Discussion
Here, using a data collation and meta-analytical approach, we demonstrate that network type is the most important driver of ant-plant network interaction specificity. Unstandardised H2’ specialisation results recapitulate previous studies, showing reduced specialisation with elevation for myrmecophytes, higher specialisation of myrmecophytes than other network types at lower elevation, and decreased specificity in response to disturbance. However, all effects were lost when H2’ was standardised by comparison with null network models. This may have been due to confounding effects of matrix size and connectance on uncorrected H2’. Both ants and plants were significantly more phylogenetically specialised in myrmecophytic networks than in other network types, although there was no significant effects of elevation, latitude, or disturbance. This is the most comprehensive analysis of global scale ant-plant network structure to date, and the first to employ null models to standardise network metrics and to explore phylogenetic specialisation.
More physically intimate network that involve greater commitment to exchange of goods and services (in the case of mutualisms), are predicted to evolve to become more specific (González-Teuber & Heil, 2015). We found this expected effect when assessing specificity independent of phylogeny and uncorrected by null modelling (H2’), with myrmecophytic networks at lower elevations showing higher specificity than for other network types. Unexpectedly, this effect was not present when H2’ standardised effect sizes were used as the response variable. This indicates that the results for unstandardised H2’ may have been driven by other aspects of network structure, and not by specificity per se . post-hoc analyses show that both total network species richness, and weighted connectance are strongly negatively correlated with H2’ (see supplementary, appendix 8), but are only weakly related to H2’ z-scores (appendix 8). This might be because networks with higher connectance are those in which links are found evenly across species in the network, and hence have lower specificity. However, the differences in results when standardising H2’ suggest that, at least in terms of network specificity, this evenness of links is to be expected on the basis of network structure alone. Hence it is vital to compare observed network metrics to distributions expected under random network assembly to avoid biases due to confounding aspects of network structure. This approach has not always been implemented in previous studies.
However, in terms of network phylogenetic specialisation, using the dsi* metric, which is already standardised against null models, we found that myrmecophytic networks were more specialised than other network types. This was the case both in terms of ant specialisation on plants and plant specialisation on ants. Each ant species interacted with a more phylogenetically clustered group of plant species than would be expected at random, and vice versa. This potentially indicates long-term coevolution between myrmecophytic plants and their ant partners, characterised by exchange of multiple goods and services. Plants can provide specialised morphological structures (e.g., domatia) that promote partner choice and thus allow direction of benefits to more beneficial mutualistic partners (Heil & McKey 2003). Myrmecophytic plants also sometimes provide FB and EFN for their ant partners. Ants can provide herbivore protection, competitor trimming, nutrients (Mayer at al., 2013), and CO2 for photosynthesis (Treseder et al., 1995). Such complex behaviours and morphologies are likely to be phylogenetically conserved, resulting in the observed high levels of network phylogenetic specificity in myrmecophytic networks. This is consistent with previous (non-phylogenetic) work showing that myrmecophytic networks are characterized by strong compartmentalization (Fonseca & Ganade, 1996).
The other network types (myrmecophilic, myrmecochorous and foraging) showed lower levels of phylogenetic specialisation than myrmecophilic networks. This is likely due to the lack of evolution of specialized morphological structures relating to the ant-plant interaction. Although EFNs predominantly attract ants for protection, they can also attract other defensive arthropods including parasitoids, wasps, spiders, mites, bugs, and predatory beetles (Heil, 2015). It is also possible that plants produce EFNs to reduce ant consumption of flower nectar and so to maximise visitations of other pollinators on flowers (Wagner & Kay, 2002). However, myrmecophilic networks showed higher specialisation than foraging networks in terms of ant specialisation on plants. This may be because ants can benefit greatly from EFNs, which contain monosaccharides and disaccharides, and amino acids that are an important energy source (Marazzi et al., 2013) and even alter the predatory behavior of some ants (Wilder & Eubanks, 2010). Indeed, some plants can even coerce their EFN-feeding ant partners through “addiction” based on enzyme inhibition, preventing the ants from feeding on other food sources (Heil et al., 2014; Houadria et al., 2023). Myrmecochorous ants tended to be generalists, being attracted to the non-specific food offered by the plants in the elaiosome (Levine et al., 2019). Although Anjos et al. (2018) showed that ants attracted to elaiosomes (a small lipid-rich structure used by ants as a food source) are more specialized than ants attracted to fruit pulp, our data combined both network types to increase statistical power, and so we were unable to explore this. Lastly, foraging networks exhibit a lower specialisation, presumably in part because this was the only network type that did not necessarily involve a mutualism between the partners. Species involved in these networks are highly adaptable and tend to exploit a wide range of resources within their environment.
Although unstandardised specialisation (H2’) showed similar relationships with elevation and habitat disturbance to previous studies, these relationships were not present for analysis of standardised H2’ or for phylogenetic network specialisation (dsi*). The interaction between network type and elevation was due specifically to differences between responses of myrmecophytic networks and myrmecochoric and foraging networks. The former showed a strong reduction in specificity (H2’) with elevation, while the latter two showed uniform low specialisation across all elevations. This pattern is consistent with the lack of herbivores at higher elevations and hence the reduced need for plant protection by ants (Moraes & Vasconcelos, 2009). For example,Myristica subalulata , a myrmecophytic plant that is abundant across a range of elevations, benefits less from myrmecophytic networks at higher elevations, and shows lower specificity towards its ant partner (Plowman et al., 2017). Previous work has showed that more intimate networks, such as myrmecophytic networks, can be more susceptible to disturbance (Emer et al., 2013; Fayle et al 2017), while less intimate networks might not be significantly affected by disturbance in island regions (Klimes 2017) but may experience greater impact in mainland or continental contexts (Corro et al., 2019). However, we found no difference in response to disturbance between network types (no significant interaction between the predictors), although we did find an overall decreased specialisation (H2’) in response to anthropogenic habitat disturbance. Our failure to replicate any of these results with either standardised H2’ or with measures of phylogenetic network structure (dsi*) raises the possibility that results from previous studies are artefacts, again driven by variation in other network properties. For example, mean network species richness in undisturbed networks was 61.7, compared to that in disturbed networks of 33.9, and network species richness is negatively correlated with H2’ (supplementary, appendix 8). However, combining networks that have been collected using different methods, and with differing sampling efforts is likely to introduce considerable noise into response variables, even when these are standardised against null models and so we feel that our results do not necessarily preclude the existence of such patterns.
Taken together, our results show that ant-plant network specificity is not strongly affected by latitude, elevation or anthropogenic habitat disturbance, but that rather the mode of interaction between the partners is most important. Mutualistic networks involving myrmecophytic plants are highly phylogenetically specialised, due to their long term coevolutionary interaction. Although our meta-analysis recapitulates previous results in terms of relationships between unstandardised H2’ and elevation and disturbance, these results are not present when H2’ is standardised against null models, or where phylogenetic specialised is assessed. This demonstrates the importance of standardising metrics of network structure against null expectations. Overall, we show that strength and intimacy of mutualistic interactions drives patterns of network specialisation at global scales, even across gradients of elevation, latitude and anthropogenic land-use change, all of which have minimal impacts on network structure.