tion syndrome; Hansen, 1997; Butler & King, 2004).
We also explore the nature of the hypothesized adapta-
tion by asking whether the trait or the environment
changes first (Pagel, 1994; Ackerly, 2004)?
Pollinators are thought mainly to be sensitive to the
proportion of total sugar constituted by sucrose (NSP),
although that by fructose (NFP) and that by glucose
(NGP) are thought not to provide reliable evidence of
pollination syndromes (Baker et al., 1998). Based on
this, we analysed the proportional content of each
sugar in turn to evaluate support for the following
hypotheses: H1: nectar sucrose is an adaptation to polli-
nators. This would be supported if a correlation
between NSP and PG cannot be rejected, if there is evi-
dence that adaptation to the environment is rapid and
accurate and if change between NSP and PG is corre-
lated, such that change in PG (the environment) pre-
cedes or accompanies change in NSP (the trait); and
H2: nectar fructose and glucose are not adaptations to
pollinators. This would be supported if a correlation
between the trait (NFP or NGP) and the environment
(PG) is rejected or if there is evidence that shifts in the
trait in relation to the environment are slow and
achieved by stochastic, rather than adaptive, change.
Materials and methods
Nectar data
We compiled nectar sugar composition data for asterids
using published records and, focusing on previously
neglected taxa (e.g. from the Old World tropics), col-
lected and analysed new nectar samples for this study.
We focused on the proportional content of the three
main nectar sugars (fructose, glucose and sucrose) and
chose the asterids because of their diversity in floral
structure, geographical range and pollinators. Further-
more, a wealth of published data on pollination ecology
is available for this clade, accessed by searching for
publications in ISI Web of Knowledge and Google
Scholar using the terms ‘nectar sugar composition’ and
‘nectar sugar content’. In contrast to nectar volume and
total sugar concentration, which are heavily influenced
by water availability and microclimate, nectar sugar
composition is relatively constant within plant species
(Baker & Baker, 1983a; Schwerdtfeger, 1996; Torres &
Galetto, 1998; Nicolson & Thornburg, 2007). The rela-
tively low level of intraspecific variation that has been
documented is mainly due to differences among
1Phylogenetic constraint, phylogenetic conservatism and phyloge-
netic inertia are here used interchangeably to describe a pattern of
evolutionary stasis, lack of variation among close relatives, and
over time, or retention of ancestral traits. We are aware that use
varies among authors and may even refer to the process of failing
to change, adapt to some factor or occupy some habitat or region
(Wiens & Graham, 2005; Ackerly, 2009; Cooper et al., 2010;
Wiens et al., 2010; Losos, 2011; Crisp & Cook, 2012).
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114 S. ABRAHAMCZYK ET AL.
individuals and only to a small degree due to differ-
ences between populations in the wild or between
plants growing in the wild or in botanical gardens (e.g.
Freeman & Wilken, 1987; Vickery & Sutherland, 1994;
Lanza et al., 1995; Gijbels et al., 2014). We further
reduced the potential for variation in nectar sugar com-
position by collecting nectar only from young flowers
to minimize the impact of bacteria and yeasts, which
are able to transfer sucrose to hexoses (Nicolson &
Thornburg, 2007). We collected nectar between
September 2007 and August 2011 in the field in Eur-
ope, South-East Asia and South America and in botani-
cal gardens. We used glass capillaries to collect nectar
from at least three young flowers per plant species. The
minimum volume of nectar collected per species was
1 lL (Morrant et al., 2009). We placed the nectar on fil-
ter paper, air-dried it and stored it in silica gel for up to
a few months to prevent microbial decomposition of
the sugars. Overall sugar concentration (%) and com-
position (relative proportions of fructose, glucose and
sucrose) were determined using standard protocols (SI
text). The proportional content of each sugar was nor-
malized by logit transformation prior to analysis.
Definition of pollinator groups
Due to the large variety of concepts for defining PGs,
these were considered carefully. Because plants that are
mainly pollinated by unspecialized nectar-feeding birds
(generalists) contrast in their morphology and physiol-
ogy with plants that are mainly pollinated by obligate
nectar-feeding birds (specialists; Johnson & Nicolson,
2008), we treated specialized and unspecialized bird
species as different PGs. Generalist passerine and non-
passerine birds that feed on nectar, as well as on larger
amounts of fruits, seeds or insects, are referred to as
unspecialized (e.g. orioles [Oriolidae], bulbuls [Pyc-
nonotidae], white-eyes [Zosteropidae], Hawaiian hon-
eycreepers [Drepaniidae] and flowerpeckers
[Dicaeidae]; Amadon, 1950; Stiles, 1981; Johnson &
Nicolson, 2008; del Hoyo et al., 2008). Some of these
birds (thrushes, starlings and mockingbirds; families in
the Muscicapoidea) lack the ability to digest sucrose
(Mart�ınez del Rio, 1990), whereas others (waxwings;
Bombycilidae) are able to digest sucrose but not as effi-
ciently as they are able to digest hexoses (Mart�ınez del
Rio et al., 1992). In contrast, the bird species we refer
to as specialized, such as New World hummingbirds
(Trochilidae) and Old World sunbirds (Nectariniidae),
sugarbirds (Promeropidae), and some small-bodied gen-
era of honeyeaters (Meliphagidae) and lorikeets
(Psittacidae; Hopper & Burbridge, 1979; Pyke, 1980;
Stiles, 1981; Tjørve et al., 2005; Johnson & Nicolson,
2008), take most of their energy from nectar and are
able to digest sucrose efficiently. Behavioural differ-
ences between specialized nectar-feeding birds in the
Old and New Worlds are associated with different
characteristics of their food plants. Therefore, we
treated specialized, nectar-feeding birds from the Old
and New Worlds as separate PGs.
Several concepts for insect pollination systems exist.
The distinction between plants pollinated by short-
tongued bees and butterflies, short-tongued bees or
long-tongued bees (e.g. Baker & Baker, 1975, 1982,
1983a,b) can be difficult to detect in nature (Schwerdt-
feger, 1996). Also, the details of the pollinators of these
plants are largely unknown. Instead, we adopted the
two categories developed by Schwerdtfeger (1996): (i)
typical bee-pollinated, often zygomorphic, flowers are
referred to as bee-pollinated, and (ii) relatively small,
open flowers, providing access to the nectar for a wide
range of insects (e.g. small bees and butterflies, wasps,
flies and beetles), are referred to as generalist insect-pol-
linated. Similarly, we recognized a butterfly-pollinated
and a moth-pollinated group, mainly distinguishing the
species pollinated during the day and night, respectively
(Schwerdtfeger, 1996). This contrasts with the various
groups of plants pollinated by different groups of butter-
flies recognized by some authors (Baker & Baker, 1975,
1982, 1983a,b). In the end, we defined nine pollinator
groups: generalist insects, bees and wasps, specialized
flies, butterflies, moths, New World bats, unspecialized
birds, specialized Old World birds and hummingbirds.
We obtained information on each asterid species’
affiliation to one pollinator group from the same publi-
cations used to extract the published data on nectar
sugar composition. For the newly generated data
(~ 30% of species), we used pollinator observations
from the literature (e.g. J€ager & Rothmaler, 2011) or
our own field observations. For species where the polli-
nator is unknown, we used categories based on floral
morphology, coloration and scent (Faegri & van der
Pijl, 1978) because this is known to be a reliable
method for identifying the most effective, main PGs of
a plant (Fenster et al., 2004; Rosas-Guerrero et al.,
2014). For example, brightly coloured, often red, scent-
less flowers with long, relatively wide corolla tubes,
pending stigmas and stamens without a landing plat-
form were scored as pollinated by specialized Old World
birds or, in the Americas, hummingbirds. Flowers with
a landing platform, long, narrow corolla tubes and
bright colours were scored as butterfly-pollinated.
Phylogenetic information
Published, DNA-based phylogenies for most species in
the nectar data set are available, but the DNA markers
used differ among studies, rendering data coverage for
individual genes highly incomplete. Therefore, we used
phylogenetic information from published studies for all
sampled asterid species to generate a summary phy-
logeny. At the higher taxonomic level, we referred to
Smith et al. (2011) and the phylomatic webpage (Webb
et al., 2008). For resolution among and within genera,
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Evolution of floral nectar sugar composition 115
we used published phylogenies based on multiple genes
(supplementary data, S1; Abrahamczyk et al., 2016) to
manually place species using Mesquite 2.74 (Maddison
& Maddison, 2009). Polytomies were randomly resolved
100 times to generate a set of 100 trees that reflect
some, shallower phylogenetic uncertainty (e.g. within
genera). The final set of trees comprised 2063 species,
for which both nectar and PG data were available.
Many trait evolution analyses rely on phylogenetic
distances (e.g. all models founded in Brownian motion;
e.g. Pagel, 1999; Thomas & Freckleton, 2012), and
because the assembled tree lacked branch-length infor-
mation, three approaches for providing branch lengths
were explored (Fig. S1). The most realistic distribution
of branch lengths, representing the results of numerous
independent studies (Table S1), was obtained by setting
all branch lengths to 1.0 and then scaling the tree
height to absolute time using 110 published age con-
straints (Table S1) in pathd8 (Britton et al., 2007).
Model fitting in a Brownian motion framework:adaptive and nonadaptive models
We devised a series of models (Table 1) that allow
change in nectar sugar to depart in various ways from
the null expectation of constant change that is random
in direction (Brownian motion, BM; Schluter et al.,
1997). The first departure allowed the rate of change in
nectar sugar to vary over time and among clades (‘dif-
ferential rates’), independently of PG. The number of
rate shifts was increased incrementally until no better
models were found (i.e. all shifts supported by
DAICc ≥ 6 were identified; Thomas & Freckleton,
2012). For practicality and to avoid inferring spurious
shifts, the minimum clade size for detecting shifts was
set to 100.
Next, a series of Ornstein–Uhlenbeck (OU) models
(Hansen, 1997; Butler & King, 2004) was fitted. These
allow change in nectar sugar to be directional, towards
one or more optimal values, at a rate dictated both by
the strength of the pull (rate of adaptation) and the rate
of (stochastic) change towards the optimum. The first
model allowed directional change towards a single opti-
mum value (OU-1), the second allowed the mean opti-
mum to differ among species in different clades (OU-
Clades; with clades defined as having uniform rates
change in the differential rates analysis; 16 putative
optima; see Results), and the third allowed the mean
optimum to differ among species pollinated by different
PGs (OU-PG; nine putative optima). More complex
Table 1 Models founded in Brownian motion compared for nectar sucrose proportion (NSP), nectar fructose proportion (NFP) and nectar
glucose proportion (NGP).
Model Hypothesis Free parameters AICc (NSP) AICc (NFP) AICc (NGP)
BM Nectar sugar evolves independently of PG and is
random in direction, with a mean change of zero
and a rate of change that is constant over time
and among lineages
k = 2 (root state and rate of change) 10539.4 8820.2 9901.5
Differential rates As BM but the rate of change may vary over time
and among lineages
k = 2 + 2n (root state, n number of
rate shifts and n + 1 number of rates)
9931.7 8004.3 9220.2
OU-1 Nectar sugar evolves independently of PG but is
directional, towards a global optimum state; the
strength of the pull towards and rate of
(stochastic) change towards the optimum are
constant over time and among lineages
k = 3 (rate of change, strength of pull
[=adaptive change] and 1 trait
optimum)
10160.5 8417.5 9398.0
OU-Clades As OU-1 but directional change is towards several
optima, which may differ among clades (defined
as having their own rate of change in the
differential rates analysis; Table S3)
k = 18 (as OU-1 and 16 putative
optima)
10134.5 8357.8 9342.8
OU-PG As OU-1 but directional change is towards several
optima, which may differ among PGs; thus,
nectar sugar evolution is dependent on PG
k = 11 (as OU-1 and nine putative
optima)
9149.1 8395.8 9344.6
OU-2 As OU-PG but directional change is towards two
optima, which may differ between generalist and
specialist PGs
k = 4 (as OU-1 and 2 putative optima) 10096.3 – –
OU-2V As OU-2 but the rate of change may differ
between optima
k = 5 (as OU-2 and 2 putative rates of
stochastic change)
10098.2 – –
OU-2A As OU-2 but the strength of pull may differ
between optima
k = 5 (as OU-2 and 2 putative rates of
adaptive change [=pull])
10096.9 – –
BM, Brownian motion; OU, Ornstein–Uhlenbeck.AICc values in bold denote the best-fitting model.
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116 S. ABRAHAMCZYK ET AL.
models in which the adaptive pull or stochastic rate
may vary among optima (Beaulieu et al., 2012) were
explored, but with 9 or 16 putative optima, such mod-
els soon become highly parameter-rich. Although the
current data set is large, not all putative optima are rep-
resented by many data points (Table S8), and prelimi-
nary findings indicated that one or more parameters
could not be reliably estimated. This resulted in a sub-
optimal model overall. Results for these more complex
models are therefore considered unreliable and are not
reported. Instead, to further test our hypotheses, three
simpler models based on the results of the OU-PG
model (see Results) were devised for NSP only
(Table 1): one in which the mean optimum was
allowed to differ between specialist and generalist PGs
(OU-2), one in which rates of stochastic change
towards those optima may also differ (OU-2V) and one
in which the strength of the pull towards those optima
may also differ (OU-2A).
All models were fitted using maximum likelihood
(ML) in R (R Development Core Team 2014), and
model fit was compared using sample-size corrected
AIC values (AICc; Burnham & Anderson, 2002). The
BM and ‘differential rates’ models were fitted using
‘transformPhylo.ML’ in motmot (Thomas & Freckleton,
2012), and the OU models were fitted using OUwie
(Beaulieu & O’Meara, 2015). Ancestral states, which
determine the phylogenetic distribution of each puta-
tive selective regime, were determined using the equal-
rates model in the ‘ace’ function of ape (Paradis et al.,
2004) for PG and manually for plant clade.
Model fitting in a continuous-time Markovframework: correlation analyses
The results of the above analyses suggested that NSP
(but not NFP or NGP) is an adaptation to PG (see
Results). To further explore this, we tested for corre-
lated change between the NSP and PG. We treated each
variable as binary, with PG coded as ‘specialist’ (bats,
specialized flies, bees and wasps, specialized birds, but-
terflies, moths and hummingbirds) or ‘generalist’ (gen-
eralist insects and unspecialized birds) and NSP as
‘high’ (>0.45) or ‘low’ (≤ 0.45, the 84th percentile
[mean + 1 standard deviation]) for all generalist-polli-
nated plants; Table S4). Next, we used two continuous-
time Markov models for discrete traits to test whether
change in one trait depends on the state of the second
trait (Pagel, 1994; Pagel & Meade, 2006). The first
model states that rates of change in one trait are inde-
pendent of the other trait (i.e. 0 ? 1 and 1 ? 0 transi-
tions occur at the same rate irrespective of whether the
second trait is in state 0 or 1). The second model states
that rates of change in one trait are dependent on the
other trait (i.e. 0 ? 1 and 1 ? 0 transitions in one trait
may differ depending on whether the second trait is in
state 0 or 1). There are eight possible transitions in the
dependent model and four in the independent model
(Table 2). Models were fitted with 10 mL iterations for
each of the 100 trees using the discrete functions in
BayesTraits V2.0 (Quad Precision version for large trees;
available from www.evolution.rdg.ac.uk/BayesTraits.
html), and fit was compared using a likelihood ratio
(LR) test with four degrees of freedom (d.f.) on each
tree.
Robustness of results to phylogenetic uncertaintyand scale and compared to simulated data
Three sets of analyses were performed to test the effect
of (i) phylogenetic uncertainty (by comparing the phy-
logenetic signal of each nectar sugar and pollinator data
across the set of 100 trees), (ii) phylogeny alone (by
comparing results of the differential rates analysis to
those for simulated data) and (iii) phylogenetic scale
(by comparing best-fitting models across the asterids as
a whole to those for a set of less inclusive clades).
Details of these analyses are provided in the SI text.
Table 2 Definition of rate parameters compared in the correlation
analyses.
Parameter Evolutionary transition* Estimate† (median [95% CI])
Forward shifts (0 ? 1)
q12 Shift from specialist to
generalist in high sucrose
background
0.00077 (0.00048–0.010)
q13 Shift from high to low sucrose
in specialist background
0.018 (0.017–0.019)
q24 Shift from high to low sucrose
in generalist background
0.45 (0.015–3.1)
q34 Shift from specialist to
generalist in low sucrose
background
0.0044 (0.0033–0.0058)
Reverse shifts (1 ? 0)
q21 Shift from generalist to
specialist in high sucrose
background
0.00 (0.00–1.51)
q31 Shift from low to high sucrose
in a specialist background
0.054 (0.050–0.058)
q42 Shift from low to high sucrose
in a generalist background
0.045 (0.0083–0.48)
q43 Shift from generalist to
specialist in low sucrose
background
0.030 (0.022–0.043)
*Eight transitions are possible under the dependent model because
transition rates in one trait may vary depending on state of the
second trait. In the independent model, transition rates in one trait
are the same irrespective of the state of the second trait. Thus,
q12 = q34, q21 = q43, q13 = q24 and q31 = q42, and the indepen-
dent model has four rate parameters.
†Rate estimates shown are summaries across the 100 trees; com-
parisons reported in the text were performed across each tree indi-
vidually and cannot be read directly from this table.
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Evolution of floral nectar sugar composition 117
Results
Variation in nectar sugar composition in relation topollinator group
The nectar sugar composition data set comprised 2116
species and subspecies of asterids, representing 660 gen-
era, 55 families and 13 of the 16 orders. Roughly two-
thirds of these data (1480 species) were taken from the
literature (see supplementary data, S2; Abrahamczyk
et al., 2016). Data for the remaining 636 species were
generated for this study (577 species sampled from
Botanical Gardens, 59 from the wild, with samples from
the wild spanning a range of families and pollinator
groups [Data S2; Abrahamczyk et al., 2016]). A ternary
plot shows separation of nectar sugar composition along
the sucrose axis, with plants pollinated by generalists
being found at lower NSP than plants pollinated by spe-
cialists (Figs 1a and S2). Only hummingbird-pollinated
plants show a skew with respect to the two hexoses,
being shifted towards fructose. There is a high degree of
variation in the NSP of species pollinated by most PGs,
especially by specialized flies, Old World birds and but-
terflies, and much overlap among them (Fig. 1b). In
particular, we documented unexpectedly sucrose-poor
nectar for some species pollinated by Old World special-
ized birds that have nectar with a low overall sugar
concentration (Fig. S3).
Best-fitting evolutionary models for NSP, NFP andNGP
The best-fitting model for NSP was OU-PG and for NFP
and NGP differential rates (Table 1). Two independent
optima were inferred for NSP: low NSP for plants
pollinated by generalist birds and unspecialized insects
and high NSP for plants pollinated by all other PGs
studied here (Fig. 2). This model is a much better fit to
the data (DAICc ≥ 783) than any of the other BM-
based models. However, the parameter estimates from
this model suggest that the adaptive process is weak
(Table 3). The stationary variance, a measure of the
rate of drift relative to the strength of selection, is very
high (r2/2a = 2.5 9 105), and the phylogenetic half-
life, defined as the time needed to evolve half the dis-
tance from the ancestral state to the trait optimum, is
extremely long (ln[2]/a = 4.0 9 105 Ma). The simpler
models (OU-2, OU-2V and OU-2A), although a worse
fit to the data (third best overall; Table 1), confirm that
generalist-pollinated plants are evolving towards a
lower NSP optimum than specialist-pollinated plants
and yield phylogenetic half-life estimates of ~ 10 Ma,
that is, suggesting an adaptive process in which species
are closer to their optimum and that is achievable
within about 10% of the age of the asterids (Table S2).
The second best model for NSP was the differential
rates model, in which 15 rate shifts were identified
(Fig. 3, Table S3). Seven shifts were slowdowns and
eight speedups; several shifts were nested and most shifts
were found in Ericales, where rates generally increased
in shallower clades, or Gentianales + Lamiales, where
rates generally decreased in shallower clades. Most clades
identified correspond to, or almost to, major named
clades. This could be an artefact of the relatively sparse
sample analysed here or, alternatively, suggests corre-
spondence between evolutionary processes and named
clades that we are only beginning to be able to detect
(Smith et al., 2011; Humphreys & Barraclough, 2014).
Group means
Nectar Sugar Composition
Fructose Glucose Pollinator group
Sucrose Generalist insects
Specialized flies
Bees and wasps
Butterflies
Moths
Unspecialized birds
Specialized OW birds
Hummingbirds
NW bats
0
0.2
0.4
0.6
0.8
1
Suc
rose
pro
porti
on
(a) (b)
Fig. 1 Composition of nectar sugars and variation among pollinator groups. (a) Ternary plot of the relative contributions of fructose,
glucose and sucrose to the nectar sugar utilized by each pollinator group (PG). All groups separate along the sucrose axis with generalist
pollinator groups tending towards lower nectar sucrose proportion (NSP; main plot: all data, n = 2116; inset: group means; see Fig. S2 for
details). NW = New Word; OW = Old World. See main text for definitions of PGs. (b) Distribution of NSP among plants pollinated by
different PGs. Horizontal line = median, boxes = upper and lower quartiles, circles = outliers (defined as lying beyond 1.5 9 the
interquartile range [Q3–Q1]). Outliers represent several plant families and are based on data sampled from both wild and cultivated plants.
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118 S. ABRAHAMCZYK ET AL.
Fifteen rate shifts were also found under the overall best
model for NFP (DAICc ≥ 354; Tables 1 and S3). Half of
these occur at exactly the same node as for NSP, and the
other half occur only one or a few nodes away. Under
the overall best model for NGP (DAICc ≥ 122), there was
support for 11 rate shifts. Again, shifts tended to occur at
the same nodes as for NSP, NFP or both. The pattern of
slowdowns and speedups was the same for all three sug-
ars: decreases tended to occur in Gentianales and Lami-
ales and speedups in Ericales. The second best model for
both NFP and NGP was OU-Clades.
Correlation analyses: nectar sucrose proportion andpollinator group
When NSP and PG are coded as binary variables, there
is significant dependency in the data (P < 0.0001, Fish-
er’s exact test, two-tailed; Table S4). Specialist PGs are
more likely to be associated with high than low NSP,
and very few generalist PGs are associated with high
NSP (specialists are three times more likely to pollinate
high-NSP flowers and generalists six times more likely
to pollinate low-NSP flowers). This association does not
hold the other way round: both high-NSP and low-NSP
flowers are more likely to be pollinated by a specialist
than a generalist pollinator (68 and four times more
likely, respectively).
More formally, the model of dependent evolution
between NSP and PG could not be rejected for any of
the 100 trees (P < 0.0001, LR tests with 4 d.f.). A
comparison of rate parameter estimates reveals the nat-
ure of this dependency: a high-NSP, specialist-polli-
nated plant is more likely to change into a low-NSP,
specialist-pollinated plant than into a high-NSP general-
ist-pollinated plant (q13 > q12; 98% of trees; Table 2).
This suggests that nectar shifts first from the ancestral
state. In addition, shifts from a specialist to generalist
PG are more likely in a low sugar background
(q34 > q12; 94% of trees) and shifts from high to low
NSP are more likely in a generalist PG background
(q24 > q13; 96% of trees). Rate estimates for the
reverse transitions were indistinguishable.
Robustness to phylogenetic uncertainty and scaleand compared to simulated data
Estimates of phylogenetic signal were constant across
the set of 100 trees for all three sugars and PG (SI text,
Table S5). Thus, our findings are robust to some phylo-
genetic uncertainty. The results of the differential rates
analysis differed for empirical and simulated data
(Fig. S4). Thus, overall, the pattern of rate increases
and decreases is not an artefact of the phylogeny and
NSP is evolving differently to expectations for a neutral
trait. However, some shift positions were recovered for
both empirical and simulated data (Fig. 3 SI text;
Table S3) and these should be interpreted with caution
because they can apparently be recovered with any
trait. Finally, analysis of less inclusive clades revealed a
strong effect of phylogenetic scale. For NSP, the find-
ings for the asterids overall were confirmed, but, in
addition, differences among specialist PGs as well as
among clades were found (Table 3, Figs S5 and S6).
Evidence for adaptation, for example as indicated by
short phylogenetic half-lives relative to overall tree
height, was much stronger for clades analysed sepa-
rately than for asterids overall. These findings were lar-
gely mirrored for NFP and NGP, thus contradicting
results across the asterids as a whole for these two sug-
ars (SI text, Tables S6 and S7, Fig. S5).
Discussion
Unexpected variation in nectar sugar compositionfor many pollinator groups
Based on the results of Baker & Baker (1982), we
expected plants pollinated by one PG to have converged
on the optimum NSP for that PG. Instead, we found
high variability in the NSP of plant species pollinated
by most PGs, most notably by specialized flies, bees and
wasps, butterflies and specialized Old World birds
(Fig. 1). The variability for these insect-pollinated
plants may be because of different preferences in males
and females (Rusterholz & Erhardt, 1997, 2000), differ-
ent requirements for different pollinator subgroups
–30
–20
–10
0
10
20
Pollinator group
Logi
t NS
C
Fig. 2 Selective optima inferred for nectar sucrose content (NSP) in
relation to pollinator group (PG) in asterids. The main differences
are found between generalist and specialist PGs, with plants
pollinated by generalist insects and unspecialized birds tending
towards lower NSP optima than species pollinated by other PGs. See
Table 3 for details. Colours and symbols as in Fig. 1.
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Evolution of floral nectar sugar composition 119
Table
3Parameter*
estim
atesforthebest-fittingOU
modelforasteridsoverallandforeach
oftheless
inclusivecladesanalysedseparately,where
such
amodelcould
notberejected
(seeTable
S6).
Clade
Model†
r†
a
h–
generalist
insects
h–bats
h–
bees
and
wasp
s
h–
specialized
flies
h–
specialized
Old
World
bird
s
h–
unsp
ecialized
bird
s
h–
butterflies
h–
moths
h–
humming-
bird
st 1/2(th)
v y
Asterid
sOU-PG
0.87
<0.001
<0.001
45.3
78.1
99.9
53.3
<0.001
15.6
100
99.8
4.0
9105(114)
2.5
9105
Fouqueria
ceae+
Polemoniaceae+
Prim
ulaceae
OU-1
0.19
0.087
––
53.7
––
–53.7
–53.7
7.98(67)
1.11
Core
Eric
aceae
OU-1
5.65
0.11
––
85.7
–85.7
––
–85.7
6.37(49)
25.9
Core
Asteraceae
OU-1
1.12
0.062
23.6
–23.6
––
–23.6
–23.6
11.1
(39)
8.98
Core
Solanaceae
OU-1
3.38
0.15
–34.7
34.7
34.7
––
34.7
34.7
34.7
4.53(28)
11.0
Gelsemiaceae+
Gentianaceae+
Apocynaceae
OU-1
1.80
0.057
–82.4
82.4
82.4
––
82.4
82.4
82.4
12.1
(62)
15.7
Rubiaceae
OU-1
1.37
0.12
––
78.2
78.2
––
78.2
78.2
78.2
5.78(56)
5.72
Gesn
erio
ideae
OU-PG
23.4
9.98
–36.2
88.5
––
––
–77.8
0.070(31)
1.17
Core
Plantaginaceae
OU-PG
0.69
0.068
<0.001
–57.8
––
––
–74.8
10.2
(46)
5.07
Core
Acanthaceae
OU-1
0.67
0.053
––
60.5
––
–60.5
–60.5
13.0
(34)
6.26
Ajugoideae+
Lamioideae
OU-PG
81.9
9.74
––
82.4
–28.8
–74.2
–91.8
0.071(34)
4.20
Nepetoideae
OU-PG
15.5
5.59
8.16
–70.0
83.9
––
––
78.1
0.12(38)
1.38
Campanulaceae
OU-PG
0.35
0.057
–6.30
23.3
––
1.15
––
77.7
12.2
(56)
3.09
Boraginales
BM
0.39
NA
––
NA
––
––
––
NA(57)
NA
*r2is
therate
ofstoch
astic
change(e.g.underdrift
orin
relationto
anunmeasuredfactor),ais
thestrength
ofthe‘pull’towardstheselectiveoptima(rate
ofadaptation)in
Ma�1,h
isthemeantraitoptimum,t 1/2
isthephylogenetichalf-lifein
Mawithtotaltreeheight(th)in
Main
brackets
(ln(2)/a;
thetimeneededto
movefrom
theancestralstate
tothenew
optimum)andv y
isthestationary
variance
(r2/2a;
thebalance
betw
een
theaction
controlledbyaandthatcontrolledbyr).
Optimum
valuesare
shown
asback-transform
edmean
estim
ates(%
NSP;seeFig.S5forvariationaroundthemean).
†OU-PG
isamodelin
whichthemeanoptimum
maydifferamongpollinatorgroups(PGs).NotallPGsare
presentin
allclades(seeTable
S8)so
thenumberofoptimadiffers
among
clades.
Best
fittingmodels
andcolumnswithtw
ogeneralist
PGsare
bolded.
ª 2016 EUROPEAN SOC I E TY FOR EVOLUT IONARY B IO LOGY . J . E VOL . B I OL . 3 0 ( 2 0 1 7 ) 1 1 2 – 12 7
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120 S. ABRAHAMCZYK ET AL.
(Goldblatt & Manning, 1999; Petanidou, 2005) or
different optimal NSP values in different plant clades
(explored further below). The variability for plants pol-
linated by specialized Old World nectarivorous birds
probably requires a different explanation. Nectarivorous
birds are known to prefer sucrose-rich nectars with a
high overall sugar concentration, but experiments have
shown that they prefer nectar composed of hexoses if
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aniracnU
snebmucorp
notyhpogapraH
mulimup
amgitsoretar
Csillo
mainredniL
faineroT
ireinruoneroT
sedionogylopai
aerupruportaaineroT
Aden
ocal
ymm
a m
argi
natu
m
Dol
icha
ndra
den
tata
Dol
icha
ndra
cyn
anch
oide
s
Dol
icha
ndra
ungu
is c
ati
Dol
icha
ndra
unca
taBi
gnon
ia b
inat
a
Bign
onia
cap
reol
ata
Anem
opae
gma
cham
berla
ynii
Anem
opae
gma
laev
e
Amph
iloph
ium
cyn
anch
oide
s
Amph
iloph
ium
pan
icul
atum
Amph
iloph
ium
spe
c I
Amph
iloph
ium
buc
cina
toriu
m
Amph
iloph
ium
elo
ngat
um
Amph
iloph
ium
spe
c II
Frid
eric
ia tr
iplin
ervi
a
Frid
eric
ia c
andi
cans
Frid
eric
ia c
hica
Frid
eric
ia s
peci
osa
Frid
eric
ia tr
unca
ta
Peria
ntho
meg
a ve
llozo
i
Cat
alpa
big
noni
oide
s
Spat
hode
a ca
mpa
nula
ta
Oph
ioco
lea
florib
unda
Zeyh
eria
dig
italis
Han
droa
nthu
s he
ptap
hyllu
s
Amph
itecn
a m
acro
phyl
la
Cre
scen
tia a
lata
Cre
scen
tia c
ujet
e
Cre
scen
tia d
acty
lon
Jaca
rand
a m
imos
ifolia
Tour
retti
a la
ppac
ea
Ecc
rem
ocar
pus
scab
er
Cam
psis
gra
ndifl
ora
Cam
psis
spe
c
Cam
psis
radi
cans
Teco
ma
stan
s
Teco
ma
cape
nsis
Teco
ma
fulv
a
Teco
ma
x sm
ithii
Inca
rville
a ar
guta
Inca
rville
a de
lava
yi
Inca
rvill
ea o
lgae
Podr
anea
rica
solia
na
Dep
lanc
hea
glab
ra
Teco
man
the
volu
bilis
Teco
man
the
venu
sta
Cam
psid
ium
val
divi
anum
Prosta
nthe
ra ro
tund
ifolia
Prosta
nthe
ra m
agnif
ica
Prosta
nthe
ra c
unea
ta
Prosta
nthe
ra st
riatifo
lia
Wes
tring
ia fr
utico
sa
Conge
a to
men
tosa
Vitex a
gnus
castu
s
Vitex t
rifoli
a
Viticipr
emna
que
ensla
ndica
Vitex d
onian
a
Ballota acetabulosa
Ballota hispanica
Marrubium peregrin
um
Marrubium supinum
Marrubium vulgare
Lamium album
Lamium maculatum
Lamium orvala
Lamium flavidum
Lamium galeobdolon
Lamium garganicum
Lamium amplexicaule
Leucas zeylanica
Leucas aspera
Leonotis nepetifolia
Leonotis leonitis
Leonotis intermedia
Leonotis leonurus
Leonotis ocymifolia var ra
ineriana
Leonotis ocymifolia var schinzii
Leonotis spec
Leonurus cardiaca
Leonurus cardiaca ssp villosus
Leonurus cardiaca ssp turke
stanicus
Leonurus sibiricusPhlomis f
ruticosa
Phlomis visco
sa
Phlomis tuberosa
Phlomis russeliana
Phlomis herba ve
nti
Betonica m
acrantha
Betonica offic
inalis
Galeopsis bifid
a
Galeopsis te
trahit
Galeopsis se
getum
Galeopsis pubesc
ens
Melittis
melissophyllu
m
Prasium m
ajus
Sideritis m
acrosta
chys
Sideritis g
lacialis
Sideritis h
ysso
pifolia
Sideritis s
yriaca
Stachys
recta
Sideritis s
pec
Stachys
alpina
Stachys
lamioides
Stachys
annua
Stachys
cassi
a
Stachys
plumosa
Stachys
aegyptia
ca
Stachys
elliptica
Stachys
palustris
Stachys sylv
atica
Stenogyne m
inutiflora
Stachys cocci
nea
Stachys
cretica
Physo
stegia vi
rginiana
Colquhounia cocc
inea
Gomphostemma sp
ec
Gomphostemma st
robilinum
Pogostemon ca
blin
Holmsk
ioldia
sang
uinea
Holmsk
ioldia
tetten
sis
Scutella
ria la
teriflora
Scutella
ria alpina
Scutella
ria co
ccinea
Scutella
ria cf
atriplic
ifolia
Scutella
ria albida
Scutella
ria in
carn
ata
Scutella
ria sp
ec
Scutella
ria sp
eciosa
Scutella
ria sc
ordifolia
Scutella
ria in
tegrifolia
Scutella
ria vi
olacea
Scutella
ria co
lumnea
Scutella
ria co
staric
ana
Scutel
laria
altiss
ima
Scutel
laria
galer
iculat
a
Rothe
ka se
rrata
Teuc
rium
poli
um ss
p ca
pitat
um
Teuc
rium
rotu
ndifo
lium
Teuc
rium
cham
aedr
ys
Teuc
rium
frut
icans
Teuc
rium
mon
tanu
m
Teuc
rium
hirc
anicu
m
Teuc
rium
scor
dium
Teuc
rium
mar
um
Teuc
rium
scor
odon
ia
Teuc
rium
het
erop
hyllu
m
Trich
oste
ma
lanat
um
Ajuga
repe
ns
Clerod
endr
um in
erme
Clerod
endr
um tr
ichoto
mum
Clerod
endr
um pa
nicula
tum
Clerod
endru
m spec
iosiss
imum
Clerod
endru
m indic
um
Clerod
endr
um ca
pitatu
m
Clerod
endr
um th
omso
niae
Clerod
endr
um sp
lende
ns
Clerod
endr
um d
eflex
um
Clerod
endr
um cf
villo
sum
Clerod
endr
um tr
acya
num
Lavandula angustifolia
Lavandula spica
Lavandula spec
Collinsonia canadensis
Plectranthus barbatus var barbatus
Plectranthus reflexus
Plectranthus amboinicus
Plectranthus ambiguus
Plectranthus zuluensis
Plectranthus fruticosus
Plectranthus ciliatus
Plectranthus epilithicus
Plectranthus ecklonii
Plectranthus saccatus
Plectranthus hilliardiae
Dauphinea brevilabra
Pycnostachys eminii
Pycnostachys reticulataOcimum selloi
Ocimum basilicum
Ocimum spec minimum
Orthosiphon thymiflorus
Orthosiphon tubiformis
Orthosiphon aristatus
Orthosiphon spec
Elsholtzia stauntonii
Agastache mexicana
Agastache aurantiaca
Agastache urticifolia
Agastache foeniculum
Agastache rupestris
Dracocephalum grandiflorum
Dracocephalum moldavica
Dracocephalum nutans
Dracocephalum ruyschiana
Hyssopus officinalis
Glechoma hederacea
Glechoma hirsuta
Cedronella canariensis
Nepeta grandiflora
Nepeta cataria
Nepeta nepetella
Nepeta parnassica
Nepeta sibirica
Nepeta x faasenii
Nepeta nudaLycopus europaeus var exaltatus
Lycopus uniflorus
Horminum pyrenaicum
Prunella grandiflora
Lepechinia conferta
Lepechinia floribunda
Melissa officinalis
Melissa officinalis ssp altissima
Mentha cf spicata
Mentha pulegiumMentha x piperitaMentha rotundifoliaMentha cervinaMentha aquaticaMentha spec
Monardella macranthaMonardella nanaMonarda didyma
Clinopodium nepetaClinopodium nepeta ssp sylvaticaClinopodium vulgare
Hedeoma hyssopifolia
Pycnanthemum pilosumPycnanthemum virginianum
Monarda fistulosaMonarda russelianaConradina grandiflora
Cuminia eriantha
Micromeria croaticaMicromeria dalmatica
Thymus praecoxThymus capitatusThymus serpyllumThymus pulegioides ssp carniolicus
Origanum vulgare
Thymbra capitata
Satureja montanaSatureja hortensisSatureja thymbraSatureja spec
Salvia sphacelifolia
Salvia trachyphylla
Salvia spathaceaSalvia microphylla
Salvia squalens
Salvia styphelusSalvia coahuilensis
Salvia divinorum
Salvia strictaSalvia spec IISalvia oppositiflora
Salvia amplifrons
Salvia amarissimaSalvia mexicanaSalvia greggii
Salvia fulgens
Salvia iodantha
Salvia purpurea
Salvia farinaceaSalvia reglaSalvia macrophyllaSalvia heerii
Salvia confertiflora Salvia karwinskii
Salvia coccinea
Salvia guaraniticaSalvia corrugataSalvia spec ISalvia tortuosa
Salvia uliginosaSalvia pichinchensis
Salvia lasiocephalaSalvia pauciserrata
Salvia spruceiSalvia patens
Salvia iodochroa
Salvia semiatrataSalvia elegans
Salvia discolor
Salvia gesneraefloraSalvia lemmoniSalvia lavanduloides
Salvia splendens
Salvia glutinosa
Salvia fruticosaSalvia bulleyana
Rosmarinus officinalis
Perovskia atriplicifolia
Perovskia abrotanoides
Perovskia scrophulariifolia
Salvia argenteaSalvia ringensSalvia aurita
Salvia multiorrhiza
Salvia verbenaca
Salvia virgataSalvia verticillataSalvia canariensisSalvia scabra
Salvia aethiopis
Salvia taraxacifoliaSalvia indicaSalvia roemeriana
Salvia judaica
Salvia jurisiciiSalvia officinalis
Salvia trilobaSalvia nemorosa
Salvia pratensis
Salvia broussonetiiSalvia namaensis
Salvia stepposaSalvia hierosolymitana
Salvia viridis
Salvia sclareaSalvia austriaca
Salvia scala
Salvia nutansSalvia somalensis
Aloy
sia g
ratis
sima
Aloy
sia w
right
ii
Lipp
ia ju
nellia
na
Phyla
filifo
rmis
Lant
ana
cam
ara
Lant
ana
fuca
taJu
nellia
juni
perin
a
June
llia tr
iden
s
June
llia c
onna
tibra
ctea
ta
June
llia s
uccu
lent
ifolia
June
llia m
ulin
oide
s
June
llia lig
ustri
na
June
llia th
ymifo
lia
Verb
ena
offic
inal
is
Verb
ena
hast
ata
Verb
ena
bona
riens
is
Verb
ena
stric
tG
land
ular
ia c
rithm
ifolia
Gla
ndul
aria
aur
antia
ca
Gla
ndul
aria
tene
ra
Gla
ndul
aria
per
uvia
na
Gla
ndul
aria
lacin
iata
Gla
ndul
aria
flava
Gla
ndul
aria
mac
rosp
erm
aDiost
ea ju
ncea
Rhaph
itham
nus
venu
stus
Stac
hyta
rphe
ta fr
antz
ii
Stac
hyta
rphe
ta s
pec
Stac
hyta
rphe
ta in
dica
Duran
ta re
pens
Dur
anta
tria
cant
ha
Petre
avo
lubi
lis
arolf
idna
rgai
debo
csE
vra
mury
pma
leM
esne
esne
tarp
mury
pma
leM
ercit
alai
stra
Bat
anor
aisa
rhpu
Ean
aivo
kts ro
tcel
asu
htna
nih
Rsu
hpol
osu
nitor
essu
htna
nih
Rro
nim
suht
nani
hR
sirts
ulap
siral
ucid
eP
fissifajellitsa
Cailocitoirtap
ajellitsaC
aanatno
mortsuaajellitsa
Canal
ajellitsaC
atgetniajellitsa
Cailofir
Cas
tille
ja to
men
tosaC
astilleja tenuifloraC
astilleja sessiliflora
Castilleja irasuensis C
astil
leja
ort
egae
Cas
tille
ja li
near
ifoliaC
astilleja integra
egsi
nilag
Aail
ofits
inad
igir
sinil
agA
ofiht
nani
hrai
xuor
uoma
Lailat
agri
vai
xuor
uoma
L
Orobanche alba mu
rocu
leh
cnab
orOO
robanche hederae
itul
gai
nna
mhe
Rnosa
ale
ainn
amh
eR
atkzes
aip
ainn
amh
eR
iiot
ain
wolu
aP
mentosa
Mazus reptans
Mim
ulus aurantiacusM
imulus guttatus
Mim
ulus flemingii silan
idra
csu
lumi
M
naia
nsu
lumi
Mdinussn
egnir
sulu
miM
suec
inup
sulu
miM
Mim
ulus luteus
Pinguicula m
acrophyllaP
inguicula hemiepiphytica
Pinguicula leptoceras
Pinguicula longifolia ssp caussensis
Pinguicula alpina
Pinguicula m
oranensis
Pinguicula laueana
Pinguicula rectifolia
Pinguicula m
octezumae
Pinguicula gigantea
Pinguicula ehlersae
Pinguicula esseriana
Pinguicula oblongiloba
Pinguicula zecheri
Utricularia vulgaris
Utricularia gibba ssp exoleta
Utricularia alpina
Utricularia reniform
is
Utricularia nephrophylla
Ibicella luteaP
roboscidea fragrans
Proboscidea louisiana
Halleria lucida
Diascia vigilis
Myoporum
acuminatum
Sutera cordata
Sutera roseoflava
Scrophularia orientalis
Scrophularia sciophila
Scrophularia nodosa
Scrophularia vernalis
Scrophularia grandiflora
Scrophularia pyrenaica
Scrophularia sm
ithii
Teedia lucida
Derm
atobotrys saundersii
Phygelius aequalis
Phygelius capensis
Buddleja globosa
Buddleja japonica
Buddleja m
endozensis
Buddleja forrestii
Buddleja crispa
Buddleja colvilei
Buddleja albiflora
Buddleja davidii
Buddleja lindleyana
Ourisia poeppigii
Stemodia suffruticosa
Gratiola officinalis
Bacopa spec
Asarina procum
bensM
abrya coccineaM
abrya acerifolia
Mabrya geniculata ssp geniculata
Mabrya rosei
Mabrya erecta
Lophospermum
purpusii
Lophospermum
turneri
Lophospermum
erubescens
Lophospermum
atrosanguineum
Lophospermum
scandens
Maurandya barclaiana
Maurandya scandens
Maurandella antirrhiniflora
Cym
balaria pallida
Neogaerrhinum
filipesM
isopates orontium
Pseudorontium
cyathiferum
Galvezia fruticosa
Galvezia leucantha
Galvezia speciosa
Gam
belia juncea
Gam
belia speciosa
Mohavea breviflora
Antirrhinum
latifolium
Antirrhinum
coulterianum ssp orcuttianum
Antirrhinum
siculum
Antirrhinum
majus
Antirrhinum
majus var cirrhigerum
Chaenorrhinum
origanifolium
Kickxia spuria
Linaria alpina
Linaria vulgarisLinaria triornithophora
Linaria dalmatica
Linaria purpurea
Linaria saxatilis
Isoplexis isabelliana
Isoplexis canariensis
Isoplexis chalcantha
Digitalis trojana
Digitalis obscura
Digitalis parviflora
Digitalis grandiflora
Digitalis purpurea
Wulfenia carinthiaca
Veronica bachofeniiVeronica m
issurica
Veronica missurica ssp stellata
Veronica spicataVeronica saturejoides
Veronica austriaca ssp austriaca
Veronica teucriumVeronica polita
Veronica persica
Veronica filiformis
Veronica salicifolia
Veronica speciosa
Veronica elliptica
Veronica diosmifolia
Veronicastrum virginica
Globularia alypum
Cam
pylanthus salsoloides
Tetranema roseum
Russelia equisetiform
isR
usselia villosa
Russelia w
orthingtonii
Russelia verticillata
Russelia sarm
entosa
Collinsia heterophylla
Keckiella antirrhinoides
Chelone glabra
Chelone lyonii
Penstemon confertus
Penstemon alam
osensis
Penstemon barbatus
Penstemon w
islizenii
Penstemon eatoni
Penstemon pseudospectabilis
Penstemon digitalis
Penstemon m
ultiflorus
Penstemon sm
allii
Penstemon spectabilis
Penstemon virgatus
Penstemon strictus
Penstemon centhranthifolius
Penstemon superbus
Penstemon parryi
Penstemon hartw
egii
Penstemon isophyllus
Penstemon cam
panulatus
Penstemon kunthii
Penstemon ram
osus
Penstemon pinifolius
Penstemon linarioides
Penstemon dasyphyllus
Penstemon lanceolatus
Penstemon serrulatus
Penstemon laetus
Penstemon ovatus
Penstemon pallidus
Penstemon stenophyllus
Penstemon spec I
Penstemon spec II
Penstemon flavescens
Besleria barbata
Besleria modica
Besleria columneoides
Besleria reticulata
Besleria formosaGasteranthus corallinus
Gasteranthus macrocalyx
Gasteranthus quitensis
Gasteranthus pansamalanus
Rhytidophyllum spec
Rhytidophyllum exsertum
Rhytidophyllum tomentosum
Gesneria libanensis
Gesneria ventricosa
Gesneria pedunculosa
Achimenes candida
Achimenes grandiflora
Achimenes flava
Achimenes longiflora
Achimenes erecta
Achimenes misera
Diastema scabrum
Diastema vexans
Solenophora calycosa
Pearcea hypocyrtiflora
Pearcea rhodotricha
Pearcea sprucei
Pearcea spec
Kohleria inaequalis var ocellata
Kohleria strigosa
Kohleria spicata
Kohleria elegans
Kohleria villosa
Kohleria hirsuta
Kohleria amabilis var bogotensis
Kohleria amabilis var amabilis
Kohleria affinis
Kohleria tigridia
Koellikeria erinoides
Gloxinia erinoides
Gloxinia sylvatica
Gloxinia gymnostoma
Gloxinia nematanthodes
Heppiella ulmifolia
Mitraria coccinea
Asteranthera ovata
Rhabdothamnus solandri
Sinningia schiffneri
Sinningia gerdtiana
Sinningia basiliensis
Sinningia araneosa
Sinningia valsuganensis
Sinningia carangolensis
Sinningia aggregata
Sinningia tubiflora
Sinningia sellovii
Sinningia warmingii
Sinningia allagophylla
Sinningia spec I
Sinningia sceptrum
Sinningia incarnata
Sinningia elatior
Sinningia nordestina
Sinningia barbata
Sinningia aghensis
Sinningia helioana
Sinningia pusilla
Sinningia villosa
Sinningia speciosa
Sinningia guttata
Sinningia lindleyi
Sinningia gigantifolia
Sinningia cochlearis
Vanhouttea spec nov indet II
Vanhouttea spec nov indet III
Vanhouttea spec nov indet I
Vanhouttea lanata
Sinningia hirsutaPaliavana sericiflora
Paliavana prasinata
Sinningia reitzii
Sinningia lineata
Sinningia macrostachya
Sinningia eumorpha
Sinningia conspicua
Sinningia cardinalis
Sinningia magnifica
Sinningia bulbosa
Sinningia hatschbachii
Sinningia cooperi
Sinningia iarae
Sinningia micans
Sinningia macropoda
Sinningia canescens
Sinningia douglasii
Sinningia calcaria
Sinningia piresiana
Sinningia rupicola
Sinningia insularis
Sinningia nivalis
Sinningia leucotricha
Sinningia spec alata aff
Sinningia spec nov ined
Sinningia spec II
Paradrymonia ciliosa
Paradrymonia hypocyrta
Nautilocalyx forgetii
Nautilocalyx bullatus
Nautilocalyx melittifolius
Nautilocalyx lynchii
Nautilocalyx spec
Codonanthe erubescens
Codonanthe gracilis
Nematanthus gregarius
Nematanthus fissus
Nematanthus crassifolius
Nematanthus saracoba
Nematanthus corticola
Nematanthus brasiliensis
Nematanthus spec
Nematanthus hirtellus
Nematanthus glabratus
Nematanthus strigillosus
Nematanthus m
aculatus
Chrysothemis pulchella
Chrysothemis friedrichsthaliana
Corytoplectus speciosus
Glossolom
a sprucei
Glossolom
a tetragonoides
Alloplectus tetragonus
Alloplectus ichthyoderma
Allopectus andinus
Allopectus spec I
Allopectus spec II
Neomortonia rosea
Monophyllea horsfieldii
Columnea byrsina
Columnea virginica
Columnea hirta
Columnea lepidocaulis
Columnea spathulata
Columnea crassifolia
Columnea rubriacuta
Colum
nea medicinalis
Columnea dielsii
Colum
nea spec III
Colum
nea hirsutissima
Colum
nea herthae
Colum
nea oerstediana
Colum
nea microphylla
Colum
nea spec I
Colum
nea querceti
Colum
nea oxyphylla
Colum
nea purpurata
Colum
nea gloriosa
Colum
nea spec II
Colum
nea orientandinaC
olumnea arguta
Colum
nea strigosa
Colum
nea magnifica
Colum
nea tulae
Colum
nea schiedeana
Colum
nea linearis
Colum
nea hirta var mortonii
Columnea argentea
Columnea inaequilatera
Columnea m
inor
Columnea nicaraguensis
Columnea m
icrocalyx
Drymonia fim
briata
Drymonia spec I
Drymonia m
arnier lapostollea
Drymonia spec IV
Drymonia spec V
Drymonia rhodolom
a
Drymonia conchocalyx
Drymonia m
ultiflora
Drymonia dodsonii
Drymonia coccinea
Drymonia serrulata
Drymonia urceolata
Drymonia warszewicziana
Drymonia spectabilis
Drymonia spec II
Drymonia spec III
Cobananthe calochlamys
Alsobia diamanthiflora
Alsobia punctata
Episcia cupreata
Episcia cupreata var viridifolia
Rhynchoglossum gardneri
Rhynchoglossum spec
Streptocarpus caulescens
Streptocarpus saxorum
Streptocarpus stomandrus
Streptocarpus wendlandii
Streptocarpus polyanthus
Streptocarpus eylesii
Briggsia muscicola
Aeschynanthus evrardii
Aeschynanthus tricolor
Aeschynanthus parasiticus
Aeschynanthus spec
Aeschynanthus parviflora
Aeschynanthus radicans
Aeschynanthus longicalyx
Aeschynanthus rhododendron
Aeschynanthus lanceolatus
Aeschynanthus micranthus
Aeschynanthus speciosus
Agalmyla chorisepalaCyrtandraspec III
Cyrtandraspec I
Cyrtandraspec II
Didymocarpus hispida
Didymocarpus crinita
Didymocarpus atrosanguineus
Didymocarpus reptans
Syringa pubescens ssp microphyllaSyringa wolfii
Syringa vulgaris
Syringa tomentella ssp yunnanensis
Syringa x chinensisSyringa x persicaLigustrum sempervirens
Ligustrum sinense
Ligustrum tschonoskii
Jasminum polyanthum
Jasminum odoratissimum
Jasminum didymum
Menodora robusta
Jasminum nudiflorum
Jasminum parkeri
Jasminum sambac
Jasminum fruticans
Jasminum humile
Jasminum mesnyi
Mandevilla cf sanderi
Mandevilla pentlandianaMandevilla petreaMandevilla hirsuta
Mandevilla angustifoliaMandevilla spec I
Mandevilla laxaParsonsia heterophylla
Trachelospermum jasminoides
Apocynum androsaemifolium
Pachypodium baronii
Pachypodium succulentum
Pachypodium bispinosum
Pachypodium decaryi
Pachypodium hybrid
Pachypodium densiflorum
Pachypodium lamerei
Acokanthera oppositifolia
Kibatalia spec I
Kibatalia spec II
Adenium obesum
Stephanostema stenocarpumWrightia spec I
Wrightia spec II
Allamanda catharica
Allamanda schottiiCerbera manghas
Cerbera odollam
Thevetia ahouai
Thevetia peruviana
Thevetia bicornuta
Thevetia neriifolia
Thevetia ovata
Amsonia tabernaemontana
Kopsia fruticosaKopsia griffithii
Kopsia arborea Vinca minor
Catharanthus roseusRauvolfia sumatrana
Rauvolfia cf ligustrina
Rauvolfia serpentina
Tabernaemontana catharinensis
Tabernaemontana pachysiphon
Marsdenia spec II
Telosma procumbensDischidia hirsuta
Dischidia ovataHoya imperialisHoya multiflora
Hoya bella
Hoya australis
Hoya kerrii
Hoya carnosaHoya kentiana
Hoya thomsoniiHoya serpens
Hoya longifolia
Hoya lacunosa
Hoya pentaphlebia
Ceropegia sandersonii
Araujia sericifera
Morrenia brachystephana
Philibertia gilliesii
Amblyopetalum coccineum
Oxypetalum arnottianum
Oxypetalum coeruleum
Vincetoxicum hirundinaria
Asclepias angustifolia
Asclepias syriaca
Asclepias fruticosa
Asclepias curassavica
Asclepias linaria
Gelsemium sempervirensFagraea fragrans
Fagraea racemosa
Lisianthus nigrescens
Symbolanthus calygonus
Symbolanthus pulcherrimus
Symbolanthus spec
Symbolanthus spec nov ined
Chelonanthus alatus
Macrocarpaea arborescensMacrocarpaea harlingii
Macrocarpaea sodiroana
Macrocarpaea noctiluca
Halenia asclepiadeaHalenia spec
Halenia weddelliana Gentianella germanica
Gentianella hirculus
Gentianella specGentiana sedifoliaGentiana walujewii
Gentiana tibeticaGentiana lutea
Gentiana pneumonantheGentiana dinarica
Gentiana acaulis
Gentiana angustifolia
Gentiana verna
Virectaria majorSabicea panamensis
Pseudomussaenda flava
Mussaenda phillipicaMussaenda angustisepala
Mussaenda aliciaMussaenda erythrophyllaMussaenda nervosaMussaenda mutabilis
Ixora chinensisIxora SunkistIxora finlaysonianaIxora coccineaIxora javanicaIxora coccinea f lutea
Alberta magnaBurchellia capensis
Pavetta revoluta
Randia scortechiniiRandia spinosa
Oxyanthus formosus
Gardenia thunbergiaGardenia tubiferaTocoyena formosa
Warszewiczia coccine
Pentagonia macrophyllaDioicodendron dioicum
Ladenbergia sp ILadenbergia sp II
Stilpnophyllum oellgaardiiIsertia laevis
Hoffmannia nebulosa
Hoffmannia ghiesbreghtiiHoffmannia refulgens
Hamelia patensHillia macrophylla
Hillia wurdackiiHillia parasitica
Cosmibuena macrocarpaChione costaricensis
Cephalanthus occidentalisRondeletia odorata
Timonius spec Gonzalagunia dependens
Gonzalagunia rosea
Arachnothryx lojensisGuettarda speciosa
Notopleura vargasiana
Heterophyllaea pustulataOreopolus glacialis
Coccocypselum condalia
Faramea cf glandulosa
Faramea unifloraFaramea coerulescens
Morinda citrifolia
Psychotria nervosa
Psychotria acuminataPsychotria capensisPsychotria elata
Psychotria reticulata
Psychotria aubletiana
Psychotria carthagenensisPsychotria tomentosa
Psychotria specMyrmecodia spec
Psychotria poeppigianaPsychotria tinctoria
Rudgea ciliata
Palicourea angustifolia
Palicourea lyristipula
Palicourea subtomentosa
Palicourea canarina
Palicourea sulphureaPalicourea heterochroma
Palicourea spec I
Palicourea cf weberbaueriPalicourea andreiPalicourea spec II
Palicourea rigidaPalicourea lobbii
Palicourea calycinaPalicourea thyrsiflora
Palicourea luteonivea
Palicourea sp nov ined
Leptodermis specPhuopsis stylosa
Pentas lanceolataPentas schimperiana
Arcytophyllum capitatumArcytophyllum filiforme
Arcytophyllum macbridei
Arcytophyllum vernicosumArcytophyllum thymifolium
Arcytophyllum setosumArcytophyllum peruvianum
Arcytophyllum ciliolatum
Arcytophyllum lavarumArcytophyllum rivetii
Manettia cordifoliaManettia spec I
Manettia spec IIIManettia spec IIManettia inflataBouvardia bouvardioidesBouvardia laevisBouvardia glabberimaBouvardia ternifolia
Cuscu
ta od
orata
Convo
lvulus
canta
bricu
s
Convo
lvulus
arvens
is
Convo
lvulus
cneo
rum
Calyste
gia se
pium
Merre
mia sp
ec
Ipomoe
a spe
c
Ipomoe
a hier
onym
i
Ipomoea indica
Ipomoea acuminata
Ipomoea rubrifl
ora
Ipomoea mauriti
ana
Ipomoea cairic
ari
Ipomoea arboresc
ensIpomoea alba
Ipomoea purpurea
Ipomoea nil
Ipomoea hederifolia
Ipomoea lobata
Ipomoea quamoclit
Maripa
nica
ragu
ensis
Petunia axillaris
Petunia spec
Fabiana imbric
ata
Fabiana denudata
Fabiana patagonica
Brunfelsia americ
ana
Brunfelsia m
ire
Brunfelsia paucif
lora
Vestia fo
etidaCestr
um nocturnum
Cestrum elegans
Cestrum aurantia
cum
Cestrum co
rymbosu
m
Cestrum cf
bracteatum
Cestrum purpureum
Cestrum parqui
Cestrum psit
tacinum
Cestrum fa
scicu
latum
Cestrum la
urifoliu
m
Salpiglossis
sinuata
Streptoso
len jameso
nii
Browallia americ
ana
Browallia sp
eciosa
Physochlaina orientalis
Hyoscyamus albus
Hyoscyamus aureus
Atropa belladonna
Jaborosa integrifolia
Lycium gilliesianum
Lycium chilense var fil
ifolium
Lycium chilense var m
inuitifolium
Lycium chilense var chilense
Lycium chilense var ve
rgarae
Lycium chilense var descolei
Lycium chilense var confertifolium
Lycium ciliatum
Lycium tenuispinosum var calycinum
Lycium tenuispinosum var te
nuispinosum
Lycium elongatum
Lycium americanum
Lycium infaustum
Lycium cuneatum
Lycium cestroides
Lycium ameghinoi
Lycium morongii
Lycium vimineum
Lycium nodosum
Lycium rachidocladum
Exodeconus miersii
Solandra maxima
Solandra grandiflora
Solandra specJuanulloa aurantiaca
Juanulloa speciosa
Trianaea nobilisMarkaea spec
Markea neurantha
Mandragora officinalis
Capsicum annuum
Salpichroa origanifolia
Salpichroa spec II
Salpichroa spec I
Cuatresia harlingiana
Cuatresia spec
Withania adpressa
Witheringia mexicana
Physalis heterophylla
Physalis crassifolia
Physalis peruviana
Iochroma coccineaIochroma cyaneum
Iochroma spec I
Iochroma fuchsioides
Iochroma calycina
Iochroma spec II
Vassobia breviflora
Dunalia fasciculataDunalia australis
Dunalia spec II
Dunalia spec III
Saracha spec
Brugmansia aurea
Brugmansia vulcanicola
Brugmansia suaveolens
Brugmansia sanguineaDatura meteloides
Datura metelDatura cf arborea
Datura wrightii
Datura stramonium
Nicotia
na otophora
Nicotia
na tabacu
m
Nicotia
na raim
ondii
Nicotia
na rustic
a
Nicotia
na cordifo
lia
Nicotia
na africana
Nicotia
na excelsio
r
Nicotia
na petunioides
Nicotia
na noctiflora
Nicotia
na glauca
Nicotia
na sylvestr
is
Nicotiana lo
ngiflora
Nicotiana plumbaginifolia
Nicotiana bonariensis
Nicotiana forgetiana
Nicotiana langsdorffii
Nicotiana alata
Nicotia
na mutabilis
Schiza
nthus pinnatus
Phac
elia
leuc
ophy
lla
Phac
elia
tana
cetif
olia
Nem
ophi
la m
acul
ata
Hyd
roph
yllu
m v
irgin
ianu
m
Cor
dia
sebe
sten
a
Cor
dia
spec
Wig
andi
a ca
raca
sana
Wig
andi
a cr
ispa
Ehre
tia d
icks
onii
Ehre
tia d
icks
onii
var j
apon
ica
Hel
iotro
pium
eur
opae
um
Hel
iotro
pium
frut
icos
um
Hel
iotro
pium
hirs
utis
sim
um
Borag
o of
ficin
alis
Symph
ytum
cor
datu
m
Symph
ytum
offi
cinal
e
Symph
ytum
x u
plan
dicu
m
Pulm
onar
ia o
fficin
alis
Pulmon
aria
obsc
ura
Pulmon
aria
moll
is
Pulm
onar
ia ru
bra
Nonea
lute
a
Cynog
lottis
bar
relie
ri
Cynog
lottis
chet
ikian
a
Anchu
sa p
usilla
Anchu
sa st
ylosa
Anchu
sa th
essa
la
Anchu
sella
cret
ica
Anchu
sa ca
lcare
a
Anchu
sa lit
tore
a
Anchu
sa a
rven
sis
Anchu
sa va
riega
ta
Anchu
sa o
fficina
lis
Anchu
sa lim
bata
Anchu
sa cr
ispa
Anchu
sa fo
rmos
a
Anchu
sa ca
pellii
Anchu
sa ca
pens
is
Anchu
sa se
mpe
rvire
ns
Anchu
sa hy
brida
Anchu
sa b
arre
lieri
Anchu
sa g
meli
nii
Anchu
sa le
ptop
hylla
Lyco
psis
arve
nsis
Anchu
sa a
egyp
tica
Horm
uzak
ia ag
greg
ata
Anchu
sa a
zure
a
Trac
hyste
mon
orie
ntali
s
Alka
nna
orie
ntal
is
Alka
nna
tinct
oria
Mac
rom
eria
viri
diflo
rus
Lith
ospe
rmum
pur
puro
caer
uleu
m
Cerin
the
maj
or
Para
mol
tkia
doe
rfler
i
Lith
odor
a ol
eifo
lia
Ono
sma
polyp
hylla
Ono
sma
aren
aria
Echi
um v
ulga
re
Echi
um c
retic
um
Echiu
m d
ecai
snei
Echiu
m s
impl
ex
Echiu
m p
inin
ana
Echiu
m w
ildpr
etii s
sp tr
ichos
ipho
n
Echiu
m w
ildpr
etii s
sp w
ildpr
etii
Echiu
m b
revir
ame
Echiu
m h
ierre
nse
Echiu
m v
iresc
ens
Echiu
m g
igan
teum
Echiu
m c
andi
cans
Echiu
m a
uber
ianu
m
Echi
um g
entia
noid
es
Echi
um s
pec
Echi
um it
alicu
mC
ynog
loss
um g
erm
anic
um
Cyn
oglo
ssum
offi
cina
le
Lind
elof
ia lo
ngifl
ora
Mer
tens
ia p
rimul
oide
s
Mer
tens
ia v
irgin
ica
Tric
hode
sma
bois
sier
i
Aucu
ba ja
poni
ca
Bar
nade
sia
arbo
rea
Bar
nade
sia
spin
osa
Barnadesia polyacantha
Barnadesia odorata
Barnadesia parviflora iu
eiss
ujag
ariuq
uhC
Ech
inop
s m
icro
ceph
alus
Ech
inop
s sp
haer
ocep
halu
s ss
p al
bidu
s
Ech
inop
s sp
haer
ocep
halu
s
Ono
pord
um a
cant
hium
Alfr
edia
niv
eaCen
taur
ea p
tero
caul
a
Cen
taur
ea a
sper
a
Cen
taur
ea u
ligin
osa
Cen
taur
ea m
onta
na v
ar n
igro
fimbr
ia
Cen
taur
ea o
rient
alis
Cen
taur
ea m
acro
ceph
ala
Cen
taur
ea c
ana
Cen
taur
ea n
igre
scen
s
Cen
taur
ea p
hryg
ia
Cen
taur
ea tr
ium
fetti
i
Cen
taur
ea o
rpha
nide
a ss
p or
phan
idea
Cen
taur
ea b
ract
eata
Cen
taur
ea o
ssic
a
Cen
taur
ea s
pinu
losa
Cen
taur
ea d
epre
ssa
Cen
taur
ea p
seud
ophr
ygia
Cen
taur
ea p
hryg
ia s
sp s
teno
lepi
s
Cen
taur
ea ja
cea
Cen
taur
ea th
raci
ca
Cen
taur
ea d
ebea
uxii
Cen
taur
ea c
anar
iens
is
Cen
taur
ea n
igra
Cen
taur
ea c
heira
nthi
folia
Cen
taur
ea g
last
ifolia
Cen
taur
ea s
cabi
osa
Cen
taur
ea s
empe
rvire
ns
Cen
taur
ea n
icae
ensi
s
Cen
taur
ea c
yanu
s
Cen
taur
ea ra
phan
ina
ssp
mix
ta
Cen
taur
ea m
onta
na
Cen
taur
ea s
cabi
osa
ssp
alpe
stris
Car
tham
us ti
ncto
rius
Car
dunc
ellu
s m
itiss
imus
Ser
ratu
la q
uinq
uefo
lia
Arc
tium
tom
ento
sum
Cou
sini
a hy
strix
Ptil
oste
mon
afe
r
Cyn
ara
card
uncu
lus
Car
duus
def
lora
tus
Car
duus
aca
ntho
ides
Car
duus
per
sona
ta
Car
duus
nut
ans
Cirs
ium
eris
ithal
es
Cirs
ium
vul
gare
Cirs
ium
tube
rosu
m
Cirs
ium
mon
spes
sula
num
Cirs
ium
ole
race
um
Sco
lym
us h
ispa
nicu
s
Mos
char
ia p
inna
tifid
a
Trix
is d
ivar
icat
a
Trix
is d
ivar
icat
a ss
p di
scol
or
Mut
isia
dec
urre
ns
Mut
isia
coc
cine
a
Mut
isia
retro
rsa
Mut
isia
ham
ata
Mut
isia
ala
ta
Mut
isia
mic
roce
phal
aM
utis
ia s
pino
saM
utis
ia s
inua
ta
Mut
isia
lehm
anni
i
Mut
isia
vic
iifol
iaA
cour
tia m
icho
acan
a
Tric
hocl
ine
rept
ans
Stif
ftia
chry
sant
ha
Hya
lose
ris r
ubic
unda
Arc
totis
fast
uosa
Vern
onia
nov
ebor
acen
sis
Vern
onia
mol
lissi
ma
Vern
onia
nud
iflor
aVe
rnon
ia w
akef
ield
ii
Less
ingi
anth
us m
ollis
sim
us
Trag
opog
on p
orrif
oliu
s ss
p po
rrifo
lius
Trag
opog
on p
rate
nsis
Hie
raci
um to
men
tosu
m
Hie
raci
um p
ilose
lla
Hie
raci
um u
mbe
llatu
mC
icho
rium
inty
bus
Son
chus
asp
er
Den
dros
eris
litto
ralis
Rei
char
dia
picr
oide
s
Leon
todo
n hi
spid
us
Leon
todo
n hi
spid
us s
sp h
yose
roid
es
Leon
todo
n hi
spid
us s
sp d
anub
ialis
Ago
seris
gla
uca
Hyp
ocha
eris
radi
cata
Hyp
ocha
eris
ach
yrop
horu
sA
pose
ris fo
etid
a
Lact
uca
tata
rica
Tara
xacu
m o
ffici
nale
Cre
pis
mol
lisC
repi
s sp
ec
Cal
endu
la a
rven
sis
Cal
endu
la o
ffici
nalis
Leon
topo
dium
alp
inum
Hel
ichr
ysum
sto
echa
s
Tana
cetu
m c
orym
bosu
mA
chill
ea m
illef
oliu
mLe
ucan
them
um v
ulga
re muiranorocmu
mehtnasyrhC San
tolin
a ch
amae
cypa
rissu
s
Kal
imer
is m
ongo
lica
Ast
er a
mel
lus
Ast
er s
pec
Sol
idag
o ca
nade
nsis
Sol
idag
o ch
ilens
isS
olid
ago
glom
erat
aS
olid
ago
virg
aure
a
Erig
eron
pin
natis
ectu
sG
rinde
lia d
isco
idea
Sym
phyo
tric
hum
nov
i bel
gii
Pyr
roco
ma
croc
ea
Eur
ybia
con
spic
uaE
uryb
ia m
acro
phyl
la
tatsahoicenesara
Psuatatned
airalugiL
cepsairalugiL
kslawezrp
airalugiLiiairod
oiceneS
sumirregetni
oiceneS
sneloevausaloetsa
Hsutavo
oiceneS
diuqeanioicene
Sen
s sudilauqsoicene
Sinotrebrab
oiceneS
cus
Sen
ecio
pam
pean
usS
enec
io v
erna
lis
Ade
nost
yarbalg
sel
sutalucitraoicene
S
whcsainiel
Kiihtrufnie
eglufainiel
Kns avivrep
mesainiel
K
aeabocajoicene
Sallyhpohpro
midarekca
P
Inul
a sa
licin
a
Inul
a he
leni
um
Inul
a en
sifo
liaIn
ula
spira
eifo
liaP
alle
nis
spin
osa
Bup
htha
lmum
sal
icifo
lium
Aca
ntho
sper
mum
his
pidu
m
Tage
tes
erec
taTa
gete
s m
inut
a
Arn
ica
long
ifolia
Ste
via
satu
reifo
lia
Mik
ania
per
iplo
cifo
liaM
ikan
ia u
rtic
aefo
lia
Liat
ris s
pica
ta
Eup
ator
ium
inul
ifoliu
m
Eup
ator
ium
sub
hast
atum
Eup
ator
ium
hoo
keria
num
Eup
ator
ium
arn
ottia
num
Bid
ens
pilo
sa
Dah
lia m
erck
ii
Cos
mos
sul
phur
eus
Bid
ens
laev
isB
iden
s sp
ecC
oreo
psis
lanc
eola
taC
oreo
psis
maj
or
Hym
enox
ys g
rand
iflor
aH
ymen
oxys
hoo
pesi
i
Hel
eniu
m a
rgen
tinum
Gai
llard
ia m
egap
otam
ica
Gai
llard
ia p
ulch
ella
Wed
elia
bup
htal
mifl
ora
Zex
men
ia b
upht
halm
iflor
aA
ngel
phyt
um a
spili
oide
s
Ver
besi
na a
ltern
ifolia
Ech
inac
ea la
evig
ata
Ech
inac
ea te
nnes
seen
sis
Ech
inac
ea p
urpu
rea
Hel
iops
is h
elia
ntho
ides
Hel
iops
is h
elia
ntho
ides
var
sca
bra
Wye
thia
am
plex
icau
lis
Zin
nia
peru
vian
a
Rud
beck
ia la
cini
ata
Rud
beck
ia la
cini
ata
var
hum
ilis
Hel
iant
hella
qui
nque
nerv
is
Acm
ella
dec
umbe
ns v
ar a
ffini
s
Tith
onia
div
ersi
folia
Hel
iant
hus
annu
us
Hel
iant
hus
mic
roce
phal
us
irek
oohf
faal
ovea
cS
lep
seht
nayn
eM
atat ail
ofirt
seht
nayn
eM
atall
yhpo
rdyh
sedi
ohp
myN
sedi
ohp
myN
atatl
ep
Lobelia columnaris
Lobelia rhynchopetalum
Lobelia validaLobelia sessilifolia
Cyanea hirtella
Cyanea angustifolia
Cyanea leptostegia
Clerm
ontia hawaiiensis
Clerm
onia kohalae
Clerm
ontia montis loa
Clerm
ontia persicifoliaC
lermontia spec
Clerm
onia parvifloraC
lermontia arborescens
Clerm
ontia kakeana
Lobelia yuccoidesLobelia hypoleuca
nitne
gra
suly
pma
cohp
iS
us
Siphocam
pylus esi
sner
odau
cS
iphocampylus lucidus
Siphocam
pylus manettiaeflorus
Siphocam
pylus nemoralis
suso
ilof
suly
pma
cohp
iS S
iphocampylus gigan
teusS
iphocampylus spec
Burm
eistera anderssonii
Burm
eistera sodiroanaB
urmeistera resupinata
Burm
eistera specceps
aimo
pisy
Lsu
naze
abfc
nogo
port
neC
ama
lat
nogo
port
neC
ncensismu
ecar
hco
nogo
port
neC
em
nogo
port
neC
asud su
etul
nogo
port
neC
ogop
ortn
eC
silifi
rbal
gn
ogop
ortn
eC
suil
ofina
los
nog
opor
tne
Csu
solu
narg
n
unic
ylac
nogo
port
neC
s
ogop
ortn
eC
VIce
psn
Ice
psno
gopo
rtne
C
suta
ucra
nogo
port
neC
gopo
rtne
Cir
elav
nogo
port
neC
Vce
psno
gopo
rtne
Csu
htna
ire
noce
psno
gopo
rtne
C II
ceps
nogo
port
neC
III
suni
dnab
usno
gopo
rtne
C
Lobelia tupaLobelia excelsa
Pratia spec
Pratia m
ontana
Lobelia tenuior
Isotoma axillaris
Lobelia elegans
Lobelia cardinalis
Hippobrom
a longifloraLobelia siphiliticaLobelia laxiflora
Lobelia erinus
Cyphia crenata
Codonopsis viridiflora
Canaria canariensis
Nesocodon m
auritianus
Wahlenbergia fernandeziana
Musschia aurea
Trachelium caeruleum
Cam
panula rapunculoides
Cam
panula drabifolia ssp drabifolia
Michauxia cam
panuloides
Cam
panula versicolor
Cam
panula trachelium
Azorina vidalii
Cam
panula thyrsoides
Cam
panula alliariifolia
Cam
panula latifoliaC
ampanula caucasica
Sym
phyandra hofmannii
Edraianthus gram
inifolius
Cam
panula baumgartenii
Cam
panula rotundifoliaC
ampanula rapunculus
Cam
panula portenschlagianaC
ampanula persicifolia
Asyneum
a canescens
Phyteum
a humile
Phyteum
a spicatumP
etromarula pinnata
Escallonia bifida
Escallonia rubra
Escallonia callcottiae
Itea virginicaC
olumellia oblonga ssp sericea
Desfontainia spinosa
Eryngium
amethystinum
Eryngium
campestre
Eryngium
bourgatii
Eryngium
giganteum
Ferula comm
unis
Tinguarra m
ontana
Thapsia garganica
Scandix australis ssp australis
Carum
carvi
Anethum
graveolens
Coriandrum
sativum
Peucedanum
cervaria
Heracleum
sphondylium
Tordylium apulum
Bupleurum
salicifolium
Astydam
ia latifolia
Hym
enosporum flavum
Pittosporum
crassifolium
Pittosporum
tenuifolium
Pittosporum
eugenioides
Pittosporum
undulatum
Pittosporum
revolutum
Pittosporum
tobira
Pittosporum
xylocarpu
Pittosporum
macrantha
Pittosporum
heterophyllum
Hedera helix
Polyscias sambucifolia
Sambucus ebulus
Viburnum carlesii
Viburnum tinus
Viburnum davidii
Viburnum opulus
Viburnum henryi
Abelia engleriana
Abelia parvifolia
Abelia m
acrotera
Abelia triflora
Abelia x grandiflora
Kolkwitzia am
abilis
Dipelta floribunda
Morina longifolia
Cephalaria am
brosioides
Cephalaria leucantha
Dipsacus laciniatus
Dipsacus pilosus
Dipsacus sativus
Knautia arvensis
Knautia spec
Succisa inflexa
Succisa pratensis
Lomelosia palestina
Pterocephalus papposum
Scabiosa atropurpurea
Scabiosa gram
inifolia
Scabiosa colum
baria
Scabiosa triandra
Scabiosa farinosa
Scabiosa canescens
Scabiosa ochroleuca
Centranthus ruber
Valeriana alliariifolia
Valeriana pyrenaica
Valeriana phu
Valeriana officinalis
Heptacodium
miconioides
Leycesteria formosa
Symphoricarpos albus
Lonicera ligustrina sspyunnanensis
Lonicera acuminata
Lonicera arizonica
Lonicera pilosa
Lonicera implexa
Lonicera periclymenum
Lonicera caprifolia
Lonicera fragrantissima
Lonicera tangutica
Lonicera caerulea
Lonicera pyrenaica
Lonicera alpigena
Lonicera alpigena var webbiana
Lonicera involucrata
Lonicera japonica
Lonicera rupicola
Lonicera myrtillus
Lonicera ruprechtiana
Lonicera maackii
Lonicera tatarica
Lonicera altmannii
Lonicera morrow
ii
Lonicera tomentella
Triosteum him
alayanumD
iervilla lonicera
Weigela decora
Weigelia hybrida
Weigela subsessilis
Weigela coraeensis
Weigelia praecox
Ilex mitis
Ilex cornuta
Ilex latifoliaIlex aquifolium
Ilex paraguariensis
Helw
ingia japonic
Eschweilera ovata
Diospyros lotus
Diospyros virginiana
Sarracenia minorSarracenia flava
Sarracenia alata
Sarracenia purpurea
Dimorphanthera spec
Agapetes buxifolius
Agapetes macrantha
Agapetes incurvata
Agapetes hosseana
Agapetes lobbii
Agapetes serpens
Vaccinium vitis idaea
Gaylussacia densa
Gaylussacia chamissonis
Gaylussacia jordanensis
Orthaea cf abbreviata
Vaccinium myrtillus
Vaccinium consanguineum
Vaccinium spec
Vaccinium uliginosum
Semiramisia speciosa
Thibaudia floribunda
Thibaudia martiniana
Sphyrospermum buxifolium
Sphyrospermum cordifolium
Oreanthes hypogaeus
Ceratostema reginaldii
Ceratostema alatumPsammisia guianensis
Psammisia ecuadorensis
Psammisia ramiflora
Psammisia spec
Macleania insignis
Macleania glabra
Macleania smithiana
Macleania mollis
Satyria warszewiczii
Cavendishia costaricensis
Cavendishia melastomoides
Cavendishia callista
Cavendishia capitulata
Cavendishia endresii
Cavendishia crassifolia
Cavendishia quereme
Cavendishia bracteata
Cavendishia smithii
Cavendishia complectens
Cavendishia nobilis var capitata
Gaultheria eriophylla
Gaultheria serrata
Gaultheria sleumeriana
Andromeda polifolia
Pieris japonicaAgarista hispidula
Agarista oleifolia
Dracophyllum secundum
Acrotriche patula
Leucopogon parviflorus
Rhododendron russatum
Rhododendron glariflorum
Rhododendron zoelleri
Rhododendron robinsonii
Rhododendron malayanum
Rhododendron multicolor
Rhododendron tuba
Rhododendron subcrenulatum
Rhododendron macgregoriae
Rhododendron gaultheriifolium
Rhododendron brassii
Rhododendron flavoviride
Rhododendron javanicum
Rhododendron inundatum
Rhododendron phaeochitum
Rhododendron haematophthalmum
Rhododendron verstegii
Rhododendron keleticum
Rhododendron cuneatum
Rhododendron intricatum
Rhododendron lepidostylum
Rhododendron burmanicum
Rhododendron viriosum
Rhododendron ciliatum
Rhododendron keiskei
Rhododendron championiae
Rhododendron moulmainense
Rhododendron canadense
Rhododendron luteum
Rhododendron occidentale
Rhododendron simiarum
Rhododendron meddianum
Rhododendron arboreum
Rhododendron barbatumRhododendron bakeri
Rhododendron atlanticum
Rhododendron neriiflorum
Rhododendron arborescens
Rhododendron ponticum
Rhododendron williamsianum
Rhododendron calophytum
Rhododendron strigillosum
Rhododendron kiusianum
Rhododendron simsii
Rhododendron hongkongense
Rhododendron vaseyi
Rhododendron farrerae
Ledum palustre
Erica ampullacea
Erica terminalis
Erica fastigiata
Erica mam
mosa
Erica pinea
Erica longifolia
Erica incarnata
Erica discolor
Erica colorans
Erica verticillata
Erica urna viridis
Erica coccinea
Erica densifolia
Erica glomiflora
Erica brachialis
Erica fascicularis
Erica plukenetii
Erica bibax
Erica perlata
Erica regia
Erica tumida
Erica diaphana
Erica blandfordia
Erica monadelphia
Erica sessiliflora
Erica viridiflora
Erica baccans
Erica thomae
Erica grandiflora
Erica vestita
Erica fourcadei
Erica cylindrica
Erica versicolor
Erica phylicifolia
Erica sitiens
Erica bauera
Erica gilva
Erica patersonia
Erica leucotrachela
Erica caffra
Erica curviflora
Erica foliacea
Erica haematocodon
Erica banksia
Erica massonii
Erica carnea
Erica cerinthoides
Erica perspicua
Erica conspicua
Erica verecunda
Erica glandulosa
Erica porteri
Erica sphaeroidea
Bejaria racemosa
Arbutus andrachne
Arbutus xalapensis
Arctostaphylos uva ursi
Enkianthus campanulatus
Pterostyrax corymbosus
Styrax japonicus
Styrax officinalis
Symplocos spec
Camellia japonicaCamellia cuspidata
Camellia salicifolia
Camellia tsaii
Camellia sinensis
Stewartia pseudocamellia
Visnea mocaner
Eurya japonica
Fouquieria diguetii
Fouquieria splendensCobaea scandens
Bonplandia geminifloraCantua candelillaCantua buxifolia
Cantua pyrifolia
Cantua quercifolia
Loeselia amplectensLoeselia mexicana
Loeselia ciliata
Ipomopsis aggregata
Ipomopsis macombii
Ipomopsis longiflora
Ipomopsis rubra
Ipomopsis thurberi
Collomia linearis
Gilia tricolor
Phlox drummondiiPhlox divaricata var laphamii
Phlox paniculata
Phlox subulata
Phlox nivalis
Polemonium caeruleum var acutiflorum
Polemonium caeruleum
Polemonium reptans
Polemonium carneum
Polemonium pauciflorum
Maesa argenteaMaesa hupehensis
Maesa perlariaDeherainia smaragdina
Jacquinia aurantiacaCoris monspeliensis
Androsace vitalianaSoldanella alpina
Dionysia aretioides
Primula boveanaPrimula verticillata
Primula edelbergiiPrimula rosea
Primula florindae
Primula vialiiPrimula capitata
Primula denticulata
Primula darialica
Primula frondosaPrimula halleri
Primula farinosa
Primula verisPrimula vulgaris
Primula juliae
Primula elatior
Primula japonica
Primula pulverulenta
Primula allionii
Primula marginataPrimula pedemontana
Primula palinuri
Primula auricula
Primula hirsuta
Primula rusbyi var ellisiae
Primula rusbyi ssp rusbyi
Primula malacoides
Primula forbesii
Primula jesoana
Primula polyneura
Primula bulleyana ssp beesiana
Primula obconica
Anagallis tenella
Marcgravia browneiMarcgravia nepenthoides
Marcgravia specNorantea brasiliensis
Norantea spec
Impatiens oncidioides
Impatiens montalbanaImpatiens eriospermaImpatiens elephanticeps
Impatiens paucidentataImpatiens parvifloraImpatiens noli tangere
Impatiens textoriImpatiens parasiticaImpatiens balsaminaImpatiens flaccida
Impatiens repens
Impatiens mackeyana ssp claeri
Impatiens mackeyana ssp zenkeri
Impatiens hians
Impatiens sakeriana
Impatiens platypetalaImpatienshawkeri white
Impatienshawkeri red
Impatiens pseudoviola
Impatiens kilimanjari
Impatiens sodeniiImpatiens burtonii
Impatiens auricoma
Impatiens catatii
Impatiens hochstetteri
Impatiens niamniamensis
Impatiens nyungwensis
Impatiens morsei
Impatiens irangiensis
Impatiens zombensis
Impatiens marianae
Impatiens namchabarwensis
Alangium platanifoliumCornus orbiculatusCornus nuttallii
Cornus sanguineaCornus macrophyllaCornus sericea
Hydrangea anomalaHydrangea quercifolia
Deutzia crenataDeutzia purpurascensDeutzia gracilisDeutzia glabrataKirengeshoma palmata
Philadelphus coronariusPhiladelphus schrenkiiPhiladelphus sericanthus
Jamesia americana
Eucnide aurea
Loasa argentinaLoasa triphyllaNasa speciosa
2069
2092
22282276
2277
2389
2672
2824
3112
3241
3438
3820
3821
3825
3832
LAMIALES
GE
NTIA
NA
LES
SOLANALES
ASTERALES
ERIC
ALES
CO
RN
ALE
S*
GARRYALES +
BORAGINALES AQUIFOLIALES
+ DIPSACALES
Mean rate:
0.25 0.8 2.15 2.85 3.35 5.75 8.64
Fig. 3 Phylogenetic position of rate shifts inferred in the differential rates analysis for nectar sucrose proportion (NSP). Branch colours
show rates as exceptionally high (red) to exceptionally low (blue), through intermediate rates (yellow then green), compared to
background rates (black). Major sampled orders are named. *The line not named (next to Dipsacales + Aquifoliales) is
Apiales + Escalloniales + Bruniales. Clades at which rate shifts occur are numbered; details are provided in Table S3. Based on a support
measure (shift support) calculated from the likelihood of finding a shift at each node, three shifts should be treated with caution: core
Solanaceae (node 2389, SS = 0.53), core Plantaginaceae (node 2276, SS = 0.85) and Gesnerioideae (node 3438, SS = 0.92). Shift support
(SS) is 1– fexp, where fexp is the expected frequency of shifts at that node based on results for simulated data (SI text; Fig. S4). The
differential rates analysis for nectar glucose (NGP) and nectar fructose proportion (NFP) revealed similar results as for NSP (Table S3).
ª 2016 EUROPEAN SOC I E TY FOR EVOLUT IONARY B IOLOGY . J . E VOL . B I O L . 3 0 ( 2 0 1 7 ) 1 1 2 – 12 7
JOURNAL OF EVOLUT IONARY B IO LOGY ª 20 1 6 EUROPEAN SOC I E TY FOR EVOLUT IONARY B IO LOGY
Evolution of floral nectar sugar composition 121
the overall sugar concentration of the nectar is low
(5%; Brown et al., 2010). This is because the birds are
sensitive to small changes in osmolarity of the nectar
and hexose solutions have a higher osmolarity than
sucrose solutions (Nicolson & Fleming, 2003). Our find-
ing, that about a third of the species pollinated by Old
World nectarivorous birds produce nectar with low
overall sugar concentration (< 20%) that is extremely
sucrose poor (NSP < 0.20; Fig. S3), corroborates the
results of Brown et al. (2010) and suggests that this
phenomenon may be more widespread in nature than
previously thought. It is possible that this represents an
alternative, energy-saving pollination strategy, which is
deceptive to the pollinators because of the compara-
tively energy-poor nectar they are rewarded with. Simi-
lar deception strategies probably occur in many plant
species belonging to several genera both within and
outside the asterids (e.g. van Wyk et al., 1993; Nicolson
& van Wyk, 1998; this study). Further studies are
needed to test this hypothesis.
Nectar sucrose proportion as an adaptation topollinator group
We tested the hypothesis that NSP is an adaptation to
PG (e.g. Heynemann, 1983; Mart�ınez del Rio et al.,
1992; Baker et al., 1998). At first glance, our results
suggest that this hypothesis cannot be rejected: we
found strong statistical support for convergence on dif-
ferent NSP optima among different PGs and for corre-
lated evolution between NSP and PG. But to what
extent do the details of our findings constitute evidence
for NSP being an adaptation to PG?
The best model for NSP evolution overall is where
NSP is allowed to evolve towards different optima for
each of the nine PGs studied here (Table 1). Inspection
of the inferred optima reveals that they in fact converge
on only two independent optimal values, one for plants
pollinated by generalists and one for plants pollinated
by specialists (Fig. 2). Lack of differences among plants
pollinated by most obligate nectar feeders implies that
the NSP requirements of the individual specialist PGs,
although being generally high, are indistinguishable.
This could be one reason why previous studies (van
Wyk, 1993; Galetto et al., 1998; Nicolson & van Wyk,
1998; Galetto & Bernadello, 2003) have failed to detect
significant differences in NSP among (specialist) PGs.
Further inspection of the best-fitting model reveals a
weak adaptive process (Table 3). The phylogenetic half-
life is unrealistically long, suggesting that species are far
from their optimum and unlikely ever to reach it (Han-
sen, 1997; T.F. Hansen, pers. comm.). The stochastic
variance is also very high, suggesting that any adaptive
evolution towards the NSP optima is overwhelmed by
stochastic movement and that a large amount of the
residual variance of the model is not explained by the
two optima. One interpretation of such a model is that
it does not represent adaptation to peaks in the
adaptive landscape in the strict sense but rather an
adaptive trend of increasing divergence from the ances-
tral state (Hansen, 1997, 2012; T.F. Hansen, pers.
comm.). Such an interpretation has been invoked for
body size evolution in relation to dietary niches in ceta-
ceans and habitat in monitor lizards (Slater et al., 2010;
Collar et al., 2011). For nectar evolution, this would
suggest slow movement towards low NSP in generalist-
pollinated plants and high NSP in specialist-pollinated
plants. However, the optima inferred from these models
tend to lie outside currently occupied ranges, perhaps
themselves therefore representing unreachable adaptive
peaks. The optima inferred for NSP approach the limits
of the occupied range but are not unrealistic (Table 3).
Another possible interpretation, therefore, is that NSP is
evolving as an adaptation to other, unmeasured vari-
ables (Labra et al., 2009; Hansen, 2012), for example
corolla shape and size (Nicolson, 2002; Witt et al.,
2013), perhaps as a function of the abiotic environment
(Petanidou, 2005; Nicolson et al., 2007). A third possi-
ble interpretation is that NSP is drifting, bounded by
the allometric constraints of floral shape and size,
which in turn could be correlated with PG. Such an
explanation has been invoked for body shape evolution
in three-spined stickleback (Voje et al., 2013). Without
formally incorporating these variables into the hypothe-
sis-testing framework, these alternatives cannot be dis-
tinguished but results from the simpler OU models
(OU2, OU2A and OU2V; Table S2) do offer some addi-
tional insight: these models suggest a much stronger
adaptive process, at the coarse level of generalist PGs
versus specialist PGs. This supports the interpretation of
adaptation rather than that of drift. However, because
the simpler models are a much worse fit to the data,
they do not capture the entire story. The more complex
model is a far superior fit to the data but one that nev-
ertheless explains less of the residual variance.
Together, these results suggest that PG is an important
component of NSP evolution, but it does not act
directly as hypothesized here – other factors are needed
to fully explain how NSP evolves.
Is nectar sucrose proportion the trait or theenvironment?
The dependency in the NSP and PG data coded as binary
variables suggests that a flower is more likely to be polli-
nated by a specialist pollinator, irrespective of its NSP
(Table S4). In contrast, a specialized nectar feeder is
more likely to pollinate a high-NSP flower and a general-
ist feeder is more likely to pollinate a low-NSP flower.
This asymmetry is explained by the finding that NSP is
the first to shift from the ancestral state of high NSP/spe-
cialist PG (q13 > q12; Table 2); that is, changes in NSP
may occur without a simultaneous or preceding change
in PG. Once variation in NSP has been established, shifts
ª 2016 EUROPEAN SOC I E TY FOR EVOLUT IONARY B IO LOGY . J . E VOL . B I OL . 3 0 ( 2 0 1 7 ) 1 1 2 – 12 7
JOURNAL OF EVOLUT IONARY B IOLOGY ª 2016 EUROPEAN SOC I E TY FOR EVOLUT IONARY B IO LOGY
122 S. ABRAHAMCZYK ET AL.
from a specialist to generalist PG are more likely in lin-
eages with low-NSP nectar and further shifts from high
to low NSP are more likely in generalist-pollinated lin-
eages. Thus, the evolution of NSP and PG is correlated in
a way that means that certain shifts are more likely than
others, but not in a way that requires simultaneous
change, as would be expected under strict coevolution
(Janzen, 1980). The finding that NSP changes first sug-
gests that the nature of the correlation is primarily dic-
tated by pollinator behaviour rather than vice versa. In
other words, it suggests that pollinating animals ‘capital-
ize’ on the NSP presented by the plant and that the
plants do not necessarily adapt their NSP to the local pol-
linator guild (cf. ‘diffuse coevolution’ of Janzen (1980)).
This contrasts with the view that a plant must adapt its
nectar composition to ensure regular visitation by effi-
cient pollinators (Nicolson et al., 2007). A conceptual
consequence of this is that NSP should perhaps be trea-
ted as the environment and PG the trait – in order to be
fully understood, the floral rewards–pollinator interac-
tion might better be viewed from the opposite perspec-
tive to that often presented in the literature (and this
study; Nicolson et al., 2007 and references therein).
Different processes in different clades and fordifferent sugars?
Analysis of less inclusive clades revealed several impor-
tant insights. Evidence for adaptation was much stronger
for individual clades than for asterids as a whole: an
adaptive model could not be rejected for 12 of 13 clades
(Table S6) and a much more rapid and precise adaptive
process was inferred from these models than from the
model for asterids overall (Table 3). This supports the
idea that, at the broadest scale, several factors are needed
to explain nectar evolution, only one of which is adapta-
tion to the broadly defined PGs analysed here. Certain
clades, however, revealed strong evidence for adaptation
to PG in some clades and none at all in other clades.
Multiple-optima models tended to corroborate the find-
ing of independent optima for generalist and specialist
PGs (Fig. S5) but also found differences among specialist
PGs. One interesting example is the low-NSP optimum
inferred for specialized nectarivorous birds, providing
further support for the hypothesis of deception elabo-
rated upon above. In contrast, single-optimum models
revealed different optima in different clades, irrespective
of the main PGs. A high optimum was inferred for the
heather family (Ericaceae) and a low optimum for the
daisy family (Asteraceae). Ericaceae are pollinated
entirely by specialist PGs (bees and wasps, specialized
OW birds and hummingbirds sampled here), whereas
Asteraceae are pollinated by both specialist and general-
ist PGs (generalist insects, bees and wasps, butterflies
and hummingbirds; Table S8). Ericaceae tend to have
tubular flowers and Asteraceae small, open flowers, sug-
gesting that the different optima inferred for these two
clades could be governed by floral shape and size, rather
than the main PGs of each clade. These results further
support both conclusions above that PG alone cannot
explain how interspecific differences in NSP evolve and
that the relationship between NSP and PG is perhaps not
governed by adaptations of the plant but by pollinator
behaviour and dietary requirements.
Finally, these findings hold true not only for NSP but
for NFP and NGP as well (Tables S6 and S7, Fig. S5).
This contrasts with findings for asterids as a whole,
where an adaptive model was rejected for these two
sugars (Table 1), and suggests either that pollinators are
sensitive to the proportion of the two hexoses in nectar
(contra Baker et al., 1998) or, because our analyses were
based on proportions, that the signal in NSP cannot be
independent of that in NFP and/or NGP, even if differ-
ent processes govern the relative proportions of each
sugar. Future (experimental) work may shed further
light on these alternatives.
Adaptation and conservatism in nectar evolutionand beyond
Much of the historical debate surrounding the evolu-
tion of nectar sugar composition has centred on the
dichotomy between adaptation to pollinator dietary
requirements and there being a ‘phylogenetic con-
straint’, limiting the amount of variation that can accu-
mulate within and among clades (Baker & Baker, 1975;
Nicolson et al., 2007). Indeed, results such as those
above, of different processes operating in different
clades and of clade-specific NSP optima that are inde-
pendent of pollinator diversity, are likely to underlie
some earlier claims of phylogenetic conservatism
(Galetto & Bernadello, 2003; Thornburg, 2007;
Rodr�ıguez-Ria~no et al., 2014). However, although we
found that adaptation to pollinators is not a sufficient
explanation on its own, phylogeny is merely a depiction
of patterns and cannot in itself constrain or explain
anything (e.g. Losos, 2011). Many empirical studies
have invoked both adaptation and conservatism in
cases such as ours, where there is some evidence for
adaptation, but where the specific hypothesis being
tested leaves some observed variance unexplained
(Ackerly, 2004; Cattin et al., 2004; Escudero et al.,
2012; Hansen, 2014). However, in these studies, phylo-
genetic conservatism is not invoked as an alternative to
adaptation but to describe a strong historical signal not
directly related to the hypothesis being tested. In other
words, conservatism is invoked in lieu of the full mech-
anistic explanation, just as appears to be the case in the
nectar literature.
Given the long-standing clarity, far beyond the nectar
literature, of the inadequacy of the adaptation/conser-
vatism dichotomy (e.g. Leroi et al., 1994; Blomberg &
Garland, 2002; Ackerly, 2004; Losos, 2011), why does
it persist? We suggest that there are several reasons.
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Evolution of floral nectar sugar composition 123
1 As a result of (na€ıve) interpretation of phylogenetic
patterns of trait similarity and divergence, often mea-
sured as phylogenetic signal (Losos, 2008; Cooper
et al., 2010; Crisp & Cook, 2012), as process. How-
ever, although it has long been clear that patterns
cannot simply be read from phylogenies and inter-
preted as processes (e.g. Blomberg & Garland, 2002),
the extent to which phylogenetic signal is discon-
nected from any underlying process has only become
clear relatively recently (e.g. Revell et al., 2008; Bou-
cher et al., 2014; M€unkem€uller et al., 2015). There-
fore, the practice of inferring process from
phylogenetic patterns remains.
2 Because of the cladistic tradition of recognizing only
autapomorphies as adaptations (Hansen, 2014). This
means that a retained ancestral state (plesiomorphy)
cannot be interpreted as an adaptation. The counter-
argument is that retained plesiomorphies must be
adaptations for something or they would have suc-
cumbed to selection pressures to change (Losos,
2011; Hansen, 2014). Thus, retention of the ancestral
state is a pattern that says nothing of its generating
or maintaining evolutionary process.
3 Because of the terminology used in the OU frame-
work of adaptive models (‘adaptation–inertia mod-
els’; e.g. Pienaar et al., 2013). This use may certainly
be perceived as conceptually confusing but inference
of ‘inertia’ over ‘adaptation’ does not necessarily
mean that the trait in question is not an adaptation
at all, only that the specific hypothesis under study is
rejected (Hansen, 2014). The trait may still be an
adaptation to an environment that itself is evolving
in a drift-like manner or to another, unmeasured
variable that shows strong similarity among closely
related species (Labra et al., 2009; Hansen, 2012).
Thus, although model inferences may be described as
either ‘adaptation’ or ‘inertia’, interpretation is not
necessarily dichotomous.
4 Due to the development of the conceptual frame-
works for studying adaptation and conservatism as
largely different fields. This is most likely historical: as
one field was realizing the challenges involved in
inferring adaptation in a comparative framework
(Baum & Larson, 1991; Leroi et al., 1994; Hansen,
1997), another, dedicated to detecting (niche) conser-
vatism (Harvey & Pagel, 1991; Wiens & Graham,
2005; Crisp & Cook, 2012), was born. Increasingly,
these fields make use of the same models (cf. e.g.
Kozak & Wiens, 2010; M€unkem€uller et al., 2015), butbecause they are developing in parallel (one is con-
cerned with adaptation [Hansen, 1997; Butler & King,
2004; Beaulieu et al., 2012; ], the other with a ‘failure
to adapt’ [Wiens et al., 2010; Kozak & Wiens, 2010; ]),
reconciliation of how adaptation and conservatism
can be interpreted together has received much less
attention than each phenomenon has separately (but
see Ackerly, 2003, 2004; Labra et al., 2009).
Conclusion
We present evidence that NSP is an adaptation to PG in
asterids but, importantly, that this is not the whole
story. Future studies may increase mechanistic under-
standing of how plant–pollinator interactions via floral
rewards evolve by focusing on dense sampling of nar-
rower clades, finer divisions of PGs and incorporating
additional factors into the hypothesis-testing frame-
work, along with consideration of how the floral nec-
tar–pollinator interaction arises, without the need to
invoke phylogenetic constraints or conservatism.
Acknowledgments
The botanical gardens of Berlin, Bonn, Freiburg, G€ottin-gen, Halle, Heidelberg, Jena, Munich, M€unster,Osnabr€uck, Potsdam, Basel, Bern, St. Gallen, Zurich,
Leiden, Kew, Graz, Cochabamba, Santa Cruz, Singa-
pore, Bogor and Cibodas and the ‘Sukkulentensamm-
lung’ Zurich provided permission to collect nectar. We
are grateful to B. Steudel, J. Kluge, E.A. Tripp, H. Mar-
tinez Piedra, H. Hentrich and J.-M. Tompkins for help
during data collection, M. Weist and A. Schmidt-
Lebuhn for help during nectar collection, P. Endress, J.
de Vos, R. Carter, G. Thomas and P. Kevan for helpful
suggestions and advice, B. Keller, S.W. Peters and A.
Egert for help during laboratory work, E. Benetti and
B. Seitz L€udi for help during literature collection,
Palack�y University for space and D. Ackerly, L. Bun-
nefeld and several anonymous reviewers for comment-
ing on earlier drafts. SA was funded by the Konrad-
Adenauer Stiftung, the Swiss Nationalfond and the Stif-
tung zur F€orderung der Pflanzenkenntnis. DH was
funded by the European Social Fund and the State
Budget of the Czech Republic (project no. CZ.1.07/
2.3.00/30.0041). AMH was funded by a Swiss NF Fel-
lowship for Prospective Researchers (grant PBZHP3-
133420) and by Carl Tryggers Stiftelse (CTS 12:409).
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Supporting information
Additional Supporting Information may be found
online in the supporting information tab for this article:
Appendix S1 Supporting figures (S1-S5) and tables
(S1-S8)
Table S1 Age constraints
Table S2 Parameter estimates from simpler OU models
Table S3 Detailed results of the differential rates analy-
sis
Table S4 Contingency table for NSP and PG coded as
binary variables
Table S5 Estimates of phylogenetic signal across 100
trees
Table S6 Model fit for less inclusive clades analyzed
separately
Table S7 Parameter estimates for OU models for less
inclusive clades (NFP and NGP)
Table S8 Distribution of PGs in asterids and less inclu-
sive clades
Figure S1 Lineages-through-time plots for three differ-
ent branch length distributions
Figure S2 Ternary plots for each PG separately
Figure S3 Sucrose proportion and sugar concentration
for specialized OW birds
Figure S4 Significance of rate shifts for simulated data
Figure S5 Selective optima inferred for NSP, NFP and
NGP in asterid subclades
Data S1 Literature used for constructing the asterid
summary phylogeny
Data S2 Nectar sugar concentration and composition
data newly generated for this study; and literature
sources for published data analyzed in this study
Data deposited at Dryad: doi: 10.5061/dryad.1r45h
Received 20 June 2016; revised 8 October 2016; accepted 12 October
2016
ª 2016 EUROPEAN SOC I E TY FOR EVOLUT IONARY B IOLOGY . J . E VOL . B I O L . 3 0 ( 2 0 1 7 ) 1 1 2 – 12 7
JOURNAL OF EVOLUT IONARY B IO LOGY ª 20 1 6 EUROPEAN SOC I E TY FOR EVOLUT IONARY B IO LOGY
Evolution of floral nectar sugar composition 127