doi: 10.1111/jeb.12991

Pollinator adaptation and the evolution of floral nectar sugar composition

S. ABRAHAMCZYK*, M. KESSLER†,D.HANLEY‡,D.N.KARGER†,M.P.J.MULLER€ †, 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: Abstract asterids; A long-standing debate concerns whether nectar sugar composition evolves fructose; as an adaptation to pollinator dietary requirements or whether it is ‘phylo- glucose; genetically constrained’. Here, we use a modelling approach to evaluate the phylogenetic conservatism; hypothesis that nectar sucrose proportion (NSP) is an adaptation to pollina- phylogenetic constraint; tors. We analyse ~ 2100 species of asterids, spanning several plant families pollination syndrome; and pollinator groups (PGs), and show that the hypothesis of adaptation sucrose. 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

Correspondence: Stefan Abrahamczyk, Nees Institute for Plant Understanding the evolution of floral rewards is central Biodiversity, University of Bonn, Meckenheimer Allee 170, 53115 to understanding the evolution of plant–pollinator inter- Bonn, Germany. actions. Nectar is the main floral reward provided by the Tel.: +49 228 734649, fax:+49 228 733120; e-mail: stefan. vast majority of modern angiosperms (70–80%, [email protected] Aelys M. Humphreys, Department of Ecology, Environment and Plant extracted from Heywood et al., 2007), but despite coad- Sciences, University of Stockholm, SE–10691, Stockholm, Sweden. aptation between plants and their animal pollinators Tel.: +46 (0)8 163 771; e-mail: [email protected] being thought to be one of the key mechanisms

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responsible for angiosperm evolution and floral diversifi- tubular flowers tend to have high NSP and shallow cation (Stebbins, 1970; Harrison et al., 1999), our under- flowers tend to have low NSP (high hexose proportion; standing of the evolution of floral nectar remains poor. Percival, 1961). This correlation has been attributed to On the one hand, it has been suggested that the chemi- the environment, because open flowers run greater risk cal composition of nectar, an aqueous solution compris- of nectar evaporation, rendering them useless to polli- ing primarily the monosaccharides glucose and fructose nators (Baker & Baker, 1983a). Hexose solutions have and the disaccharide sucrose (Baker & Baker, 1982), is higher osmolarity, and therefore lower evaporation as an adaptation to the nutritional constraints or prefer- rates, than sucrose solutions, and this is thought to ences of a plant’s pollinator(s) as well as to flower mor- explain the correlation between shallow flowers and phology (Baker & Baker, 1975, 1982, 1983a). On the nectars with a high proportion of hexose (Nicolson other hand, the sugar composition of floral nectar has et al., 2007). However, high-hexose nectars also tend to been found to be relatively invariable within plant require more water. In Mediterranean regions, there is clades, with any interspecific differences being indepen- a predominance of tubular flowers with high-sucrose dent of the plants’ main pollinators (e.g. van Wyk, 1993; nectars, suggested to be the result of selection against Galetto et al., 1998; Nicolson & van Wyk, 1998; Galetto high-hexose nectars in a warm, dry climate (Petanidou, & Bernadello, 2003; Rodrıguez-Riano~ et al., 2014). These 2005; Nicolson et al., 2007). This correlation reflects the seemingly contradictory perspectives call into question physical constraints of sugar solutions themselves, but our understanding of what drives the evolution of floral it is also thought to constitute evidence for adaptation rewards and, in particular, floral nectar. to pollinators because a plant will only be regularly vis- Early studies documented convergence in the sugar ited by efficient pollinators, whose requirements of suf- composition of nectar among plants pollinated by the ficiently dilute, easily accessible nectar are fulfilled same pollinator group (PG; Baker & Baker, 1982, (Nicolson et al., 2007). 1983a). Various groups of insects (bees, wasps, butter- Given the obvious adaptive advantage of a good fit flies, moths and some groups of flies) and several between floral traits and animal pollinators, it is sur- groups of vertebrates (e.g. hummingbirds, sunbirds, prising that more recent studies of plant species polli- honeyeaters, phyllostomid and pteropodid bats) are nated by different PGs have failed to find NSP values obligate nectar feeders and, by visiting flowers regu- characteristic of the individual PGs (e.g. van Wyk, larly, often also act as pollinators (referred to as special- 1993; Galetto et al., 1998; Nicolson & van Wyk, 1998; ists; Fleming & Muchhala, 2008). In addition, a Galetto & Bernadello, 2003). Instead, similar NSP has surprising variety of unspecialised vertebrates and been recorded for closely related species in the same insects (songbirds, geckos, mice, kinkajous, short-ton- plant family (e.g. in Gesneriaceae, Proteaceae and Scro- gued flies and some groups of beetles) are known to phulariaceae), and in aloes and relatives, NSP has been feed on nectar occasionally (referred to as generalists, found to be conserved within but not among genera, e.g. van Tets & Nicolson, 2007; Nicolson, 2002; Hansen irrespective of PG (e.g. van Wyk et al., 1993; Nicolson et al., 2006; Johnson & Nicolson, 2008). These animals & Thornburg, 2007; Rodrıguez-Riano~ et al., 2014). lack special morphological adaptations to feed on nec- These findings have led to the suggestion that there is a tar, but are still known to be effective pollinators. How- ‘phylogenetic constraint’ (sic) on the adaptation of NSP ever, their nutritional requirements differ from those of to pollinators (Galetto & Bernadello, 2003; Thornburg, nectar-feeding specialists with respect to sugar concen- 2007; Rodrıguez-Riano~ et al., 2014). For example, it has tration (in solution) or composition (relative contribu- been suggested that the differences in NSP between tion of sucrose and the two hexoses, fructose and plants pollinated by hummingbirds and passerine birds glucose, to total sugar content). Although most special- might be because they belong to different plant clades ist PGs, such as moths, bees or hummingbirds, prefer rather than due to any innate differences in the nectar with a high sucrose proportion (Nicolson et al., requirements of the pollinators themselves (Nicolson & 2007; Johnson & Nicolson, 2008), nectar-feeding bats Thornburg, 2007). prefer a low sucrose proportion (Baker et al., 1998). Considerable attention has been paid to the question Similarly, sucrose-rich nectar cannot be digested as effi- of what causes interspecific differences in the relative ciently by, or is even toxic to, some generalists proportions of fructose, glucose and sucrose in nectar. (Martınez del Rio, 1990; Martınez del Rio et al., 1992). To date, the debate has generally been centred on a Therefore, it has frequently been proposed that inter- perceived dichotomy between adaptation to pollinators specific differences in nectar sugar composition and and phylogenetic constraints (e.g. Schmidt-Lebuhn concentration, especially in nectar sucrose proportion et al., 2006; Nicolson et al., 2007). We are not aware of (NSP), reflect adaptations to the dietary requirements any explicit, biological mechanism generating the con- of different PGs (e.g. Heynemann, 1983; Martınez del straint being proposed and believe that focus on the Rio et al., 1992; Baker et al., 1998). perceived dichotomy between adaptation and conser- In addition, there is a long-recognized correlation vatism may have hampered progress into understand- between floral shape and NSP, such that deep or ing of how floral nectar evolves. In general,

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phylogenetic conservatism or constraint1 is often sugar composition of nectar as the trait and PG as the invoked to explain the lack of variation among close environment. We then test for a correlation between relatives or the tendency of closely related species to the trait and the environment, such that there is con- retain their ancestral state over time (e.g. Wiens & Gra- vergence of the trait in relation to the environment ham, 2005; Cooper et al., 2010; Wiens et al., 2010; Crisp (i.e. convergence of nectar sugar composition for plants & Cook, 2012). However, this conveys only that there pollinated by the same PG; Leroi et al., 1994; Ackerly, is limited trait variation among close relatives, not what 2004) and such that an adaptive shift in the trait is the causal explanation for the observed pattern might associated with a shift in function (i.e. a new pollina- be (Westoby et al., 1995; Blomberg & Garland, 2002; tion syndrome; Hansen, 1997; Butler & King, 2004). Losos, 2011). In the case of nectar, documentation of We also explore the nature of the hypothesized adapta- phylogenetic conservatism in sugar composition sug- tion by asking whether the trait or the environment gests limited variation among closely related plant spe- changes first (Pagel, 1994; Ackerly, 2004)? cies, irrespective of their pollinators, but provides no Pollinators are thought mainly to be sensitive to the insight into how floral nectar evolves, nor does it con- proportion of total sugar constituted by sucrose (NSP), stitute evidence for or against adaptation (Leroi et al., although that by fructose (NFP) and that by glucose 1994; Blomberg & Garland, 2002; Ackerly, 2003, 2004; (NGP) are thought not to provide reliable evidence of Crisp & Cook, 2012). Both stasis and change can result pollination syndromes (Baker et al., 1998). Based on from both adaptive and nonadaptive processes; for this, we analysed the proportional content of each example, stabilizing selection provides an adaptive sugar in turn to evaluate support for the following explanation for the pattern of stasis and retention of hypotheses: H1: nectar sucrose is an adaptation to polli- the ancestral state does not mean that the trait in ques- nators. This would be supported if a correlation tion is not an adaptation to something (Westoby et al., between NSP and PG cannot be rejected, if there is evi- 1995; Ackerly, 2004; Losos, 2011; Hansen, 2014). For dence that adaptation to the environment is rapid and instance, if a correlation between NSP and PG was accurate and if change between NSP and PG is corre- rejected, the hypothesis that NSP evolves as an adapta- lated, such that change in PG (the environment) pre- tion to PG might be rejected, but that would not pre- cedes or accompanies change in NSP (the trait); and clude that nectar sugar composition was an adaptation H2: nectar fructose and glucose are not adaptations to to something else, say, corolla shape and size (Nicolson, pollinators. This would be supported if a correlation 2002; Witt et al., 2013). Alternatively, a nonadaptive between the trait (NFP or NGP) and the environment hypothesis might be favoured if change in NSP was (PG) is rejected or if there is evidence that shifts in the found to be stochastic with respect to any environmen- trait in relation to the environment are slow and tal variable to which it was hypothesized to be an adap- achieved by stochastic, rather than adaptive, change. tation, for example if it were found to be drifting according to the allometric constraints of floral shape Materials and methods and size or the physical constraints of the environment. Thus, mechanistic explanations do not require infer- Nectar data ence of conservatism and can be distinguished using comparative methods, by setting up testable hypotheses We compiled nectar sugar composition data for asterids to be evaluated in a model comparison framework using published records and, focusing on previously (Hansen, 1997; Butler & King, 2004). Here, we use this neglected taxa (e.g. from the Old World tropics), col- approach to evaluate the hypothesis that nectar sugar lected and analysed new nectar samples for this study. composition, in particular NSP, is an adaptation to pol- We focused on the proportional content of the three linator preferences. We compile a data set that is main nectar sugars (fructose, glucose and sucrose) and unprecedented in scope for this purpose, with nectar chose the asterids because of their diversity in floral sugar composition, pollinator and phylogenetic data structure, geographical range and pollinators. Further- broadly sampled for the asterids, a major angiosperm more, a wealth of published data on pollination ecology clade of about 80 000 species (Bremer, 2009), including is available for this clade, accessed by searching for the carrots, daisies, heathers and mints. We define the publications in ISI Web of Knowledge and Google Scholar using the terms ‘nectar sugar composition’ and 1Phylogenetic constraint, phylogenetic conservatism and phyloge- ‘nectar sugar content’. In contrast to nectar volume and netic inertia are here used interchangeably to describe a pattern of total sugar concentration, which are heavily influenced evolutionary stasis, lack of variation among close relatives, and by water availability and microclimate, nectar sugar over time, or retention of ancestral traits. We are aware that use composition is relatively constant within plant species varies among authors and may even refer to the process of failing (Baker & Baker, 1983a; Schwerdtfeger, 1996; Torres & to change, adapt to some factor or occupy some habitat or region Galetto, 1998; Nicolson & Thornburg, 2007). The rela- (Wiens & Graham, 2005; Ackerly, 2009; Cooper et al., 2010; tively low level of intraspecific variation that has been Wiens et al., 2010; Losos, 2011; Crisp & Cook, 2012). documented is mainly due to differences among

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individuals and only to a small degree due to differ- characteristics of their food plants. Therefore, we ences between populations in the wild or between treated specialized, nectar-feeding birds from the Old plants growing in the wild or in botanical gardens (e.g. and New Worlds as separate PGs. Freeman & Wilken, 1987; Vickery & Sutherland, 1994; Several concepts for insect pollination systems exist. Lanza et al., 1995; Gijbels et al., 2014). We further The distinction between plants pollinated by short- reduced the potential for variation in nectar sugar com- tongued bees and butterflies, short-tongued bees or position by collecting nectar only from young flowers long-tongued bees (e.g. Baker & Baker, 1975, 1982, to minimize the impact of bacteria and yeasts, which 1983a,b) can be difficult to detect in nature (Schwerdt- are able to transfer sucrose to hexoses (Nicolson & feger, 1996). Also, the details of the pollinators of these Thornburg, 2007). We collected nectar between plants are largely unknown. Instead, we adopted the September 2007 and August 2011 in the field in Eur- two categories developed by Schwerdtfeger (1996): (i) ope, South-East Asia and South America and in botani- typical bee-pollinated, often zygomorphic, flowers are cal gardens. We used glass capillaries to collect nectar referred to as bee-pollinated, and (ii) relatively small, from at least three young flowers per plant species. The open flowers, providing access to the nectar for a wide minimum volume of nectar collected per species was range of insects (e.g. small bees and butterflies, wasps, 1 lL (Morrant et al., 2009). We placed the nectar on fil- flies and beetles), are referred to as generalist insect-pol- ter paper, air-dried it and stored it in silica gel for up to linated. Similarly, we recognized a butterfly-pollinated a few months to prevent microbial decomposition of and a moth-pollinated group, mainly distinguishing the the sugars. Overall sugar concentration (%) and com- species pollinated during the day and night, respectively position (relative proportions of fructose, glucose and (Schwerdtfeger, 1996). This contrasts with the various sucrose) were determined using standard protocols (SI groups of plants pollinated by different groups of butter- text). The proportional content of each sugar was nor- flies recognized by some authors (Baker & Baker, 1975, malized by logit transformation prior to analysis. 1982, 1983a,b). In the end, we defined nine pollinator groups: generalist insects, bees and wasps, specialized flies, butterflies, moths, New World bats, unspecialized Definition of pollinator groups birds, specialized Old World birds and hummingbirds. Due to the large variety of concepts for defining PGs, We obtained information on each asterid species’ these were considered carefully. Because plants that are affiliation to one pollinator group from the same publi- mainly pollinated by unspecialized nectar-feeding birds cations used to extract the published data on nectar (generalists) contrast in their morphology and physiol- sugar composition. For the newly generated data ogy with plants that are mainly pollinated by obligate (~ 30% of species), we used pollinator observations nectar-feeding birds (specialists; Johnson & Nicolson, from the literature (e.g. Jager€ & Rothmaler, 2011) or 2008), we treated specialized and unspecialized bird our own field observations. For species where the polli- species as different PGs. Generalist passerine and non- nator is unknown, we used categories based on floral passerine birds that feed on nectar, as well as on larger morphology, coloration and scent (Faegri & van der amounts of fruits, seeds or insects, are referred to as Pijl, 1978) because this is known to be a reliable unspecialized (e.g. orioles [Oriolidae], bulbuls [Pyc- method for identifying the most effective, main PGs of nonotidae], white-eyes [Zosteropidae], Hawaiian hon- a plant (Fenster et al., 2004; Rosas-Guerrero et al., eycreepers [Drepaniidae] and flowerpeckers 2014). For example, brightly coloured, often red, scent- [Dicaeidae]; Amadon, 1950; Stiles, 1981; Johnson & less flowers with long, relatively wide corolla tubes, Nicolson, 2008; del Hoyo et al., 2008). Some of these pending stigmas and stamens without a landing plat- birds (thrushes, starlings and mockingbirds; families in form were scored as pollinated by specialized Old World the Muscicapoidea) lack the ability to digest sucrose birds or, in the Americas, hummingbirds. Flowers with (Martınez del Rio, 1990), whereas others (waxwings; a landing platform, long, narrow corolla tubes and Bombycilidae) are able to digest sucrose but not as effi- bright colours were scored as butterfly-pollinated. ciently as they are able to digest hexoses (Martınez del Rio et al., 1992). In contrast, the bird species we refer Phylogenetic information to as specialized, such as New World hummingbirds (Trochilidae) and Old World sunbirds (Nectariniidae), Published, DNA-based phylogenies for most species in sugarbirds (Promeropidae), and some small-bodied gen- the nectar data set are available, but the DNA markers era of honeyeaters (Meliphagidae) and lorikeets used differ among studies, rendering data coverage for (Psittacidae; Hopper & Burbridge, 1979; Pyke, 1980; individual genes highly incomplete. Therefore, we used Stiles, 1981; Tjørve et al., 2005; Johnson & Nicolson, phylogenetic information from published studies for all 2008), take most of their energy from nectar and are sampled asterid species to generate a summary phy- able to digest sucrose efficiently. Behavioural differ- logeny. At the higher taxonomic level, we referred to ences between specialized nectar-feeding birds in the Smith et al. (2011) and the phylomatic webpage (Webb Old and New Worlds are associated with different et al., 2008). For resolution among and within genera,

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we used published phylogenies based on multiple genes the null expectation of constant change that is random (supplementary data, S1; Abrahamczyk et al., 2016) to in direction (Brownian motion, BM; Schluter et al., manually place species using Mesquite 2.74 (Maddison 1997). The first departure allowed the rate of change in & Maddison, 2009). Polytomies were randomly resolved nectar sugar to vary over time and among clades (‘dif- 100 times to generate a set of 100 trees that reflect ferential rates’), independently of PG. The number of some, shallower phylogenetic uncertainty (e.g. within rate shifts was increased incrementally until no better genera). The final set of trees comprised 2063 species, models were found (i.e. all shifts supported by for which both nectar and PG data were available. DAICc ≥ 6 were identified; Thomas & Freckleton, Many trait evolution analyses rely on phylogenetic 2012). For practicality and to avoid inferring spurious distances (e.g. all models founded in Brownian motion; shifts, the minimum clade size for detecting shifts was e.g. Pagel, 1999; Thomas & Freckleton, 2012), and set to 100. because the assembled tree lacked branch-length infor- Next, a series of Ornstein–Uhlenbeck (OU) models mation, three approaches for providing branch lengths (Hansen, 1997; Butler & King, 2004) was fitted. These were explored (Fig. S1). The most realistic distribution allow change in nectar sugar to be directional, towards of branch lengths, representing the results of numerous one or more optimal values, at a rate dictated both by independent studies (Table S1), was obtained by setting the strength of the pull (rate of adaptation) and the rate all branch lengths to 1.0 and then scaling the tree of (stochastic) change towards the optimum. The first height to absolute time using 110 published age con- model allowed directional change towards a single opti- straints (Table S1) in pathd8 (Britton et al., 2007). 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 Model fitting in a Brownian motion framework: change in the differential rates analysis; 16 putative adaptive and nonadaptive models optima; see Results), and the third allowed the mean We devised a series of models (Table 1) that allow optimum to differ among species pollinated by different change in nectar sugar to depart in various ways from 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 k = 2 (root state and rate of change) 10539.4 8820.2 9901.5 random in direction, with a mean change of zero and a rate of change that is constant over time and among lineages Differential rates As BM but the rate of change may vary over time k = 2 + 2n (root state, n number of 9931.7 8004.3 9220.2 and among lineages rate shifts and n + 1 number of rates) OU-1 Nectar sugar evolves independently of PG but is k = 3 (rate of change, strength of pull 10160.5 8417.5 9398.0 directional, towards a global optimum state; the [=adaptive change] and 1 trait strength of the pull towards and rate of optimum) (stochastic) change towards the optimum are constant over time and among lineages OU-Clades As OU-1 but directional change is towards several k = 18 (as OU-1 and 16 putative 10134.5 8357.8 9342.8 optima, which may differ among clades (defined optima) as having their own rate of change in the differential rates analysis; Table S3) OU-PG As OU-1 but directional change is towards several k = 11 (as OU-1 and nine putative 9149.1 8395.8 9344.6 optima, which may differ among PGs; thus, optima) nectar sugar evolution is dependent on PG OU-2 As OU-PG but directional change is towards two k = 4 (as OU-1 and 2 putative optima) 10096.3 –– optima, which may differ between generalist and specialist PGs OU-2V As OU-2 but the rate of change may differ k = 5 (as OU-2 and 2 putative rates of 10098.2 –– between optima stochastic change) OU-2A As OU-2 but the strength of pull may differ k = 5 (as OU-2 and 2 putative rates of 10096.9 –– between optima adaptive change [=pull])

BM, Brownian motion; OU, Ornstein–Uhlenbeck. AICc values in bold denote the best-fitting model.

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models in which the adaptive pull or stochastic rate dependent model and four in the independent model may vary among optima (Beaulieu et al., 2012) were (Table 2). Models were fitted with 10 mL iterations for explored, but with 9 or 16 putative optima, such mod- each of the 100 trees using the discrete functions in els soon become highly parameter-rich. Although the BayesTraits V2.0 (Quad Precision version for large trees; current data set is large, not all putative optima are rep- available from www.evolution.rdg.ac.uk/BayesTraits. resented by many data points (Table S8), and prelimi- html), and fit was compared using a likelihood ratio nary findings indicated that one or more parameters (LR) test with four degrees of freedom (d.f.) on each could not be reliably estimated. This resulted in a sub- tree. optimal model overall. Results for these more complex models are therefore considered unreliable and are not Robustness of results to phylogenetic uncertainty reported. Instead, to further test our hypotheses, three and scale and compared to simulated data simpler models based on the results of the OU-PG model (see Results) were devised for NSP only Three sets of analyses were performed to test the effect (Table 1): one in which the mean optimum was of (i) phylogenetic uncertainty (by comparing the phy- allowed to differ between specialist and generalist PGs logenetic signal of each nectar sugar and pollinator data (OU-2), one in which rates of stochastic change across the set of 100 trees), (ii) phylogeny alone (by towards those optima may also differ (OU-2V) and one comparing results of the differential rates analysis to in which the strength of the pull towards those optima those for simulated data) and (iii) phylogenetic scale may also differ (OU-2A). (by comparing best-fitting models across the asterids as All models were fitted using maximum likelihood a whole to those for a set of less inclusive clades). (ML) in R (R Development Core Team 2014), and Details of these analyses are provided in the SI text. 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, Table 2 Definition of rate parameters compared in the correlation 2012), and the OU models were fitted using OUwie analyses. (Beaulieu & O’Meara, 2015). Ancestral states, which Parameter Evolutionary transition* Estimate† (median [95% CI]) determine the phylogenetic distribution of each puta- tive selective regime, were determined using the equal- Forward shifts (0 ? 1) q – rates model in the ‘ace’ function of ape (Paradis et al., 12 Shift from specialist to 0.00077 (0.00048 0.010) 2004) for PG and manually for plant clade. generalist in high sucrose background

q13 Shift from high to low sucrose 0.018 (0.017–0.019) Model fitting in a continuous-time Markov in specialist background q – framework: correlation analyses 24 Shift from high to low sucrose 0.45 (0.015 3.1) in generalist background The results of the above analyses suggested that NSP q34 Shift from specialist to 0.0044 (0.0033–0.0058) (but not NFP or NGP) is an adaptation to PG (see generalist in low sucrose Results). To further explore this, we tested for corre- background lated change between the NSP and PG. We treated each Reverse shifts (1 ? 0) q – variable as binary, with PG coded as ‘specialist’ (bats, 21 Shift from generalist to 0.00 (0.00 1.51) specialized flies, bees and wasps, specialized birds, but- specialist in high sucrose terflies, moths and hummingbirds) or ‘generalist’ (gen- background q – eralist insects and unspecialized birds) and NSP as 31 Shift from low to high sucrose 0.054 (0.050 0.058) > ≤ in a specialist background ‘high’ ( 0.45) or ‘low’ ( 0.45, the 84th percentile q – + 42 Shift from low to high sucrose 0.045 (0.0083 0.48) [mean 1 standard deviation]) for all generalist-polli- in a generalist background nated plants; Table S4). Next, we used two continuous- q43 Shift from generalist to 0.030 (0.022–0.043) time Markov models for discrete traits to test whether specialist in low sucrose change in one trait depends on the state of the second background trait (Pagel, 1994; Pagel & Meade, 2006). The first model states that rates of change in one trait are inde- *Eight transitions are possible under the dependent model because transition rates in one trait may vary depending on state of the pendent of the other trait (i.e. 0 ? 1 and 1 ? 0 transi- second trait. In the independent model, transition rates in one trait tions occur at the same rate irrespective of whether the are the same irrespective of the state of the second trait. Thus, second trait is in state 0 or 1). The second model states q12 = q34, q21 = q43, q13 = q24 and q31 = q42, and the indepen- that rates of change in one trait are dependent on the dent model has four rate parameters. other trait (i.e. 0 ? 1 and 1 ? 0 transitions in one trait †Rate estimates shown are summaries across the 100 trees; com- may differ depending on whether the second trait is in parisons reported in the text were performed across each tree indi- state 0 or 1). There are eight possible transitions in the vidually and cannot be read directly from this table.

ª 2016 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY. J. EVOL. BIOL. 30 (2017) 112–127 JOURNAL OF EVOLUTIONARY BIOLOGY ª 2016 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY 118 S. ABRAHAMCZYK ET AL.

Results pollinated by generalist birds and unspecialized insects and high NSP for plants pollinated by all other PGs Variation in nectar sugar composition in relation to studied here (Fig. 2). This model is a much better fit to pollinator group the data (DAICc ≥ 783) than any of the other BM- based models. However, the parameter estimates from The nectar sugar composition data set comprised 2116 this model suggest that the adaptive process is weak species and subspecies of asterids, representing 660 gen- (Table 3). The stationary variance, a measure of the era, 55 families and 13 of the 16 orders. Roughly two- rate of drift relative to the strength of selection, is very thirds of these data (1480 species) were taken from the high (r2/2a = 2.5 9 105), and the phylogenetic half- literature (see supplementary data, S2; Abrahamczyk life, defined as the time needed to evolve half the dis- et al., 2016). Data for the remaining 636 species were tance from the ancestral state to the trait optimum, is generated for this study (577 species sampled from extremely long (ln[2]/a = 4.0 9 105 Ma). The simpler Botanical Gardens, 59 from the wild, with samples from models (OU-2, OU-2V and OU-2A), although a worse the wild spanning a range of families and pollinator fit to the data (third best overall; Table 1), confirm that groups [Data S2; Abrahamczyk et al., 2016]). A ternary generalist-pollinated plants are evolving towards a plot shows separation of nectar sugar composition along lower NSP optimum than specialist-pollinated plants the sucrose axis, with plants pollinated by generalists and yield phylogenetic half-life estimates of ~ 10 Ma, being found at lower NSP than plants pollinated by spe- that is, suggesting an adaptive process in which species cialists (Figs 1a and S2). Only hummingbird-pollinated are closer to their optimum and that is achievable plants show a skew with respect to the two hexoses, within about 10% of the age of the asterids (Table S2). being shifted towards fructose. There is a high degree of The second best model for NSP was the differential variation in the NSP of species pollinated by most PGs, rates model, in which 15 rate shifts were identified especially by specialized flies, Old World birds and but- (Fig. 3, Table S3). Seven shifts were slowdowns and terflies, and much overlap among them (Fig. 1b). In eight speedups; several shifts were nested and most shifts particular, we documented unexpectedly sucrose-poor were found in Ericales, where rates generally increased nectar for some species pollinated by Old World special- in shallower clades, or Gentianales + Lamiales, where ized birds that have nectar with a low overall sugar rates generally decreased in shallower clades. Most clades concentration (Fig. S3). identified correspond to, or almost to, major named clades. This could be an artefact of the relatively sparse Best-fitting evolutionary models for NSP, NFP and sample analysed here or, alternatively, suggests corre- NGP spondence between evolutionary processes and named The best-fitting model for NSP was OU-PG and for NFP clades that we are only beginning to be able to detect and NGP differential rates (Table 1). Two independent (Smith et al., 2011; Humphreys & Barraclough, 2014). optima were inferred for NSP: low NSP for plants

(a)Nectar Sugar Composition (b)

Sucrose Generalist insects

NW bats 1

Specialized flies

Bees and wasps 0.8

Unspecialized birds

Group means Specialized OW birds 0.6

Butterflies

Moths 0.4 Hummingbirds Sucrose proportion

0.2

0 Fructose Glucose Pollinator group

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.

ª 2016 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY. J. EVOL. BIOL. 30 (2017) 112–127 JOURNAL OF EVOLUTIONARY BIOLOGY ª 2016 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY Evolution of floral nectar sugar composition 119

20 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- 10 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). 0 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

Logit NSC –10 (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 –20 reverse transitions were indistinguishable.

–30 Robustness to phylogenetic uncertainty and scale and compared to simulated data Estimates of phylogenetic signal were constant across Pollinator group the set of 100 trees for all three sugars and PG (SI text, Fig. 2 Selective optima inferred for nectar sucrose content (NSP) in Table S5). Thus, our findings are robust to some phylo- relation to pollinator group (PG) in asterids. The main differences genetic uncertainty. The results of the differential rates are found between generalist and specialist PGs, with plants analysis differed for empirical and simulated data pollinated by generalist insects and unspecialized birds tending (Fig. S4). Thus, overall, the pattern of rate increases towards lower NSP optima than species pollinated by other PGs. See and decreases is not an artefact of the phylogeny and Table 3 for details. Colours and symbols as in Fig. 1. 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 Fifteen rate shifts were also found under the overall best because they can apparently be recovered with any model for NFP (DAICc ≥ 354; Tables 1 and S3). Half of trait. Finally, analysis of less inclusive clades revealed a these occur at exactly the same node as for NSP, and the strong effect of phylogenetic scale. For NSP, the find- other half occur only one or a few nodes away. Under ings for the asterids overall were confirmed, but, in the overall best model for NGP (DAICc ≥ 122), there was addition, differences among specialist PGs as well as support for 11 rate shifts. Again, shifts tended to occur at among clades were found (Table 3, Figs S5 and S6). the same nodes as for NSP, NFP or both. The pattern of Evidence for adaptation, for example as indicated by slowdowns and speedups was the same for all three sug- short phylogenetic half-lives relative to overall tree ars: decreases tended to occur in Gentianales and Lami- height, was much stronger for clades analysed sepa- ales and speedups in Ericales. The second best model for rately than for asterids overall. These findings were lar- both NFP and NGP was OU-Clades. 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). Correlation analyses: nectar sucrose proportion and pollinator group Discussion When NSP and PG are coded as binary variables, there is significant dependency in the data (P < 0.0001, Fish- Unexpected variation in nectar sugar composition er’s exact test, two-tailed; Table S4). Specialist PGs are for many pollinator groups more likely to be associated with high than low NSP, and very few generalist PGs are associated with high Based on the results of Baker & Baker (1982), we NSP (specialists are three times more likely to pollinate expected plants pollinated by one PG to have converged high-NSP flowers and generalists six times more likely on the optimum NSP for that PG. Instead, we found to pollinate low-NSP flowers). This association does not high variability in the NSP of plant species pollinated hold the other way round: both high-NSP and low-NSP by most PGs, most notably by specialized flies, bees and flowers are more likely to be pollinated by a specialist wasps, butterflies and specialized Old World birds than a generalist pollinator (68 and four times more (Fig. 1). The variability for these insect-pollinated likely, respectively). plants may be because of different preferences in males More formally, the model of dependent evolution and females (Rusterholz & Erhardt, 1997, 2000), differ- between NSP and PG could not be rejected for any of ent requirements for different pollinator subgroups

ª 2016 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY. J. EVOL. BIOL. 30 (2017) 112–127 JOURNAL OF EVOLUTIONARY BIOLOGY ª 2016 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY 120 .ABRAHAMCZYK S.

Table 3 Parameter* estimates for the best-fitting OU model for asterids overall and for each of the less inclusive clades analysed separately, where such a model could not be rejected (see Table S6).

h – h –

h – bees h – specialized h – h – AL. ET generalist and specialized Old World unspecialized h – h – humming- ORA FEOUINR BIOLOGY EVOLUTIONARY OF JOURNAL Clade Model† r† a insects h – bats wasps flies birds birds butterflies moths birds t1/2 (th) vy ª 5 5 06ERPA OIT O VLTOAYBIOLOGY. EVOLUTIONARY FOR SOCIETY EUROPEAN 2016 Asterids OU-PG 0.87 < 0.001 < 0.001 45.3 78.1 99.9 53.3 < 0.001 15.6 100 99.8 4.0 9 10 (114) 2.5 9 10 Fouqueriaceae + OU-1 0.19 0.087 – – 53.7 ––– 53.7 – 53.7 7.98 (67) 1.11 Polemoniaceae + Primulaceae Core Ericaceae 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 + OU-1 1.80 0.057 – 82.4 82.4 82.4 – – 82.4 82.4 82.4 12.1 (62) 15.7 Gentianaceae + Apocynaceae Rubiaceae OU-1 1.37 0.12 – – 78.2 78.2 – – 78.2 78.2 78.2 5.78 (56) 5.72 Gesnerioideae OU-PG 23.4 9.98 – 36.2 88.5 ––– ––77.8 0.070 (31) 1.17 ª Core Plantaginaceae OU-PG 0.69 0.068 < 0.001 – 57.8 ––– ––74.8 10.2 (46) 5.07 06ERPA OIT O VLTOAYBIOLOGY EVOLUTIONARY FOR SOCIETY EUROPEAN 2016 Core Acanthaceae OU-1 0.67 0.053 – – 60.5 ––– 60.5 – 60.5 13.0 (34) 6.26 Ajugoideae + OU-PG 81.9 9.74 – – 82.4 – 28.8 – 74.2 – 91.8 0.071 (34) 4.20 Lamioideae 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

*r2 is the rate of stochastic change (e.g. under drift or in relation to an unmeasured factor), a is the strength of the ‘pull’ towards the selective optima (rate of adaptation) in Ma 1 , h .EO.BIOL. EVOL. J. is the mean trait optimum, t1/2 is the phylogenetic half-life in Ma with total tree height (th) in Ma in brackets (ln(2)/a; the time needed to move from the ancestral state to the new 2 optimum) and vy is the stationary variance (r /2a; the balance between the action controlled by a and that controlled by r). Optimum values are shown as back-transformed mean estimates (% NSP; see Fig. S5 for variation around the mean). †OU-PG is a model in which the mean optimum may differ among pollinator groups (PGs). Not all PGs are present in all clades (see Table S8) so the number of optima differs among clades. Best fitting models and columns with two generalist PGs are bolded. 30 21)112–127 (2017) Evolution of floral nectar sugar composition 121

LAMIALES

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m i a

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r l a C r i i e u k y r i P u e a y a biflo r e C A phe h i e a n ia a an ri a e n s A h e r l i a A phe o a n ia a f a l n a a d e m i ni i i A phe m l r p o a u sa a n l i na A t n i s c p i y r C a M l cu a l s d e s A d er l d t l ma i l u h G a m sca a r o re p u s a A h er a z te an g g h s a a r q d vil s r rl l e i z i a a d y r b A l e l vo s a n m e a s v A l o n z o a r o d h r ba r o n d an i a A r u e r r b en ia u c a b u s smit c ti a n l n i e f g p e G y s a m r e ci i p a r r ila r l r ata a c c n a i a y a u e osa s Ap a r e a n c e n dii Ap r a e e i c u i eb v c r Ga G n r min s i i a W a al s c o u e p ili ic a V e A m s ry m ci e i Gy l a b h e a t u u c e o fl n a a A a t g b m u d l t r M a l M b a b u rs d r B a l l h l e i a m A M nt u g i r a B a s h d e a x b na a u ve a p e o a h i l a p yu o e h e n d G o n n o si a i Ba y o c yg e ta e n m a ry s b a d l B e i o c a b m n k m e m l b u a r li e al p r n a m of i i B r e c i a b y d r o N o v a arc p i B 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id t s e co o r l e u e o s t T e s s a n v sp spe u Tec c vi i h e m li e ro n at e lia e s t lo yl r u T a r n ch t n o oi e e w e ir e e t s Te e c rvi n id h flo a a c l z C m l s ne l us s a a n t ig c t h t ia li o e te r g s e us T r a s n a i s a ty e o gin C o r e a h c c In l a g t l o G a r l r i l c nc d p a b le a i u c lu d n q s v th ia n a e I ncao p m m el ar a o r o ly I I I e m a o e d a je a i at i e u a e v p o b n I P o m d th a v v lumm O a r i o a lp c a n d m s m i m r n h i r s D c o o i cu at r n n u iol suf s t g il d n a c a io r a cn a Co Co e i l y e i C e t h ia al a Co C neae r B a e c to o l i T e a h t e e ia ne c a a i ii i acopa ti i s l s T a ro t nt t m i i t des o a s f ro f n ll a p h d i ia a s at n l lu o i of r o t ata n a C h e n m ipl d o a y Co l u lum a u o i O n e r n c i t a c u m m m f s r i Sp ey p ly t n c a hoi la m e po i ti e m s Z a sc ent homega a a at is r C C C n r c c a m sc a u e c s Co l n s a um is H e c c a c r c e o ol o u n e e n ic in o A r i t p i ta e l m e t epp s s re s ant c a s h un anc e b m d m C u u l l a a e r edi al C e i i i a la v i m Co m C u u a q a op pec a C r c i a c dent n m tu o u o m m n o i i c i a y o e II u i Co ol m e p i s Cr er i a a a a a h t r lu n n xy u sp h a gi denode er r ic i r a unguc e l h c c o l ea um n n a u e na P i r c r r ta g la t u l mn e e g y i A r d e i p a c e n n m u Co C a e r p r e ll F i d e r ra a p a u a a a p h ce c a r i d e a n a lo n n Colm o o n m lo u F r i handr nd c i m n ic i I Co l e l s y I r d c hand g m e y n c e n u a u r e t a r r l ti F i i a b m s c c a C e m mnie a a r r io a la F r ic ha andi e g c a l ol um s g ig g t F ic h n ia a e iu m p u e C C um h a n nt u s a c m p ii u c s n o a Dol i o n p a h iu b C o o ir hi e h e andip i s t Dol n o o p p h iu m s tz s l C n t m n a ec fic a Dol ol m a a u o umn lu C a ea r ie a a g n m o p h iu m s h n c t l o mne ea n s s t a D g ilo p h iu li t a i s u l o v e u d u Bi e m h ilo h iu i n d c C m u l a h t pe e n II Bi n e o p b a s fr e u mn umn m a i a la a p h il p h n in p n o n e r e s A p h ilo o p lu c a e l C a a m l sim c n e An m il a e t a s u ea e in rt a m p h lo o i p e t v Co m o i e d ha II A p h i v tr h e a C C l n a ru e i o ea I A m h re t s o n n umn a a c r a A m a a p h e u C l o i eq a br i to r e mp e t a p h n a a u lu lu e car r d na i A r n t i C o m m a g ia i ni s A mp t n tar ar rp m ti im M lu Co m e u e e l A e ra y ce h o ne n m ag i cu l i i ra h yt ta a n na on N l m n a l n si s P u c h ig iss u e e i a t t i u h y it ju r t ia s a o e m n a lumne a c u mi t e a D ta c h a l i t o ea a r e e a D a c h a w r a a ia A phy n le b o n r S t p el m r l A m e v c n a ta te a g n r at a o a ea G llo A p ir y al s or S a i u c f in llopleA A l o a s i g r i S h s s ia j ifo u r ina ct lo p l lo ll r p doca hi s yx s io y il f ammi t r a l ll lop e to c a in in R a f c y s e r lia s e opect p a r t D o ys a s b fo so G c ec n a h ic 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2228 ec tran thu s a boi t husa t Pl c n s Ga erant p fo rba a le tra thu am xu st ans quirm ta P ec an us efle ra us Ae Aesce hus a te os Pl ctr th s r flo um ltat sch rant m ma ns a le ran hu ndi c xa yn hynanhus ac lan is P ct ra renai r e Ae a roc us Ple tranta g py s va sch nth thuscor a ec ll m oru us is A A yn us al lyx Pl uneinu nifl ae ns es esc a pa triclinus Pr m u rop rie A chy h nth ra olor r us eu na Ae A esc na yn us siti Ho op s ca sc es hy nth ant ev cu Lyc opu lla ii A hyn chyn na us hu rar s yc ne da en es an a nth pa s sp dii L dro nu as A chy thu nth us rv e 2276 Ce eta x fa ca ca es n s us ra iflo c ep iri ssi A ch ant rho lo dic ra N peta sib na lla es ynan hu do ng an Ne eta ar ete ch t s la de ica s ep ta p ep A ynanthu nc ndr lyx N pe n taria ra ca ga s m eola on Ne eta ca iflo tia D Did lm hus icr tu ep ta ran na idy ymocyla sp ant s 2277 N epe grand au ica m Di c ec hus N a e ex ris oc dy a hor io ch m est um arp mo rpu ise su Nepetasta he p cul Di us ca s h pa s Ag tac e ru eni dym atr rpu isp la gas ch fo folia oc osan s c ida A asta che tici C arp gu rini Ag ta ur a yrt us in ta gas che irsutaace rum C and rept eus A sta a h der lis iflo C yrtan ras an ga om he ina and ca S Br yrt d pe s A ch ma ffic gr davi na St trep igg and ras c II Gle ho us o lum ol a rep toc sia ras pec I lec p m yschi Strepttoca arp mu pec I Gysso cephaalum ru ns S o rpu us sci II H aco ph lum ta trept ca s st sax col Dr oce ha m nu da a Str o rpus om oru a rac ep alu un m ept car ca and m D coc ph orib ta ltissi oca pus ules ru Dra oce l nfer a Rhy Str rpu we ce s rac o s ssp nch epto s p ndla ns D pechiniainia fc nali R og ca oly ndii Le ech fici lis is hynchloss rpus anth p a of ina nal a o um ey us Le iss ffic ficiifoli lia J glos gard lesii Mel a o s ofplic riifo J asm sum n eliss rinuatri ula s asm inu sp eri M makia roph oide Jas inu m h ec Rosovs sc tan J min m m umi Per skia bro J asm um es le erov ia a asmi inu fru nyi P vsk rita s nu m s tica ero u en 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Sal hie osa a an stipu i alvia tepp a Palico gust la S lvia s oros Pali ure ifolia Sa nem Pa cour a an lvia ba Pa licou ea s drei Sa trilo ensis lico rea pec I Salvia prat sis P urea calycin I alvia en tii alico thyrsif a S a nama sone Palic urea lor Salvi rous a ourea luteo a lvia b tinos P sp n nivea Sa ia glu yana alicou ov ine Salv bulle Palic rea d alvia icosa R ourea rigida S a frut pitata Psych udge lobb Salvi ra ca P otria a cilia ii Thymb spec a sycho acumin ta tureja mbr Psy tria c ata Sa ja thy tensis chotr apen ature a hor na Psyc Psy ia ner sis S turej onta ca hotria chot vosa Sa reja m lmati Ps carthageria ela Satu ria da tica s ychot n ta rome croa rniolicu Psych ria to ensis Mic meria lgare sp ca otria mento icro m vu ides s Psych aubl sa Mriganu legio otria r etiana O us pu yllum Psy eticul Thym serp My chotria ata hymus itatus Psyc rmecod spec T us cap ox hotria p ia spe Thym praec Psy oepp c hymus ec chotria igiana T tha sp ta Arcyt Mo tincto Men f spica ophyl rinda cit ria tha c atica Arcytop lum ve rifolia Men a aqu Arcy hyllum rnicosum Menth rvina A tophy thym ntha ce ifolia rcytoph llum setifolium Me rotundrita A yllum pe osum Mentha x pipe m rcytoph ruvianu Mentha ulegiu Arc yllum la m entha p tha A ytoph varum M ia erian rcytoph yllum riv Cumin idyma GENTIANALES y d Arcyto llum cilio etii onarda na A phyllum latum M ella na tha A rcytoph capitat Monard macran a rcytoph yllum um nardella vulgare ylvatic yllum m filiforme Mo podium a ssp s Manetti acbridei Clino ium nepet a sp linopod nepeta Manett ec III C ium pifolia Ma ia spec II Clinopod hysso nianum M nettia in Hedeoma um virgi anettia flata nanthem pilosum Man cordifolia Pyc hemum ra Bouvar ettia spe Pycnant andiflo dia bouv c I radina gr B ardioide Con russeliana Bou ouvardia s Monarda ulosa vardia gl laevis arda fist folia Bou abberima Mon sphaceli vardia te Salvia s Pentas rnifolia via fulgen Penta lanceol Sal chyphylla s schimpe ata Mean rate: Salvia tra hylla ri op Leptoder ana alvia micr Phuop mis spec S spathacea sis stylo Salvia rons Farame sa lvia amplif Farame a uniflora Sa eggii Far a coerules Salvia gr amea cf glan cens ia mexicana Coccocyps dulosa Salv marissima Heter elum cond Salvia a lens ophyllaea p alia Salvia squa Oreo ustulata ahuilensis polus glacial Salvia co lus Gardenia t is Salvia styphe hunbergia oppositiflora Gardenia t Salvia m Oxyanthu ubifera lvia divinoru T s formosus Sa spec II ocoyena formo Salvia Randia sa lvia stricta scortechinii Sa splendens Randia spinosa 0.25 0.8 2.15 2.85 3.35 5.75 8.64 Salvia Pa lvia heerii Bu vetta revoluta Sa antha rchellia capensi Salvia iod ylla Albe s Salvia macroph rta magna purpurea Ixora chin Salvia ensis 2069 Salvia regla Ixora Sunkis Ixora finlays t Salvia farinacea oniana a karwinskii Ixora coccine Salvi fertiflora Ixora javanicaa Salvia con Ixora Salvia tortuosa coccinea f lutea ia spec I Mussaenda a Salv Mussaenda eryth licia Salvia coccinea rophylla ugata Mussaenda nervos Salvia corr Mu a Salvia guaranitica ssaenda mutabilis des Mussaenda phillipica Salvia lavanduloi Mussaenda angustisepala Salvia discolor Salvia lemmoni Pseudomussaenda flava gesneraeflora Pentagonia macrophylla Salvia Dioicodendron dioicum Salvia pichinchensis Warszew 3112 Salvia uliginosa iczia coccine Virectaria major Salvia pauciserrata Sabicea panamensis Salvia lasiocephala Hoffmannia ghiesbreghtii Salvia patens Hoffmannia refulgens Salvia sprucei Hoffmannia nebulosa Salvia iodochroa Hamelia patens Salvia elegans Salvia semiatrata Hillia macrophylla Alangium platanifolium Hillia wurdackii Cornus orbiculatus Hillia parasitica Cornus nuttallii Cosmibuena macrocarpa Cornus sericea Chione costaricensis Cornus m Ladenbergia sp I acrophylla II Cornus sanguinea Ladenbergia sp Eucnide aurea Stilpnophyllum oellgaardii s Nasa speciosa Isertia laevi Loasa triphylla Gonzalagunia dependens Loa gunia rosea sa argentina Gonzala Jamesia amer Timonius spec Hydra icana lojensis ngea quercifolia Arachnothryx Hydrangea anomala Guettarda speciosa Philadelphus c odorata oronarius Rondeletia ntalis Philadelphus serican Cephalanthus occide Philadelp thus ura vargasiana hus schrenkii Notople a Kirengeshoma palma Mandevilla pentlandian Deutzia ta a petrea glabrata Mandevill Deutzia gra devilla hirsuta D cilis Man stifolia eutzia purpurasce Mandevilla angu I Deutz ns Mandevilla spec Nora ia crenata anderi ntea spec Mandevilla cf s Norantea b andevilla laxa Marc rasiliensis M rophylla gravia spec Parsonsia hete Marcgravia m jasminoides Ma nepenthoides achelospermu folium rcgravia brown Tr m androsaemi Impatiens ei Apocynu dium baronii I irangiensis Pachypo lentum 3820 mpatiens mo ium succu Impa rsei Pachypod spinosum tiens namch hypodium bi ryi Impatiens m abarwensis Pac podium deca Impa arianae Pachy m hybrid Imp tiens zomben Pachypodiu um atiens mo sis m densiflor Impat ntalbana Pachypodiu lamerei iens oncidio achypodium c I Impatiens e ides P ibatalia spe Impa riosperma K pec II tiens pauc Kibatalia s Impatiens identata obesum Impa elephantic Adenium folia tiens nyung eps ra oppositi I Impatien wensis Acokanthe ghtia spec Imp s parviflo Wri pec II atiens text ra Wrightia s Impatien ori nocarpum Imp s noli tang stema ste ahouai atiens pa ere Stephano hevetia Impatiens rasitica T ia peruviana Impat balsam Thevet rnuta iens repe ina vetia bico a Impatiens ns The neriifoli Impati flaccida Thevetia vata Im ens sake hevetia o s patiens riana T mangha 3821 Impati hians era ens Cerb odollam Impati mackey erbera rica Im ens mac ana ssp C ze CORNALES nda catha i patiens p keyana s nkeri Allama schotti Impatien latypeta sp clae llamanda na Impati shawk la ri A rnaemonta a ensha eri red nia tabe matran Impa wkeri w Amso olfia su ustrina Im tiens so hite Rauv ia cf lig ina patien denii Rauvolf erpent Impa s kilima volfia s roseus Im tiens ps njari Rau anthus inor patiens eudovio Cathar inca m ii Impati burton la V griffith Impat ens nia ii Kopsia ea iens hocmniam ia arbor Impat hste ensis Kops ticosa Im iens ca tteri sia fru is patien tatii Kop rinens Fouqu s auric catha iphon Fo ieria s oma ontana achys ens uquier plende rnaem tana p a serp Bonp ia digu ns Tabe aemon Hoy ngifolia C landia etii abern oya lo onii obaea gemin T H thoms na Cantu scan iflora Hoya entia Ca a que dens oya k nosa ntua rcifol H lacu rii Cantu cande ia Hoya a ker C a pyri lilla Hoy osa P antua folia carn olem buxifo Hoya a bella Po onium lia Hoy tralis P lemon pauc a aus ra olemo ium c ifloru Hoy ultiflo Po nium arneu m a m alis lemon repta m Hoy peri Polem ium c ns oya im hlebia Ph oniu aerule H entap ta 3825 lox ni m cae um p su Ph va ru Hoya ia hir ta lox su lis leum ischid ia ova II Phlo bulat var a D ischid pec Ph x dru a cutiflo D nia s ens lox p mmo rum arsde umb Phlo anicu ndii M proc cifera Gil x diva lata sma seri ana C ia trico ricat Telo raujia teph ii ollo lor a var A ys llies Loe mia l laph a brach rtia gi um L selia inear amii rreni libe ine m oese amp is Mo Phi cocctianu Loe lia ci lecte talum rnot eum Ipo selia liata ns lyope lum a erul ia mop mex Amb peta m co stifol Ipomo sis ican Oxy etalu ngu iaca Ip ps thurb a xyp ias a syr omo is rub eri O lep epias Ipom psis ra Asc Ascl uticosavica Ipo ops long epias frassa mops is ma iflora Ascl cur naria Ma is com ias li aria M esa aggr bii sclep clepiasndin nii aesa arge egata A As hiru erso Mae per ntea cum and rica Ja sa h laria toxi gia s dina lis D cquin upe nce ope na au eh ia a hens Vi Cer entia ac ifolia An erain ura is G ntiana st a aga ia s ntiac Ge angu lute And llis t mar a tiana iana he Co rosa enel agdi Gen Gent onant ii So ris m ce v la na m alujew lda ons italia pneua w etica Pri nell peli na iana tian tib na Pri mul a al ensi Gent Gen tiana ver mu a ob pina s Gen tiana folia Pri la bu coni n sedi ica P mul lley ca Ge na man s rim a po ana tia ger ulu Pri ula lyn ssp Gen lla hirc ec P mu jeso eura be tiane lla la sp ec rimu la fo ana esia Gen tiane nel a sp Prim la rbe na Gen ntia leni na P ula mal sii Ge Ha ellia ea rimu rus aco dd iad Pri la r byi ides ia we clep mus Pr mul usb ssp len as rri c imu a hi yi v rus Ha enia lche spe Prim la mrsut ar e byi Hal s pu hus us Pr ula arg a llisia thu nt gon d P imu allio ina e olan bola caly ine rim la p ni ta mb Sym hus nov tus Pr ula ede i Sy nt pec ala gii P imu au mo bola s s us rlin rim la p ricu nta m hu nth ha na Pr ula ali la na Sy nt lona ea iroa ca imu pu nur mbola he rpa sod tilu Pri la lve i Sy C roca ea oc s P mu japo rule ac rpa ea n escenns rim la e nic nta M oca rpa bor gra Prim ula lati a acr oca ar fra sa Pr ul ve or M acr ea ea emo ns D imul a ju ris M arpa gra rac sce ion a v liae oc Fa ea gre rens Pr ysi ulg acr gra s ni rvi m P imu a a aris M Fa thu e neu I rim la reti an sempcya ec P ula bov oid Lisi m a sp a rim ed ean es miu rom ma e Prim ula elbe a lse och hro occin es 3832 Pr ul ver rgi e I c c id i a tic i G Io a sio ina Pr mul rose ill rom ch lyc c II P im a f a ata ch a fu ca e rim ula lorin Io om ma a sp lora Pr ul via da chr hro om vif lis P imu a d lii e Io Ioc chr bre ra I rim la c en Io bia ust c I P ul ap ticu so lia a spe II Pr rim a d ita lata as na lia ec I a imuula aria ta V Du na sp lat Pri la fro lic Du lia icu ec Escmu fa ndo a una asc sp la h rin sa D f cha olia Di hw al osa alia ra if D osp eil leri n Sa rass ana ios yro era Du is c uvi ylla Sy py s ov sal per ph na P mp ros virg at hy is ero ica a ter loco lo ini a P ysal het x ss Sty ost s tus an Ph lis me pre na S ra yra sp a gia ad gia c tyr x o x ec hysarin ia lin spe Eu ax ffic cor P the an har c II Vi rya jap ina ym Wi th ia resia pe I sne ja on lis bo Wi es at a s pec Ste a poni icu su atr Cu o s olia C wa m c s s SOLANALESCu chr roa nif m C am rti oc a pi ch ga uu a el a psaner Sal lpi ri n rea C me lia eu Sa a o an bo tii am lli jap doc hro um ar igh Ca el a s oni pic sic cf wr m Cammel lia tsine ca am l ap ra ra niu s Sar lia a ns el Sa C atu atu mo ide l ell s ii is lia D D tra elo te Sar rac ia c alic a s et me ea S rac en us ifo ur m ra r a ar e ia pi lia at ra tu au ol S rac nia m da D atu Da sia nic ns E arr eni p ino ta D an ca ole a nk ac a ur r m ul ve ne Ar ia en al pu rug a v ua ui lis A ctosnth ia ata rea B si s ng ina 3241 rb t us fla n a ut a v a sia s ffic pec Ar u ph ca a m n sia o s ha D bu s x yl m ruggma n ra ea is L rac tus al os pa B ru ma go ka urantbil eu o a ap uv nul B ug dra ar no ca A c ph ndr en a at Br n M ne tia a cro op yllu a sis urs us Ma kea ea an ios Pie tr og m ch i ar ana ur ec a A ri ich on s ne M Tri a sp xim a ga s j e p ec loa a a lor Ag ris ap pa arv un ul llo m dif ec A ar ta on tula ifl du n nu ra an sp ii nd ist o ic or m Jua a nd gr ra rs G ro a lei a us Ju ola a d ie G aul me his fol S dr lan s m liume a th d pi ia lan o u tifo ns Gauult er a p du o S on ui ile m V l he ia o la S c in ch u e V ac th ria sl lifo oder m r lifoli ra i a cin eri s eu lia x va va fi rga le V cc iu a er me E e e ar ve co V ac ini m eriora ri ns ns e v r es lium a cin um c p ta an le ile s va d fo m Dimcc iu on hy a hi ch len e ar rti atu m V in m uli sa lla c hi ns v fe ili u a or ium s gin n um ium c ile se on c cin m O cc ph mpe o gu ci yc um ch en r c m ly su G rth in an y c su ine Ly L ci hil a iu no tum ay a ium th rt m u Ly ium c e v Lyc r ca i a m G lu ea e illu m c m s va isp ng nu ay s cf vitis ra s Ly ciu len m nu lo ca um Ga lu sa a sp Ly hi u te e ri st m Ag y ss ci b id e c os ar m e au u m A a lus a a jobre ae c in v iu am inf ine u i g pe sa cia r vi a cium isp m Lyc m m s gi Agaap te ci chadan ata Ly u su u um vi odo n i A e s a e ten o yci i m n ro ino g pe te se de m n pin L Lyc u o h m A ap te s l rp n iss sis um is yci um m eg tu s Agga e s ob en sa o i nu L yci um m ea e pe te h b s n Lyc te L ci a n oidum Sa ap te s b os ii is m Ly m cu tr n m C ty e s u se u iu m es ia du a C av ri te in xi a yci yc iu c ies a li a e a s m cu fol na L L c m ill cl us C ve nd w a rv iu Ly iu g do grifolb s C a n is ar c a s yc m i te a u a ve di hi sz ra ta L iu ach in s e lis C v nd sh a n ew nt yc r a u aur ta a en is ia o ic ha L m os am s n na Ca ve di h c b z iu or y u rie on s C v n sh ia om ilis ii b sc m o d i a enddis ia c p v LycJa yo ya a lla ens C vendis h q os le ar H sc in e i ianafii C av ish ia u ta cte c o la b et f av end ia sm ere ric n ap Hy ch pa g dor a C endi h b m e s it so bonarfor at ra C av is ia ra ith e ns ata Atro al lo a a endi s hi c c ii is Phy iana langs if li Se ve h a al tea ot iana ianan g ifo is T mi n s ia m lis t ic ot ot lo in str s T hi r di hi c el ta a N ic iana c a g de h ba amsh a api as N ot Ni n baylveoi ra Sp ib u ia cr t tom ic tia m s i lo a a d isi e as ul N o lu a un tif Sphhy ud ia a n s at oi ic p n et auc Or ro ia m sp d ifol a d N a tia p nocgl ana e yr s f a e re ia es an co a ic ior Ce a os pe lo rti ci si ti an r s a C r nt p r rib ni osai co Ni ti ianaiana af cel tic a M er at h e m u an i co ot ot x s li i a a os es rmumum nd a N c ic ana ru ifo i M c to te h a Ni Ni N i a ea d nd a M a le st m yp co cot an n or o or a cl a e a o b r ti tia c im h m M c ea ni m a g u di Ni co o a a p u P acl le n a a la a xi fo ic n r to ac ilis s e an ia m re tu eu fo liu Ni N tia na o b b m Ps am a ia s o g m s liu m o ia a ta ta u P a n mi lli in m ic t an a u ac ums P s mmm ia gl t s al N co ti n m ti s n s a is i ab h di i o a n o a B a m i ia nsi r ia i N ic otia n a b eg um Leej m m si sp g a na N ic tia ur ym l n m a m is a n N o a e ur tu m R du ria is ia ra ec is ic m cor m ct a u i R h m ia g e m N ru ru o te re qu h o ra cu ifl st m st c u r m R o d p ce u o e tru e m n ra rp pa R ho d od al m ia ad ra C s C b u inu m h d od e us o n o e tru f p m c tu m Rh o o e nd tr s e re C s ru tta la u R d d n r e a n n e m cum st si u li da od o e d o si si C ru tr e p ic fo ti a R ho o de ndronro n f s s st s C sc ri e n Rhh d d n n a e e m au fo ca sa i o o e d v rre C C ru fa l a ri io ni Rh o d de nd ro a st m m ti e c o ta Rhod d od n r n ho se ra e u s m pe s o o e d o s n y e C tr tru e a s e ua a R do d n r n ims g i s s V a a m n at a R h d en d on kius k e e lli lli ja si d ic R h od o e d ro c i on C C a a n is nu n ta h o oddenn r n a i i g w w e e go a is R o d d on m n a e o ol d a ric r c R h d od e d ro e a nu n Br Bro s loss at b lla ho od o e nd ronn ba d d m se to ig nap m xi pe a R o de n r a r d ens p lp ia i a s an e R h d d n d on s rb ba ia re b a a a ia c r h od o e d ro im o t n e Sa a an n n ri ra R o o d n ro n o re u u St F bi ia uni tu milo R hodod d e dr n lu cc ia u m m a b e me ia if o e ndr on t i ru m F a et P a ls c atus R hodo d n st e den m F P a fe n ea il R hodod e dr o c ri u i n au ur n R hodo de n o n al g m t s u p pin p d n dro n pontw o illo al r a ur ea a R h e dr il p s e ERICALES o nfel B lsi us o albali ho d e ndr n lia h u ru e p m a fo ta R o d ndr on a msyt m B nf th a ri lit R ho do d e on rb i um u n e ba c 3438 h e n on b o cu i r Ipo o s R do d n dr ak a B iza moe ed l o a R hodoodo en d on ner re m n o omoeh en n ri Rhoho den ro at e s um ch Ip Ip a ea amsc ia a den dr n l ii ri ce S e o e it c ra Rho d dr on m a flo n o r ri o a R d o den ch oulnt r s om a quor uai fl c o d dr on a icumu Ip b a c ri i ta R ho d d e dr on k m m m om oe m b d a h d o e n ci ei ai Ip m a u in n mi R o o d n dr on l s p a area e r a i y c R h d d e dr o v ia k io ne oe o o a e m n e c h o o e n n b ir t ei n Ipo m e o u o e R o d d n d o l u ios um ia ns m m o o c r sp p s R h d o e dr ronn e r e e o o Ip m a ie a s si R h o o d n i p m u Ip Ip om o a h e n m o d d e d o n id anim p Ip e a o a e s R h d o e n r n c tr o I o e v ru u h o o d n d o r u ic s o m mi r o c m R o d d e d ro n u n at t cum m o a e ri iu a R h d o e n ro n k s e u yl o m Ip rre s n b p t h o o d n d e s at m u Ip o e u c a e ra is R o d d e d ro n v l a u m Ip M l s t s o s a R h d o e n ro n i e e tu m vu n d n s R h o o d n d n rs tic m l lu ia o e o llii o d d e d ro n h u te u o u cag u e R h d 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i a p onse u lt i ide e u a r n s E r c v h c h h A nchus lep c e lo la E r ic a u lo e c A hus b a rv y a la i a s e y pi n s r a a ll t s il ri E ri c p i r lic d a iifo An ncnc s e a s s s E r c a ti s i c a A A u s is a e u lie a ic a c e e ic fol ua li hus h u s s h p e n a E ric a c e rs n o u c c h p u t ia t a Er r a ri p s lo ia m n n c o h a a rr k a E ic a ma r n i r A A n c c s s a ti g re a i a b n th c y n u u b e e c s E ri c a s e u A L h h r zu ti li E r c a h n s a o a A h c tis g a E ic a a i c n t c g a yp ta s ri a l fo e k o d n o a a g n li E r c e l mas n e A A l tis s e e cur l E r ic a c u ia ia ii s g t ia u ri s lis a ic a c u c c o lo k a b a r a E r a r o e to n g a h a o o mo b E r ic p a v a z c s n in te m i a g a ff i tr c o n a ia ic ru u e E ri c i t r fl a o Cy u A u o ri r ff l tu l r c a b lv e a o c d m m a ia a a E i a m a r r h o Cynr ch a n o r a n E r c u a s a e n n te n o a e rd i umlis ic a fa a o s o n n c c e E ric e n la Ho A m riao o 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n m u is c on c W n u m s P g d s e e fr i s is n e rvi r is m lo o n n t s ut d a r e e a W e i n u m c e r i r e ap t ll a e i g u he a b e g n L e m m s j c c p y W g e l m op o t e d ir ia r a s s H e ig e la m r u p r iu r a e oli e l n l l s n Cy e M o h a i a ph f a L e ig e la ia d e u h p piu et v d b i i T e i la lo t a u r s o c o r i ca e c pt g e i y s h Cy M i m h n rd co num ea S r y e l d h n n vi lu i ii t r tr tro a a s ii Lo ios ce a i su e y i u i T iu E ni i o u aculataia cax L y la a b c d s L io o d ig a e oni ac is L m c c e s i l p i C l in j u s o nic t s odi p b o r i e o s n d m aci s a L o n phoeu c r id r elior k W r a anacet g jap r n pi r L o te o a s r a H c a r ea a L o ni ic e e a a H g li i ea h ie le li a n m r um ra e i e a t v r t b r ig i L o n ce e r i s liot di Co o n o l a L n ic a r a e c s c if o s s o ic r i o e a W a eli uba au de n f L o n i e r a c hi f e i i ophila na e a o n a c e a t ar o m x li H h um t th ti i s a L o n i e r m o m n s uc a s e L o i c r a m r si ret P ac ll s re n b ir o s a L n c e r a a po al m ic h y A ent aurea c u a a a l s L o n i a a lt o em rea p r l ic ia o n c e r l en o on s P h C u a a i c rv u e a Lo o n ic r a i c m rr a Eh N s t g r s g e a i e a p g um s y s a s e in y t ii L n i c e r a i u o t i op entt re s n a p s d t L o c a c l a w e al a a oi he a p p o r i a a L ni ic e e ra o s C n u e e e h r a o n ra r n l n a r e m s n e et L o n c e r p a i s t i n ii l b d t C d a p a f e ia L o i a z a r n a u um es ydr gia a c u e a r L n i ce e r im e p o i a ii Ce n y ur e o h p os o n ce a f r n s H e ta e a r act m n b lis a L o ice r t r r n a t e r r a s r e d p i a a L n i r a a a p i if a n t u r iu o n c ca c o i C h u a u r u r b as g al n s L on ic r a n gr l l c s p e e u a o tr i nt n a D on n i e r a p e y l a ta r a t e l a i i c e r a in yr e g x ia s C t a n s u e ph e la Ko i c e a a u a m p a n Cenu t ea i c g A p ic r r a n e p ea rofimr e c y u is s A i e r a a l v e u t nt e e e n sp ea a s be e c e a j p o i y re ta s c a r a s u a A lk e r a lp na l c is n C e C a ur o e e h n t a A b l r a m ig l e a u u n C aurre o r c n s A b w t r a r p ig u a u n C e a a a r r e n i M b e l a a u y e s ta e r aur p o a ix r s e ia t o c i m n e t e u ig r e a t Ce b e li it m a p r en n ca ima n C u ar nigr a y t u s l a z f ru n r a d n enttau a e a m s i a V o e l i x lo t i t a a e a i ent v t n e t c n r u li V i a i a a c il ica n t e C n c e m x V a r l a t a r l a t n C macn a r p i p o o o i aler n in ia r g p a ri o u v a e C n C e a tau a s p t im f e V a l m i a e u n l L e t p if r a b r c c l s a n e n n a a e s m c s e su a l r a e l a u e a h C Ce r a r a ar Pt o e r a a a o m k a r s C e e t e a n s u o um Sc l i n n n c p ta r u r u a a i t ystr g m s m e r a n l r c r i w i r C n e p ti q um Sc e ian o v a d ab h i s n u r a t i n h u e s S r ia n t g r d o ta t in s ul n S a ro e i h n ifo o t e o au a u re s in os e c a a l if a i t n Ce t n n s e a v r a e al s S a l na u g e t l i a b a a u u m u i l c d ata s Sc c ab b o n a e o l m n n t e a i n s S c b c o s i r l i n b e a a s m n u a io e s a p fo i i r r s r h t m q be a ith a t u Suc a i f a a a a i Ce e C s u o su r t l Su c a b i os i p f r a a u p n a l t si um u s on a fer Kn b o s p a a h i l n ea Ce C en o l a t e tho s u a a i y c u ia n a a e i h l u ri r Kn b i o s a h u a t C t e si r c um e C b o a p ll r i b a b u m r ol nu o a i c c i s a a i e n ur r C r c t i pes an e v s C au i o s c a a a e n a u e fl n n h us D e c i os a l na a a a a n a i Co s s t dus u a s s a o t u r r e t c r C um p e o ni i l a D e i gr o r l l e u m u al sa t a D i p u s a a t o s e i i C n s C r ct s d b a r D p p t a i s r si um u ac u m h a a C i h t i a r am l st fol i e r r on i rdu an a o e t a I i p s h i a c i u p c e u rd i s u al h l s p a p f c a p a A si d s a e r n a a i t o e sa a m u i a a a S m r s u u r t p t m i l a i E e a a s i r ar an n a na i C t C i r ac ep n s E s sa l nf h a i c s p e c E a l cu l a a at i r p re C u d a uu edi a a h n a P s u f a p r d ni b p n C r r s c o a He s o c r r l i e o u C o f ce r h p n li r s c m cu ec e en n ra a p e a C ra l s oc a rren ta Hy o c v u r i v u rd o i i o c a n s i a o s l f o a ium a a f at o a P l i s a e x e ol r rea C t ard C a Al i a co u i a l P y a a r e t c i a s ce p i d a d l a s sa a s s u a s n s n Pti dum cr s i c m c o s P P it m s l l g l l n e i r us i i si t s i it l lo o li p a e a a u C C aer t i a nu fi n a P to e l in i s i c e y t e h ic i r c n a s P it c o nia n l u s n or ti a h i t en a a i t m a m al m u si d v s s a P i t t o r i n l i C Ci C u cro ia e i t d u s P i t t s a a n i i c o i ca s s p ph l c t us osp os c o a v h ti Mu va n c P it t t s i i s b s s M a a a i na a p i is E i tosp osp p o he s a a a i u o M i i d d a tto t p b n r p mi tis a un i l t E i o bi s u n n ia s d n o e n de E r t o po s c l i s o ep s si u i s p i r s i E t o s r p a s t o Mu i i a A r y o sp r o p a t is s h ic o B r o p l a ubr a f s h O i s y sp rus s y n s r u i n i t n M t p c b r bia ca d i s S s r y s o r u o i d n u i oc i si ut ut i e r pa i i o i l F y n p o r x m l o a i u x s t T u g um m lc g r i a h u s h u e c T c ty n p o r u m r a o s no t i i d a e n gi o r u i Mu M M r m in r se lauca e r C h p g i r u bu a a d ch r l c n a d e le a A i a um o u m t o sa M T ta h ph a r d gi ru u m he ae hi c n r o aspero ollis T n ap le iu u m t e E a s g f p a c l H a u n r m m ss a a a i o t oi i l o n a m t Mu i o o yo t m P gu u m u xy c s c h i r s s r r m s C r l d u m r i t da s i m s in e s Cy e e m m t fl a ph Ec i d h s l u Ca r u s a m m un ob a i c r h ft e u yr ris i a t u is C eu i r g e e f p f ri ic s u W o r dy t x lo e s c o p r is t u a i m a i u t e c a o s u i s is b i s s Ne a h c i b v r i t p s e s fic o a s l r i i M o r a a c i c m i a l s p r g e ug i r o v l s o r ch p p f l l y n T i c u o a m a o o r c i var o nt ae s chu r p t i o ima s d a C a na c li r a du a i S l y o lo l C d a a r a u a e c T l s e t f e u r h c g m u n a p ss o e s m u e l u m g a m u l as l n Mo a o h a n e ia r o p t n s Ca M a s h n e a m u r d s re a n nt if e m a o i a a n u e r h m A o b ri m Ca a s a da m s s r t i y c s g o s e m o u Ca c o le ri t et l pu s c r a d fi u m a A m n d u r m m g t i ni a t h y c s c u C m e i t i a C i sc r t a i p u nops o o rd C m r llis c u ta c m e s f i Le ri A S u l i a C h c o a ru m v g r f a o l e H u d m o u e s a n l i a m n c l o t a S Apose r a u m i a C z n o a h e i m l x i tu u m p o a t n li a l i C a m h p o a r i u i u oide u um a hi e k s o l a A p e r a t f l i d c i p n stu f o a o m h b p a ci l i d h u i s t P c u p n lis y s ii o i m r p yp c o s ia c i f o P a m au a d e m n i m a i l o o ta s a p a l s n u c n m a l a r f f Ph s m r pa i i e si a v a s t p n c a t r or tia i o c m C m t f l T s h i a f a i e c C e mp p n u a o n u i o r i m Ec i H a ia t l pi if l u C h mp i a n p e a i s x m u o o e i u a r yn p n r n c t e u s e o sp b w e vi s ii C S s i c L r h oc a e e t Ed a t p a x u m n a s lu s i e o g n a y n u g h n li s a u g ia n s k u r r o L a r n a a o a n m h i m h s e i s p i e u k L a y an a h o D e c j i L y o a nul i la t a c s u r b n id p c la L a m t ul a i vi o m R i o n o t o n pl i e l m i L o m e la u a l a u u c v ia s u c o t an u m a r c in i t e ra s m m e an e e p p a i s u r t s s s Lo o m e m n c t m o o m s L o ra vi c i n m n p o n o s m o r ola r r e u o b u d r r i on H a n ri r l la a C b p u u la a e r n y T ci s s sp o u i s b p a vu u r a a n mi u C u u e a f i d r C i l e l i s C o b p p a r a o i o n n o u h e s s e ma u h n l C Cl b e a m u d e d v d ct m f a C e p a m l a a n s l e s e i C y e ia an u r e H r at e i t a C b m l a v a u y e r t a p o y b e a a u d ra g n h ns n c h c t a n vi s e l h r l a a t a r i o t lis C ya a l a nu m s m o t m m p s me l nu f i s C l l ia a l a c er p r f t e V a a u ca d te i a C l el i r ri n l f r iu e i d o i r n Lob l e e a el l n n a u a l r s o e a i A m i a i e e n p n s Lob l e l i a y l b u i iu i Li h Lob e i n a l ach i r i l o u ff ea e r H ne a u i a u ora s t Hi r n u u a e n L l e i a a a t i n V e s n s e a ata L l r n a l p a t r i i i g m h o r a P er rm a t u i a n n d a e m a P l r n i c t i l i v Bi p p nsi ra a L e r u l s a s r T iu o i id l u ia r a d b r i L e i e h p uc n f m r a r a inia o r m a s l a h l tif e a o H r g p g i a i m a c h a n V t n l n u i uli l I o e h n la a o a o i r a u p l B m e a li i an e u vi i B r p r m y p e s a ra a olia o so obel r a l c on o o h r c o a i B obel r r r u e yrso c u n e a B B rg l na B b m o a u p d s h f des S S a b a n g a a A T s e p o a l o um S at e m a y d ne o li lis n t o tor k u v o i S p e m ont o a h u i e i c h i i S u p g c S e o v i as u e i ia s f s S u l n r r o p t T m a a Si o s m u L r ive r if u e l c a eo s L o m i r ul e p k u if i i a s C u t e a p r n St g u l c gi c C i l e u r a li a a s e s C C i n y c n s l i r a o s n o us ta a C i o l o al b o r y r see ic cu ylla l i C i rm t i l i n e l L d th i p ph rm i o u a o i i l a C C i phoc i n a s i C C e u C o h o r d C y i p r l i a o ss zi u s q r e p o a a l n o i a o M s C r g u n h va e s Cs p a s n mn p s i p r l eif m C c p a u s C C p c C p i i n o e Da s x m a m s N e p b a r i f i si s i i n a m N e ti

Barnadesia polyacantha Barnadesia M o odorata Barnadesia parviflora Barnadesia p M m S ci r m i eni re C e e n p t a l n l e h a n a s t de i s m ti i t i e i l c m s s V m c p olium i s a n i o s i M y ns ocea ns s h i l ali r a a s t l t r s n i e l e e h m s c m o u e i r e a c o i s e u a p a i e h r d h u u e a u E a u s u f c s o u i a h a i d ox va e pinos s a r a e i a u a a n h e u m n e l i a i e n a mo ia t e d ph u r e spec g me a be a e e l p e n n oc e t a y de n a ur l n o ca a a l al n i i r i c n e C l y u u u a f l u s ect h si a t h t lt e i u t o o i e l a e s r o e ei h n i e n n o g oi k i p s n ol s v n p ia n n sp a l n n o e ko a o n l n ei m i i t s u e e e e s d cu o t o n a t le t E n u t ia e l E i e t o u m a per l v e n n u o n t a d e i n u ci r b m g n n h a a a n t t i i i a a c a m mi p s m t i n e t a Eu ox ck i n n t i t x r t u a h hel a u r c m k n ia s s l o r e r st e o o i e n n t t c d ch e i g l y t t r r x p f d c a o o l o s m L n h pi r o i e t t r c f l s o p e ta n e vi is a r c e p ar l c a a a l m t t c s s l e d v s as m t o a s e me a a t r r a r o t s t ste a i s g t r r o a m n o hi f n e r r o o l r a i o n s l a i o a a a p t g sc q o s d q a cr r l r a n p r l p u u g a h a b i d u y c y s c r h p t s a r r r a i h n e r a i b o l o m hi fl c d v s o di m p r e p o o a p a o a i c e ali o rn o a t n a t e a egans b e l n e t h a r m a s r f p n f C r s a o m w l le n lp i o e t v o p m o e o s t o o e m h i ula o p p G be t e u lo e p m e a k a a o a u a p e p b i i o g m t e l acr r xi o a C u l p h a c o u e m a in a e o u p p h t t h a u p p m e di s p r f la n e p m u g a us u o ra na pht m n v e a m m l o i a o n o e a vi o p ra l n n i a u p y r m p o i nt e H a w p l n p d n n s p o o o s d i ula p o r ai r r n g i n o f p i i f p l l i e v or l t l na en v r r b h e c o a p i o q p p n l i b I r v o o i o o o r Z I a l i c o ll g r o py s o t i o i i a s a r a u d n a i p t m l a t in y st o g a s al a nnat q o p a e e T mo o o g l or a o i e r o g p l a u a o g a a H n As y c g p i sic if e a a t c H ul m e t g y t e a i ci tu s y g i y ym s ia go t h i a i i n o i r o g g i i g g a c c m h g cu I a g n e l h e f r b h c a h y a l d a a n h z o s g g s y e e m e g m d sp a r g o y n es o j a g g l iu c g o o l y lu o y mi e i o l u n b g a o u a lus i n a a pi go u c R ia s s e h c p ri or i p l r a th o o l T um o w o o oco um a o l u H e i go i o g s c I e l i e p l e n i a o r e i ybia conspi m t o n u s n A a o l e e a th a o n l o o u e r o n n li o o m l n n n u r a s i Pall i a f n od lo i a e r u G da a r iu ci u if s acea o c u p s i n n s A ty o ia h i n n s l rb p n n i i

f s Ec i m s su d c i n a s e e s a E et del n n s s n i n n m s n a n n s f a o n d ph g a l e c e s o n i n a s d d i e s s m s c c g l ur ch o c yb e t o l e e da l s e a yr i a l y de e j h s e i in o b c c c i i n i sp l a o a i l a e f gig a l c s a o l u t s ol e p v lia s a lian e r p u i o n e n i s a i i S h f s i e l m u o g a o r i s l g en m m m p c ma V E ysu r p ro pina ns u l l e h i o o o c e r H ll P r me e L r u i r a p p r a r l da o u n i Kn s e e u t i e i i p b e cki p o e y er S o b ss W h n o c n r r l H ge S a h a a l e c i l f e ch i g n o e c i e e li m a n tu d t a a a l l e m s e a g e c i c e o c e i l d l o G So n i a an e g o hr e mo W l y a E l e e a e e e H n S u m r S h t c c t t c he i k u c t n a E yot e e e i b i n c c n a a n e e L d e l a c e s o a n r c c n s S e u e n d r d n c a u Ac i a s l i e e A i a e n n o ex phthal Ka c h a r I l u a t So S t r t i I n u c e n u s c n t n cm db i d a a u t e g V z u s I I te a t a i a h Er i n I A r n e a I K d i i r u a o p Z a r t I e e S f l u n l e t t u e e s s i

Calendula arvensis f V u i a i A n i s a s a o i u i i e S u t o n o L Barnadesia arborea Barnadesia spinosa e H h n l a k Calendula officinalis u n u B a s c e i H S K i n a S l R p s a s s l u s r lin y i a L S c e m u s ymph L P i s s u o u e u e

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r s P l e n s o

i h

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Sa s AQUIFOLIALES ASTERALES * + DIPSACALES

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).

(Goldblatt & Manning, 1999; Petanidou, 2005) or probably requires a different explanation. Nectarivorous different optimal NSP values in different plant clades birds are known to prefer sucrose-rich nectars with a (explored further below). The variability for plants pol- high overall sugar concentration, but experiments have linated by specialized Old World nectarivorous birds shown that they prefer nectar composed of hexoses if

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the overall sugar concentration of the nectar is low it does not represent adaptation to peaks in the (5%; Brown et al., 2010). This is because the birds are adaptive landscape in the strict sense but rather an sensitive to small changes in osmolarity of the nectar adaptive trend of increasing divergence from the ances- and hexose solutions have a higher osmolarity than tral state (Hansen, 1997, 2012; T.F. Hansen, pers. sucrose solutions (Nicolson & Fleming, 2003). Our find- comm.). Such an interpretation has been invoked for ing, that about a third of the species pollinated by Old body size evolution in relation to dietary niches in ceta- World nectarivorous birds produce nectar with low ceans and habitat in monitor lizards (Slater et al., 2010; overall sugar concentration (< 20%) that is extremely Collar et al., 2011). For nectar evolution, this would sucrose poor (NSP < 0.20; Fig. S3), corroborates the suggest slow movement towards low NSP in generalist- results of Brown et al. (2010) and suggests that this pollinated plants and high NSP in specialist-pollinated phenomenon may be more widespread in nature than plants. However, the optima inferred from these models previously thought. It is possible that this represents an tend to lie outside currently occupied ranges, perhaps alternative, energy-saving pollination strategy, which is themselves therefore representing unreachable adaptive deceptive to the pollinators because of the compara- peaks. The optima inferred for NSP approach the limits tively energy-poor nectar they are rewarded with. Simi- of the occupied range but are not unrealistic (Table 3). lar deception strategies probably occur in many plant Another possible interpretation, therefore, is that NSP is species belonging to several genera both within and evolving as an adaptation to other, unmeasured vari- outside the asterids (e.g. van Wyk et al., 1993; Nicolson ables (Labra et al., 2009; Hansen, 2012), for example & van Wyk, 1998; this study). Further studies are corolla shape and size (Nicolson, 2002; Witt et al., needed to test this hypothesis. 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 Nectar sucrose proportion as an adaptation to the allometric constraints of floral shape and size, pollinator group which in turn could be correlated with PG. Such an We tested the hypothesis that NSP is an adaptation to explanation has been invoked for body shape evolution PG (e.g. Heynemann, 1983; Martınez del Rio et al., in three-spined stickleback (Voje et al., 2013). Without 1992; Baker et al., 1998). At first glance, our results formally incorporating these variables into the hypothe- suggest that this hypothesis cannot be rejected: we sis-testing framework, these alternatives cannot be dis- found strong statistical support for convergence on dif- tinguished but results from the simpler OU models ferent NSP optima among different PGs and for corre- (OU2, OU2A and OU2V; Table S2) do offer some addi- lated evolution between NSP and PG. But to what tional insight: these models suggest a much stronger extent do the details of our findings constitute evidence adaptive process, at the coarse level of generalist PGs for NSP being an adaptation to PG? versus specialist PGs. This supports the interpretation of The best model for NSP evolution overall is where adaptation rather than that of drift. However, because NSP is allowed to evolve towards different optima for the simpler models are a much worse fit to the data, each of the nine PGs studied here (Table 1). Inspection they do not capture the entire story. The more complex of the inferred optima reveals that they in fact converge model is a far superior fit to the data but one that nev- on only two independent optimal values, one for plants ertheless explains less of the residual variance. pollinated by generalists and one for plants pollinated Together, these results suggest that PG is an important by specialists (Fig. 2). Lack of differences among plants component of NSP evolution, but it does not act pollinated by most obligate nectar feeders implies that directly as hypothesized here – other factors are needed the NSP requirements of the individual specialist PGs, to fully explain how NSP evolves. although being generally high, are indistinguishable. This could be one reason why previous studies (van Is nectar sucrose proportion the trait or the Wyk, 1993; Galetto et al., 1998; Nicolson & van Wyk, environment? 1998; Galetto & Bernadello, 2003) have failed to detect significant differences in NSP among (specialist) PGs. The dependency in the NSP and PG data coded as binary Further inspection of the best-fitting model reveals a variables suggests that a flower is more likely to be polli- weak adaptive process (Table 3). The phylogenetic half- nated by a specialist pollinator, irrespective of its NSP life is unrealistically long, suggesting that species are far (Table S4). In contrast, a specialized nectar feeder is from their optimum and unlikely ever to reach it (Han- more likely to pollinate a high-NSP flower and a general- sen, 1997; T.F. Hansen, pers. comm.). The stochastic ist feeder is more likely to pollinate a low-NSP flower. variance is also very high, suggesting that any adaptive This asymmetry is explained by the finding that NSP is evolution towards the NSP optima is overwhelmed by the first to shift from the ancestral state of high NSP/spe- stochastic movement and that a large amount of the cialist PG (q13 > q12; Table 2); that is, changes in NSP residual variance of the model is not explained by the may occur without a simultaneous or preceding change two optima. One interpretation of such a model is that in PG. Once variation in NSP has been established, shifts

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from a specialist to generalist PG are more likely in lin- clades could be governed by floral shape and size, rather eages with low-NSP nectar and further shifts from high than the main PGs of each clade. These results further to low NSP are more likely in generalist-pollinated lin- support both conclusions above that PG alone cannot eages. Thus, the evolution of NSP and PG is correlated in explain how interspecific differences in NSP evolve and a way that means that certain shifts are more likely than that the relationship between NSP and PG is perhaps not others, but not in a way that requires simultaneous governed by adaptations of the plant but by pollinator change, as would be expected under strict coevolution behaviour and dietary requirements. (Janzen, 1980). The finding that NSP changes first sug- Finally, these findings hold true not only for NSP but gests that the nature of the correlation is primarily dic- for NFP and NGP as well (Tables S6 and S7, Fig. S5). tated by pollinator behaviour rather than vice versa. In This contrasts with findings for asterids as a whole, other words, it suggests that pollinating animals ‘capital- where an adaptive model was rejected for these two ize’ on the NSP presented by the plant and that the sugars (Table 1), and suggests either that pollinators are plants do not necessarily adapt their NSP to the local pol- sensitive to the proportion of the two hexoses in nectar linator guild (cf. ‘diffuse coevolution’ of Janzen (1980)). (contra Baker et al., 1998) or, because our analyses were This contrasts with the view that a plant must adapt its based on proportions, that the signal in NSP cannot be nectar composition to ensure regular visitation by effi- independent of that in NFP and/or NGP, even if differ- cient pollinators (Nicolson et al., 2007). A conceptual ent processes govern the relative proportions of each consequence of this is that NSP should perhaps be trea- sugar. Future (experimental) work may shed further ted as the environment and PG the trait – in order to be light on these alternatives. fully understood, the floral rewards–pollinator interac- tion might better be viewed from the opposite perspec- Adaptation and conservatism in nectar evolution tive to that often presented in the literature (and this and beyond study; Nicolson et al., 2007 and references therein). Much of the historical debate surrounding the evolu- tion of nectar sugar composition has centred on the Different processes in different clades and for dichotomy between adaptation to pollinator dietary different sugars? requirements and there being a ‘phylogenetic con- Analysis of less inclusive clades revealed several impor- straint’, limiting the amount of variation that can accu- tant insights. Evidence for adaptation was much stronger mulate within and among clades (Baker & Baker, 1975; for individual clades than for asterids as a whole: an Nicolson et al., 2007). Indeed, results such as those adaptive model could not be rejected for 12 of 13 clades above, of different processes operating in different (Table S6) and a much more rapid and precise adaptive clades and of clade-specific NSP optima that are inde- process was inferred from these models than from the pendent of pollinator diversity, are likely to underlie model for asterids overall (Table 3). This supports the some earlier claims of phylogenetic conservatism idea that, at the broadest scale, several factors are needed (Galetto & Bernadello, 2003; Thornburg, 2007; to explain nectar evolution, only one of which is adapta- Rodrıguez-Riano~ et al., 2014). However, although we tion to the broadly defined PGs analysed here. Certain found that adaptation to pollinators is not a sufficient clades, however, revealed strong evidence for adaptation explanation on its own, phylogeny is merely a depiction to PG in some clades and none at all in other clades. of patterns and cannot in itself constrain or explain Multiple-optima models tended to corroborate the find- anything (e.g. Losos, 2011). Many empirical studies ing of independent optima for generalist and specialist have invoked both adaptation and conservatism in PGs (Fig. S5) but also found differences among specialist cases such as ours, where there is some evidence for PGs. One interesting example is the low-NSP optimum adaptation, but where the specific hypothesis being inferred for specialized nectarivorous birds, providing tested leaves some observed variance unexplained further support for the hypothesis of deception elabo- (Ackerly, 2004; Cattin et al., 2004; Escudero et al., rated upon above. In contrast, single-optimum models 2012; Hansen, 2014). However, in these studies, phylo- revealed different optima in different clades, irrespective genetic conservatism is not invoked as an alternative to of the main PGs. A high optimum was inferred for the adaptation but to describe a strong historical signal not heather family (Ericaceae) and a low optimum for the directly related to the hypothesis being tested. In other daisy family (Asteraceae). Ericaceae are pollinated words, conservatism is invoked in lieu of the full mech- entirely by specialist PGs (bees and wasps, specialized anistic explanation, just as appears to be the case in the OW birds and hummingbirds sampled here), whereas nectar literature. Asteraceae are pollinated by both specialist and general- Given the long-standing clarity, far beyond the nectar ist PGs (generalist insects, bees and wasps, butterflies literature, of the inadequacy of the adaptation/conser- and hummingbirds; Table S8). Ericaceae tend to have vatism dichotomy (e.g. Leroi et al., 1994; Blomberg & tubular flowers and Asteraceae small, open flowers, sug- Garland, 2002; Ackerly, 2004; Losos, 2011), why does gesting that the different optima inferred for these two it persist? We suggest that there are several reasons.

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€ 1 As a result of (naıve) interpretation of phylogenetic Conclusion patterns of trait similarity and divergence, often mea- sured as phylogenetic signal (Losos, 2008; Cooper We present evidence that NSP is an adaptation to PG in et al., 2010; Crisp & Cook, 2012), as process. How- asterids but, importantly, that this is not the whole ever, although it has long been clear that patterns story. Future studies may increase mechanistic under- cannot simply be read from phylogenies and inter- standing of how plant–pollinator interactions via floral preted as processes (e.g. Blomberg & Garland, 2002), rewards evolve by focusing on dense sampling of nar- the extent to which phylogenetic signal is discon- rower clades, finer divisions of PGs and incorporating nected from any underlying process has only become additional factors into the hypothesis-testing frame- clear relatively recently (e.g. Revell et al., 2008; Bou- work, along with consideration of how the floral nec- cher et al., 2014; Munkem€ uller€ et al., 2015). There- tar–pollinator interaction arises, without the need to fore, the practice of inferring process from invoke phylogenetic constraints or conservatism. phylogenetic patterns remains. 2 Because of the cladistic tradition of recognizing only autapomorphies as adaptations (Hansen, 2014). This Acknowledgments means that a retained ancestral state (plesiomorphy) The botanical gardens of Berlin, Bonn, Freiburg, Gottin-€ cannot be interpreted as an adaptation. The counter- gen, Halle, Heidelberg, Jena, Munich, Munster,€ argument is that retained plesiomorphies must be Osnabruck,€ Potsdam, Basel, Bern, St. Gallen, Zurich, adaptations for something or they would have suc- Leiden, Kew, Graz, Cochabamba, Santa Cruz, Singa- cumbed to selection pressures to change (Losos, pore, Bogor and Cibodas and the ‘Sukkulentensamm- 2011; Hansen, 2014). Thus, retention of the ancestral lung’ Zurich provided permission to collect nectar. We state is a pattern that says nothing of its generating are grateful to B. Steudel, J. Kluge, E.A. Tripp, H. Mar- or maintaining evolutionary process. tinez Piedra, H. Hentrich and J.-M. Tompkins for help 3 Because of the terminology used in the OU frame- during data collection, M. Weist and A. Schmidt- work of adaptive models (‘adaptation–inertia mod- Lebuhn for help during nectar collection, P. Endress, J. els’; e.g. Pienaar et al., 2013). This use may certainly de Vos, R. Carter, G. Thomas and P. Kevan for helpful be perceived as conceptually confusing but inference suggestions and advice, B. Keller, S.W. Peters and A. of ‘inertia’ over ‘adaptation’ does not necessarily Egert for help during laboratory work, E. Benetti and mean that the trait in question is not an adaptation B. Seitz Ludi€ for help during literature collection, at all, only that the specific hypothesis under study is Palacky University for space and D. Ackerly, L. Bun- rejected (Hansen, 2014). The trait may still be an nefeld and several anonymous reviewers for comment- adaptation to an environment that itself is evolving ing on earlier drafts. SA was funded by the Konrad- in a drift-like manner or to another, unmeasured Adenauer Stiftung, the Swiss Nationalfond and the Stif- variable that shows strong similarity among closely tung zur Forderung€ der Pflanzenkenntnis. DH was related species (Labra et al., 2009; Hansen, 2012). funded by the European Social Fund and the State Thus, although model inferences may be described as Budget of the Czech Republic (project no. CZ.1.07/ either ‘adaptation’ or ‘inertia’, interpretation is not 2.3.00/30.0041). AMH was funded by a Swiss NF Fel- necessarily dichotomous. lowship for Prospective Researchers (grant PBZHP3- 4 Due to the development of the conceptual frame- 133420) and by Carl Tryggers Stiftelse (CTS 12:409). 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 References (Baum & Larson, 1991; Leroi et al., 1994; Hansen, Abrahamczyk, S., Kessler, M., Hanley, D., Karger, D.N., 1997), another, dedicated to detecting (niche) conser- Muller,€ M.P.J., Knauer, A.C. et al. 2016. Data from: Pollina- vatism (Harvey & Pagel, 1991; Wiens & Graham, tor adaptation and the evolution of floral nectar sugar com- 2005; Crisp & Cook, 2012), was born. Increasingly, position. Dryad Digital Repository. doi:10.5061/dryad.1r45h. these fields make use of the same models (cf. e.g. Ackerly, D.D. 2003. Community assembly, niche conservatism, Kozak & Wiens, 2010; Munkem€ uller€ et al., 2015), but and adaptive evolution in changing environments. Int. J. – because they are developing in parallel (one is con- Plant Sci. 164: 165 184. Ackerly, D.D. 2004. Adaptation, niche conservatism, and con- cerned with adaptation [Hansen, 1997; Butler & King, vergence: comparative studies of leaf evolution in the Cali- 2004; Beaulieu et al., 2012; ], the other with a ‘failure fornia chaparral. Am. Nat. 163: 654–671. to adapt’ [Wiens et al., 2010; Kozak & Wiens, 2010; ]), Ackerly, D. 2009. Conservatism and diversification of plant reconciliation of how adaptation and conservatism functional traits: evolutionary rates versus phylogenetic sig- can be interpreted together has received much less nal. Proc. Natl Acad. Sci. 106(Suppl. 2): 19699–19706. attention than each phenomenon has separately (but Amadon, D. 1950. The Hawaiian honeycreepers (Aves, see Ackerly, 2003, 2004; Labra et al., 2009). Drepaniidae). Bull. Am. Mus. Nat. Hist. 95: 157–262.

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