How does one ‘test’ the pollination syndromes? This is not obvious, which is probably one reason for the paucity of tests! As we see it, there are three steps. First, one must define what one means by the syndromes. Secondly, one must make the syndromes operational in order to test them quantitatively. Finally, one must decide what properties or predictions of the syndromes are the most important ones to scrutinize.
Numerous definitions seem possible, and, indeed, the syndromes have long had a quality of being something each worker understands but none exactly agrees upon. For example, a recent review (Fenster et al., 2004
) first defines syndromes (their p. 376) as evolutionarily convergent suites of floral traits ‘associated with the attraction and utilization’ of specific ‘functional groups’ (p. 377ff.) of pollinators. Later (p. 388), a close reading suggests that the ‘convergence’ and ‘trait suite’ components of the definition can be relaxed to include any association of floral traits with functional pollinator groups within a specific lineage, whether or not the association adheres to a specific set of floral traits. Finally, these authors speak of adherence to ‘traditional syndromes’ (p. 395). We have attempted to test only the last of these three definitions, but this raises the question of what the ‘traditional syndromes’ are. Hence the next task is to choose a source of syndrome descriptions. We chose Faegri and van der Pijl (1979)
, with occasional additional guidance from Proctor et al. (1996)
. These sources distinguish syndromes that will not accord with the intuition of all workers [as examples, the bee syndrome is not divided further into syndromes for small vs. large bees, as was done by Vogel (1954)
and others; and some workers, such as Hess (1983)
, omit all aspects of flower shape from syndromes]. Furthermore, they give little or no guidance as to how different floral traits ought to be weighted, so that the default is equal weighting, as we have used. Finally, they imply that one set of syndromes will apply across geographic regions and plant taxa (below alternatives to such a ‘universalist’ approach are discussed below). On the other hand, these two books are frequently cited in discussions of pollination syndromes, and provide a starting point for a test.
How do we next prepare the verbal descriptions of syndromes, derived from our source books, for analysis? Whereas it is straightforward to classify a given flower as white or yellow, some other trait descriptions are more difficult to interpret (e.g. ‘vivid’ colour, ‘stiff’ anthers), and it took considerable discussion and re-reading of the source texts in order to reach consensus. Acknowledging these difficulties, we now must subject verbal descriptions to quantitative scrutiny. This would be impossible without modern methods of multivariate analysis, which allow the conversion of words into trait vectors. The method used here is NMDS, which is recommended for ordination of binary (+/–) ecological data (Minchin, 1987
; McCune and Grace, 2002
). In contrast to NMDS, which makes no assumptions about the distribution of the variables, other techniques assume that variables are unimodally distributed [e.g. correspondence analysis (CA) and DCA], or assume linear relationships among variables (e.g. PCA and DFA), thus rendering them inappropriate for data such as ours (McCune and Grace, 2002
Finally, what properties or predictions of the syndromes should we examine? We have examined their ability to describe actual trait combinations in flowers and to predict major pollinators. Is the latter reasonable? As explained in the Introduction, the pollination syndromes are an evolutionary concept (leaving aside that several strong proponents couched them in essentialist and teleological, rather than strictly Darwinian, terms; see Pancaldi, 1984
; Vogel, 1954
). The syndromes describe presumed adaptations to ‘attract and utilize’ pollinators, i.e. results of past (and potentially ongoing) natural selection on the floral phenotype (e.g. Faegri and van der Pijl, 1979
). Therefore, we might expect to see the same types of pollinators at present as those that have formed the pollination (=selection) environment of the past. This argument supports successful prediction of pollinators as one criterion for evaluating the utility of syndromes. It is reasonable to argue, of course, that pollination environments observable at the present time will not always indicate past environments (Ollerton, 1996
; Lamborn and Ollerton, 2000
; Rivera-Marchand and Ackerman, 2006
). We certainly agree that plant–pollinator interactions can be dramatically altered by such things as anthropogenic disruption (e.g. Kearns et al., 1998
). On the other hand, we are unaware of any evidence for recent modifications of pollination environments sufficiently widespread to render prediction of pollinators an inappropriate test of syndromes. Furthermore, arguing that current pollination does not reflect past pollination may lead to the conclusion that any observation is consistent with interpreting a given floral phenotype as ‘the ghost of pollination past’ – in other words, it is in danger of explaining everything, and therefore nothing.
How did the syndromes fare by our test? We found that each idealized syndrome forms a cluster of points in floral phenotype space, and that these clusters segregate reasonably well in the multivariate space. However, the regions of phenotype space that the syndromes define are largely unoccupied by real plant species. In other words, the combinations of floral traits of real plant species rarely conform exactly to the traditional pollination syndromes (we know, for example, that there are bird-pollinated flowers with blue, zygomorphic corollas, and beetle-pollinated flowers that are small, yellow and unscented, even though the traditional syndromes do not include such combinations). Furthermore, the primary pollinator was successfully predicted by the nearest syndrome for only about one-third of the plant species for which data on pollinator visitation frequencies as well as floral phenotype were obtained. What should we conclude? Most readers might agree that traditional syndromes (as defined above) fail to describe actual floral trait combinations accurately, but success in predicting major pollinators for one-third of all plant species is open to more individual interpretation. There is no disagreement that some fraction of angiosperms produces generalized flowers not strongly adapted to any particular type of pollinator (e.g. Delpino, 1874
, p. 364; Proctor et al., 1996
, p. 173ff.). If one assumes that this fraction is small, then successful prediction in one-third of all cases is not very impressive, whereas if one assumes (say) that half of all plant species have generalized flowers, then successful prediction in one-third of all species might evoke the opposite reaction. However, in either case, prediction of pollinators from the traditional syndromes alone, as various recent workers have done (e.g. Grant, 1994
; Bernardello et al., 1999
; Harrison et al., 1999
; Hansman, 2001
; Perret et al., 2001
; Carpenter et al., 2003
), seems a risky business.
We stress that we do not take our results as evidence against convergent floral adaptation resulting from pollinator-mediated natural selection. In fact, we adhere strongly to the view that many floral traits reflect adaptive responses to selection by pollinators, and that the direction of selection is a function of properties of pollinator morphology and behaviour (e.g. Waser, 1983). However, we propose that thinking solely in terms of selection by a single ‘most effective pollinator’ (the most common functional group of visitor, or the one most effective in transferring pollen during a single visit, which are sometimes taken to be the same thing; Stebbins, 1970
) fails to capture the range of logical possibilities. Floral adaptation might also be influenced by antagonistic floral visitors (e.g. Strauss and Armbruster, 1997
; Strauss and Irwin, 2004
), by mixtures of pollinators of different functional types (e.g. Hurlbert et al., 1996
; Waser, 1998
) and, indeed, by pleiotropic effects on other plant traits (e.g. Rausher and Fry, 1993
; Levin and Brack, 1995
; Simms and Bucher, 1996
). Observed floral phenotypes might even represent adaptations to ‘minor’ pollinators (Aigner, 2001
), which certainly would contribute to mismatch between observed ‘major’ pollinators and putative syndromes! We argue for this broader set of perspectives as working hypotheses to explore empirically.
In the end, readers will draw their own conclusions about our test and its results, and it is sincerely hoped that some will devise and implement additional tests. Nonetheless, we would like to end by offering our own personal views on possible directions for future work on these questions. Of course we advocate a continued discussion of the classical syndromes, but our hope is that these will eventually be replaced with a conceptual view of plant–pollinator interactions that is less classificatory in its aims and that relates directly to both pollinators and antagonists, and their ability to influence the evolution of the floral phenotype, with reference to the phylogenetic constraints or other influences that may also be important. We can think of three general ways to proceed toward this goal. First, we might adopt a ‘bottom-up’ mechanistic perspective, putting aside the traditional syndromes, starting fresh from simple assumptions about which traits matter most in determining which pollinators visit which flowers, which traits are the result of selection by antagonists and which are a result of the phylogenetic identity of the plant species in question. Such a ‘minimalist’ approach of identifying only those traits that are important may take us far toward explaining observed patterns of plant–pollinator interactions, and the (majority of) exceptions which do not seem to fit into the classical scheme. Several recent studies exemplify such a strategy. Stang et al. (2006)
could predict most observed plant–pollinator links in a Spanish community in relation to accessibility of floral reward. Furthermore, such an approach successfully explained observed features of plant–pollinator interaction webs within single communities (Stang et al., 2007
) and across multiple communities (Santamaría and Rodríguez-Gironés, 2007
). Secondly, we could take a ‘top-down’ pattern-analytic approach, using multivariate analysis to explore associations between floral traits and pollinator communities. We recognize the grave difficulties here of knowing which traits are relevant to pollinator attraction and use, and of measuring them in ways that reflect pollinator cognition (which varies even within taxa), rather than human cognition (the basis for traditional syndromes). Thirdly, we could use the approach of authors such as Armbruster (1993)
and Castellanos et al. (2006)
, among many others, to map floral traits, pollinators and antagonists on to well resolved phylogenies in order to understand the association between particular flower phenotypes and the pollinating vector – a ‘pollination systems’ approach that requires a combination of rigorous field work and molecular laboratory skills. Currently some workers are using syndromes in this context, but in a more informed way than previously, with some supporting field evidence (e.g. Whittall and Hodges, 2007
); however, the role of antagonists vs. pollinators has barely been explored in this regard (though see Armbruster, 1997
It is not a foregone conclusion that any of these strategies (or others that future workers may devise) will uncover a universal or near-universal set of syndromes. Any syndromes that emerge may turn out to be idiosyncratic to geographic region or plant taxon (see also Ollerton et al., 2003
; Fenster et al., 2004
; Goldblatt and Manning, 2006
). Region-specific traits are suggested by the difficulty of applying traditional syndromes developed in the Northern Hemisphere to the Gondwanan flora (Newstrom and Robertson, 2005
), and by the poor predictive value of, for example, the butterfly syndrome in Tasmania (Hingston and McQuillan, 2000
), in contrast to the Guyana community surveyed in this study. Taxon-specific traits are suggested by our results, with apparent differences across plant families in the predictive ability of traditional syndromes: Fabaceae, Apocynaceae and (surprisingly) Asteraceae fare better than other families. Indeed, some taxon-specific traits not included in the traditional syndromes have been emphasized in recent literature, for example the green vs. red floral bracts and differing schedules of pollen presentation correlated with bee vs. hummingbird pollination in Costus
, respectively (Thomson et al., 2000
; Kay and Schemske, 2003
; Castellanos et al., 2006
), and the details of scent chemistry identified by Andersson et al. (2002)
and Raguso et al. (2003)
. We view such idiosyncrasy, if it is confirmed, as no less interesting in suggesting mechanisms of floral evolution and patterns of floral ecology than universally recognizable end-points such as those proposed by the traditional syndromes.
The possibilities outlined above, and others we have not thought of, will provide exciting grist for the mill of future research, and should help in devising more profitable ways for reducing the dimensionality of floral variation and understanding the evolution of floral phenotypes. The traditional pollination syndromes have contributed a great deal to the development of pollination biology as a field, but our test across diverse communities suggests that the way forward lies in looking beyond them.