Consequences of invasion for pollen transfer and pollination revealed in a tropical island ecosystem

Research Consequences of invasion for pollen transfer and pollination revealed in a tropical island ecosystem Anna L. Johnson and Tia-Lynn Ashman Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA Author for correspondence: Anna L. Johnson Tel: +1 412 624 0984 Email: alj73@pitt.edu Received: 22 January 2018 Accepted: 28 June 2018 doi: 10.1111/nph.15366 Key words: Apis mellifera, dry tropical forest, floral traits, Hawaii, heterospecific pollen, interspecific pollen transfer, invasive species, pollination network. Summary Pollination is known to be sensitive to environmental change but we lack direct estimates of how quantity and quality of pollen transferred between plant species shifts along disturbance gradients. This limits our understanding of how species compositional change impacts pollen receipt per species and structure of pollen transfer networks. We constructed pollen transfer networks along a plant invasion gradient in the Hawaiian dry tropical forest ecosystem. Flowers and stigmas were collected from both native and introduced plants, pollen was identified and enumerated and floral traits were measured. We also characterized pollen loads carried by individuals of the dominant invasive pollinator, Apis mellifera. Species flowering in native-dominated sites were more tightly connected by pollen transfer than those in heavily invaded sites. Compositional turnover in the pollen loads of A. mellifera was correlated (70%) with turnover in the composition of pollen transfer networks. Floral traits predicted species roles within pollen transfer networks, but many of these differed qualitatively depending on whether plants were native or introduced. Our work indicates that pollen transfer networks change with invasion. Floral morphology and foraging behaviour of the introduced super-generalist pollinator are implicated as key in determining the roles introduced species play within native pollen transfer networks. Introduction Ecological functions that are reliant on mutualistic plant animal interactions, such as pollination and seed dispersal, are some of the processes most threatened by loss of habitat and species invasions (Tylianakis et al., 2008; Neuschulz et al., 2016). For example, the ability of 90% of tropical plant species to successfully reproduce relies on the presence of animals as pollen vectors (Ollerton et al., 2011). Pollination networks, in particular, have emerged as powerful tools for quantifying how patterns of species diversity and composition relate to key ecological functions (Tylianakis et al., 2010; Kaiser-Bunbury et al., 2017). The ecological role of individuals within communities is contingent upon the presence and function of co-occurring species, particularly when species are mutualistically interacting, as in pollination networks. Describing the emergent structure of networks (Tylianakis & Morris, 2017) provides a community-wide context for understanding how individual species characteristics mediate ecological functions of interest in natural communities. A key ecological function that is understudied at the scale of the community is that of pollen transfer. The quantity and quality of pollen transferred within and between plant species determine reproductive fitness and population abundances, and mediate selection on floral traits and plant mating systems (Knight et al., 2005). A more comprehensive understanding of pollen transfer dynamics may be especially important for predicting the impacts of introduced plant and pollinator species on remnant native plant species. To date, there has been little support for a consistent effect of species invasions on pollinator visitation network structure (Vila et al., 2009; Albrecht et al., 2014). A recent meta-analysis (Charlebois & Sargent, 2017) found no consistent effects of invasive plant species presence on visitation and seed set in coflowering native species. There is reason to predict, however, that in some cases, introduced species have strong impacts on pollen transfer dynamics and native species reproductive fitness. For example, invasive plant species with showy floral displays have impacted the structure of interactions within the coflowering community (e.g. Bartomeus et al., 2008; Emer et al., 2015). There is also evidence that native plant species fitness is reduced by sharing pollinators with introduced plants, because pollen from invasive plants can have outsized negative impacts on reproductive fitness of native coflowering species (Arceo-Gomez & Ashman, 2016). Introduced super-generalist pollinators that interact with a wide variety of plant species can cause shifts in network structure, such as increases in pollination network connectivity and stability (e.g. Aizen et al., 2008; Traveset et al., 2013). In some cases, particularly for the widely introduced and highly generalized European honeybee (Apis mellifera), it is unclear whether the majority 142

Phytologist Research 143 of these ecological impacts on network structure are positive or negative for remnant native plant species. While A. mellifera plays a substantial role in pollination in natural ecosystems around the world and may fill important empty pollination niches (Hung et al., 2018), studies have also found that honeybee presence can reduce the abundances of native pollinators without effectively replacing their pollination services to native plants (e.g. Norfolk et al., 2018). Studies of pollination network structure and pollen transfer dynamics that consider both pollinator foraging niche breadth and floral morphological traits are likely to lead to more useful frameworks for predicting the impacts of species introductions on pollination quantity and quality to remnant native plant communities. This is because not all native species would be expected to receive pollen from coflowering invasive species, as floral morphology mediates the amount of heterospecific pollen species receive (Adler & Irwin, 2006; Fang & Huang, 2013; Arceo- Gomez et al., 2016), and pollinator generalism determines the degree to which co-occurring species actually interact via pollen transfer. For example, floral traits that are predicted to lead to high heterospecific pollen receipt, such as large flowers, large stigmas and exerted styles (Fang & Huang, 2013; Arceo-Gomez et al., 2016) may make these species also more susceptible to increased pollen interactions caused by species introductions. Likewise, plant species which are abundant in the community or produce large quantities of pollen may be more likely to attract generalized introduced pollinators and donate pollen to coflowering native species (e.g. Dietzsch et al., 2011). A recent study by Emer et al. (2016) highlighted that invasive species tend to conserve their functional roles within pollination networks between native and introduced ranges. This suggests that identifying correlates between invasive species floral traits, which mediate interactions between plants and pollinators, and their roles within pollen transfer networks may lead to improved predictions of the impacts on pollination to the coflowering community by newly introduced species. While some invasive plant and pollinator species might quickly integrate into communities and become central and impactful components of pollen transfer networks, other invasive species with different floral characteristics for example, less showy floral displays and less accessible nectar or pollen may remain more peripheral and interact with relatively low numbers of native species via pollen transfer, which in part may explain the observed generally inconsistent impacts of introduced species on pollination dynamics (Vila et al., 2009; Albrecht et al., 2014). To understand how invasive plant and pollinator species interact within pollen transport networks and to determine whether plant species roles within pollen transfer networks result from variation in abundance, species origin and floral morphology, we quantified pollen receipt and constructed directed pollen networks along a plant invasion gradient in the remnant dry tropical forest of Hawaii, HI, USA. Contemporary Hawaiian dry forest communities are fragmented and relatively species poor, but they contain a functionally and phylogenetically diverse suite of native and introduced species, the latter of which arrived primarily over the last several hundred years and have achieved moderate dominance (Blackmore & Vitousek, 2000). The Hawaiian dry forest is also an important example of an ecosystem in which introduced generalist pollinators may have already broadly restructured pollen transfer dynamics: remnant native specialist pollinators (primarily endemic birds and bees in the genus Hylaeus) are in sharp decline (Magnacca & King, 2013; Aslan et al., 2014), while the non-native super-generalist pollinator, Apis mellifera (European honeybee), is one of the most abundant current pollinators in Hawaii, with unclear impacts on pollination to the native plant species adapted to primarily interacting with specialized pollinators. Thus, we specifically asked: (1) Does interspecific pollen transfer network structure vary with intensity of plant invasion? (2) Does the overall amount of heterospecific and conspecific pollen that plant species receive vary significantly along the invasion gradient? (3) Is variance in the structure of pollen transfer networks more strongly correlated with shifts in the composition and abundance of the coflowering community or the composition and abundance of pollen carried by A. mellifera? (4) Do plant abundances and floral morphology explain variation in native and introduced species structural roles in the pollen transfer network? Materials and Methods Study system This study was conducted on the island of Hawaii, HI, USA, within one of the largest remaining intact sections of dry tropical forest in the archipelago. Thirteen sites were located from 610 to 1669 m elevation in the Hawaii Experimental Tropical Forest reserve, at Pu u Wa awa a (PWW) (19 43 0 52 N, 155 53 0 23 W) and the conservation areas of the Pohakuloa Training Area (PTA) (19 43 0 20 N, 155 43 0 44 W) (Supporting Information Fig. S1). The surveyed sites were arranged along a a and pahoehoe lava flows of varying ages and contained a savannah-like mix of grasses (primarily the highly invasive fountain grass, Pennisetum setaceum), flowering native and introduced herbs, shrubs and short-statured trees. Data were collected for 23 flowering species representing 16 families (Table 1). A combination of invasion, fire and grazing pressures has reduced dry forest area located at PWW by over 50% since 1950 (Blackmore & Vitousek, 2000), leaving a mosaic of invasive dominated and relatively intact native forest. The study areas within PTA are managed for conservation and remain native-dominated. Although bees in the genus Hyleaus were observed during data collection, by far the most commonly observed flower visitor at these sites was A. mellifera (A. L. Johnson, pers. obs.), which is also the most generalized pollinator in the system (P. Aldrich, unpublished data). Data collection From March to April 2016, at each of the 13 sites, we established two (50 m apart) parallel 100 9 1 m transects. Within each transect, we counted all open flowers and identified each to species once during the study period (Table 1). These data were used to

144 Research Phytologist Table 1 List of plant species present and flowering in surveyed plots Family Origin Species Code Mean (SE) of proportional floral abundance at sites Amaranthaceae Native Chenopodium oahuense CHOA 0.119 (0.084) Asteraceae Introduced Ageratina riparia AGRI 0.063 (0.030) Asteraceae Introduced Senecio madagascariensis SEMA 0.061 (0.045) Ericaceae Native Styphelia tameiameiae STTA 0.380 (0.094) Ericaceae Native Vaccinium reticulatum VARE 0.001 (0.0004) Fabaceae Native Acacia koa ACKO NA Fabaceae Native Sophora chrysophylla SOCH 0.003 (0.002) Gentianaceae Introduced Centaurium erythraeae PINK 0.0004 (0.0004) Geraniaceae Introduced Geranium homeanum GEHO 0.006 (0.005) Malvaceae Native Sida fallax SIFA NA Myrtaceae Native Metrosideros polymorpha MEPO 0.035 (0.026) Passifloraceae Introduced Passiflora tarminiana PASS NA Poaceae Introduced Pennisetum setaceum PESE 0.038 (0.022) Primulaceae Introduced Anagallis arvensis ANAR 0.001 (0.0004) Primulaceae Native Myrsine lanaiensis MYLA NA Proteaceae Introduced Grevillea robusta GRRO 0.048 (0.032) Rosaceae Native Osteomeles anthyllidifolia OSAN 0.009 (0.006) Rubiaceae Native Coprosma montana COMO NA Santalaceae Native Santalum paniculatum SAPA NA Sapindaceae Native Dodonaea viscosa DOVI 0.230 (0.043) Scrophulariaceae Native Myoporum sandwicense MYSA NA Scrophulariaceae Introduced Verbascum thapsis VETH NA Solanaceae Introduced Nicotiana glauca NIGL 0.0001 (0.0002) Verbenaceae Introduced Lantana camara LACA 0.006 (0.006) Stigmas were collected from all species listed except for P. setaceum. Some species were present in plots and had stigmas collected from them but were too scattered in their distribution to be measured in floral transects; floral abundance is listed for them as not available (NA). Species codes are used in figures and tables throughout this paper to refer to individual species. calculate species richness, the proportion of invasive floral cover at each site as well as overall floral abundance, and these measures reflect quantitative invasion level for each site. Additionally, we randomly collected 5 30 stigmas from each flowering species (barring grasses) at each site, by searching around the two established transects. We collected stigmas from each site on multiple days across the two-month study period. Three to five stigmas per species were preserved in 70% ethanol in centrifuge tubes, following Arceo-Gomez et al. (2016). We collected stigmas at flower senescence to integrate pollen deposited across the full lifetime of the flower. We average pollen counts across multiple stigmas per individual to reduce variation in results from stochastic events such as loss of deposited pollen grains due to wind, rain or animals. For analysis, we acetolyzed (Kearns & Inouye, 1993) two randomly selected tubes of stigmas of each species at each site. We counted and identified all pollen grains in each sample at 9400 magnification on a compound light microscope (CX41; Olympus Corp., Center Valley, PA, USA) and calculated the number pollen per stigma. In total, 27 904 pollen grains from 986 stigmas were observed. Pollen grains were identified to species using a pollen reference collection from all species observed flowering at the sites. At nine of the 13 sites, we collected 10 individuals of A. mellifera and stored each individually in 70% ethanol. Rough terrain and weather, along with low insect abundances, precluded collection of 10 bees at the remaining four sites. In the lab, we removed pollen from their bodies via 30 s of sonication, concentrated it by centrifuging and removing supernatant, and acetolyzed the remaining pollen. This method led to the inclusion of pollen grains from both the corbiculae and the bodies, so while it may accurately depict which plants were visited by the bees, it does not necessarily depict which pollen grains were available for pollination versus stored as food for bee larvae. We identified the first 200 pollen grains per bee encountered on each slide using 9400 magnification on a compound light microscope (CX41). Rarefaction analysis indicated this sampling intensity effectively captured the richness of pollen species on a bee (Fig. S2). Bees with less than 200 pollen grains available were removed from analysis, leaving a total of n = 57 bees analysed (n = 3 10 bees per site, mean per site = 6). Assessing pollen transfer along invasion gradients For each site, we constructed a directed interspecific pollen transfer network (e.g. Fang & Huang, 2013), using functions contained in the IGRAPH package (Csardi & Nepusz, 2006) in R (R Core Team, 2015). Directed networks portray each plant species as a vertex, with the connections between each vertex representing either donation of pollen by a species (directed away from the focal vertex, or out ) or pollen receipt from other species in the network (directed towards the focal vertex, or in ). We created an external designation to group pollen grains from species not present locally at each site and prevent bias in calculations towards donation as a consequence of lack of stigma collection from these

Phytologist Research 145 species. Species grouped into this category included grasses (Pennisetum setaceum, 69% of all external pollen grains), pollen grains we were unable to identify (20%) and identifiable species not growing within the sampled plot (11%). To understand whether the structure of pollen transfer networks shifts with changing species composition, we calculated parameters that describe network structure at each site. We reasoned that if introduced plant species were more generalized in their interactions and more successful at attracting the generalist introduced pollinator, A. mellifera, compared with more specialized native plant species, then connectivity, linkage density and network size would increase and modularity and nestedness would decrease with increasing invasive plant dominance. Network size was calculated as the total number of species either donating or receiving heterospecific pollen at each site and connectivity (White & Harary, 2001) was calculated as a metric which assesses robustness of the network to loss of nodes and represents the proportion of possible links which are actually present in a network. We also estimated linkage density, or the average number of links per species. Modularity is a measure of whether species are structured into subsets within the network that are more densely connected to one another than to species outside the module. We used the Girvan man algorithm (man & Girvan, 2004), implemented via the cluster_edge_betweenness function in the IGRAPH package. We assessed overall nestedness of each network, using the wnodf statistic, which incorporates weights of network edges (Almeida-Neto & Ulrich, 2011). Pollinator visitation networks tend to be more modular and nested than expected by chance (Tylianakis et al., 2010), which is hypothesized to make interactions more robust to disturbance or change. To determine whether these patterns held true for pollen transfer networks as well, we conducted null model analysis of the degree of modularity and nestedness for each observed pollen network. This was done by simulating 1000 random networks, maintaining observed species richness and linkage density, and then calculating the nestedness and modularity of each simulated network and comparing that to the actual observed level of nestedness and modularity at each site. To address whether interspecific pollen transfer network structure varies with intensity of invasion, we used linear mixed models to relate individual site network structural parameters to site invasion level. We grouped sites by 500-m-wide altitude bands, creating four groups (see later Table S3) and included this as a random effect in models, as previous studies in Hawaiian dry forest have suggested that pollinator communities and visitation rates shift along elevation gradients (Koch & Sahli, 2013). We log-transformed invasion level, estimated from floral cover surveys, to fulfil normality distribution requirements for models. To assess whether including site-specific invasion level in the model improved model fit, we compared the full model to a null model containing just the random effects, using a likelihood ratio test (Zuur et al., 2009). As an estimate of the overall quality of pollen received, for each species we calculated the amount of heterospecific and conspecific pollen per stigma and calculated the proportion heterospecific pollen received. We then evaluated whether these metrics varied along invasion gradients in predictable ways across species, using the modelling procedure described above. We estimated whether the amount of conspecific and heterospecific pollen received, as well as the proportion of heterospecific pollen in the load varied along an invasion gradient, this time including altitude as well as recipient species identity as random effects in the models. We also modelled the change in the proportion of heterospecific pollen received from invasive plant species along invasion gradients, as invasive pollen can have stronger negative impact on recipient reproduction (Arceo-Gomez & Ashman, 2016). Correlation between floral cover, A. mellifera pollen loads and pollen transfer To address whether variance in the structure of pollen transfer networks was better explained by shifts in the composition and abundance of the flowering community from site to site or the variation in composition and abundance of pollen carried by A. mellifera from site to site, we performed Procrustes rotations (Peres-Neto & Jackson, 2001). Using this procedure, we statistically compared the concordance of nonmetric multidimensional scaling (NMDS) ordinations of site floral composition, A. mellifera pollen load compositions and heterospecific pollen network composition at the nine sites for which A. mellifera was collected. Each data set was first range-transformed to account for variation in units of measurement. Significance of correlations between ordinations was assessed via permutational analysis (n = 999) using the PROTEST function in R (Oksanen et al., 2015), with correlations reported based on symmetric sum of squares. When compositional ordinations were significantly correlated, we explored which species drove the majority of compositional similarity by fitting compositional matrices to one another using the envfit algorithm in R, from the VEGAN package (Oksanen et al., 2015). Species-level network roles and floral traits To understand the structural contribution each plant species made to each network, we calculated species-level parameters at each site. Degree in and degree out for each plant species in each network were assessed as simply the number of connections in and out (i.e. the number of other species interacted with via pollen transfer, e.g. Foster et al., 2010). Weighted degree in and out was calculated as the degree in and out, weighted by the number of pollen grains exchanged. We estimated the structural centrality of each plant species in the network using the pagerank algorithm, a weighted measure which incorporates the number of links in and out of a particular node, as well as the centrality of other nodes to which that node is linked (Brin & Page, 2012). A more central focal species exchanges more pollen with other species in the network which also are exchanging pollen with a relatively large number of species in the network. We additionally calculated a hub and authority score for each species (Kleinberg, 1999). A species which is a good hub donates many pollen grains to other well-connected species. A species which is a good authority receives many pollen grains from other well-connected

146 Research Phytologist species in the network. Finally, we subtracted the hub score from the authority score for each species in each network, to create a net contribution score to the network for each species; a value > 0 indicates a species which receives more pollen from the network than it donates while a value < 0 indicates a species which donates more pollen than it receives. To determine whether floral characteristics correlated with species structural role in pollen transfer networks and the amount and type of pollen received, we measured floral traits that have been suggested to impact pollen transfer (e.g. Ashman & Arceo-Gomez, 2013; Fang & Huang, 2013; Tong & Huang, 2016) on five flowers from each species. Flowers were haphazardly collected in the field, preserved in ethanol, and in the lab, the following traits were measured under a dissecting microscope to the nearest mm with digital calipers: corolla width at the widest point, style length and anther length. The area of the stigma was estimated to the nearest 0.01 mm from a photograph taken using a dissecting microscope (Leica EZ4W), using IMAGEJ (Schindelin et al., 2015). Mean values per species were used in analyses. Additionally, we recorded whether the position of the stigma extended beyond the petals (exerted stigma) or remained below the petals (enclosed stigma), and the species origin (native or invasive). Finally, we also calculated each species proportional floral abundance at each site, based on the floral transect data (Tables 1, S1). We used a generalized linear mixed model (GLMM) to evaluate the influence of species characteristics on species roles in pollen transfer networks. The distribution of dependent variables was strongly right skewed for many of the models and was presented as count data in some cases (i.e. degree in and degree out), leading us to select a combination of poisson and negative binomial distributions for modelling. We estimated model family appropriateness using tests for distribution of residuals, uniformity, overdispersion and zero inflation specifically developed for use with hierarchical models via the DHARMA package (Hartig, 2017). To account for the hierarchical nature of our data, we included the interaction between species and site as a random effect in all models. In addition, several models were significantly overdispersed so we also included an individual sample error term in an effort to address this issue (Harrison, 2014), which in all cases improved fit based on model diagnostics. For models to assess the effects of plant traits, we selected coefficients to include in each model a priori, based on previous findings from the literature (Fang & Huang, 2013; Arceo-Gomez et al., 2016). All models contained species origin and proportional abundance at sites as coefficients, as well as the interaction between these two. For estimates of species pollen receipt (degree in, weighted degree in, quantity of conspecific and heterospecific pollen received, proportion of heterospecific pollen received), we included stigma area, style length, corolla width and stigma position, in addition to the interaction between these traits and species origin. For estimates of species pollen donation (degree out, weighted degree out), we included corolla width and stamen length, in addition to the interaction between these traits and species origin. For models describing species roles in the context of the structure of the network (centrality, authority and hub position), we did not have a strong a priori reason to expect species traits to predict these roles so we focused simply on species origin, proportional abundance at sites and the interaction between the two. To fit models, we first fit the full model, including all possible traits. We then simplified the model using the drop1 function to remove model terms one at a time, but stopped removing terms when model AIC scores did not substantially improve with the removal of an additional term (using a cutoff value of 2, Burnham & Anderson, 2010). For each dependent variable, we also ran a null model, containing just the random effects, and used likelihood ratio tests to compare the null model to the final model containing predictors (either the original full model or the simplifying model). If there was no significant improvement between the null and the selected model, then we report just the null model. We report the estimate and standard error of each variable remaining in the best explanatory model, as well as the significance of the term. For all remaining significant interaction terms in the models, we extracted and visualized the effects of the predictor variables from the focal GLMM models using the EFFECTS package in R (Fox & Hong, 2009). Results Invasive species accounted for < 1 99% of the floral cover at our study sites (Table S2; Fig. S1). However, neither overall floral abundance at each site nor flowering species richness were correlated with degree of invasion (Figs S3, S4). Twenty-three flowering species (15 native, eight invasive) representing 16 families (Table 1) were represented in the pollen transfer data set that totalled 26 682 conspecific and 739 heterospecific pollen grains from 986 stigmas. The majority of heterospecific pollen received came from the 23 known species, with only 40 pollen grains remaining unidentified. The proportion of heterospecific pollen on individual stigmas ranged from 0 to 86% of the pollen load (mean = 7%, CV = 140.6). Pollen loads collected from A. mellifera contained pollen from 15 identified species, representing both native and invasive species (proportion of unknown pollen species in pollen loads, mean SD: 0.05 0.17) (Fig. S5). Network structure and variation along invasion gradient Pollen transfer networks ranged in size from 5 to 13 species per site (mean SD: 9.5 2.3, Table S3). On average, connectivity was relatively low (0.12 0.05) corresponding to on average only 12% of all possible connections between species being realized. Five species (Senecio madagascariensis, Dodonaea viscosa, Metrosideros polymorpha, Osteomeles anthyllidifolia and Pennisetum setaceum) contributed 82% of all the heterospecific pollen observed across the sites. Eight of the 13 networks were significantly more nested than expected by chance (Z score range: 9.1 to 4.5, P < 0.001), as is typically seen in pollination networks, while one site was significantly less nested (Z score 3.5, P < 0.001) and four were no different from the null expectation

Phytologist Research 147 (Z score range: 1.9 to 0.9, P > 0.06, Table S3). None of the networks, however, were more or less modular than expected by chance (Z score range 0.2 to 0.28, P > 0.78, Table S3). Heterospecific pollen transfer networks became significantly less connected as the overall cover of invasive species at sites increased (v 2 = 4.55, P = 0.03; Fig. 1; Table 2). Linkage density (the number of connections per species) also showed a marginally significant decrease as sites became more invaded (v 2 = 3.47, P = 0.06). There was no change, however, along invasion gradients in the overall network size, network modularity, the number of modules or overall network nestedness (all v 2 < 1.67; all P > 0.2). Relationship between pollen transfer, floral composition and A. mellifera pollen loads Stress values from NMDS for pollen transfer networks, floral cover and A. mellifera pollen ordinations, respectively, were 0.11, 0.07 and 0.06. Floral composition at each site was not significantly correlated with the composition of heterospecific pollen transferred between stigmas at each site (Procrustes correlation = 0.33, P = 0.74). There was also no relationship between A. mellifera pollen loads and site floral composition (Procrustes correlation = 0.40, P = 0.5). The composition of A. mellifera pollen loads at each site was significantly related, however, to the composition of heterospecific pollen transferred between stigmas at each site (Procrustes correlation = 0.68, P = 0.024), indicating that almost 70% of variation in the composition of heterospecific pollen transferred between stigmas was explained by variation in pollen loads carried by A. mellifera. When the proportional representation of species in A. mellifera pollen loads from each site was fitted to the ordination of sites based on the composition of pollen on stigmas, four species two native (Metrosideros polymorpha and Santalum paniculatum), one invasive (Senecio madagascariensis), and one unidentified species were found to significantly contribute to the correlation between bee loads and stigmas (Fig. 2). Variation in quantity and quality of pollen received by species Species in sites dominated by invasive floral cover received slightly, but nonsignificantly, smaller loads of heterospecific pollen (v 2 = 2.94, P = 0.08, Table 3) and these contained proportionally less pollen from invasive donors (v 2 = 4.8, P = 0.03). We observed no change, however, in the total amount of conspecific pollen received along the invasion gradient nor in the proportion of the two (Table 3). Impact of species characteristics on roles in networks and quantity and quality of pollen loads Some species characteristics influenced species roles within networks. Species degree out and weighted degree out (a measure of pollen donation to the network) showed a significant negative relationship to stamen length and a significant positive relationship with corolla width but the strength of these relationships depended on species origin (Table 4a; Fig. 3a,b). Specifically, (1) invasive species with longer stamens donated less pollen to the network, while the opposite relation was true for native species and (2) native species with larger corollas tended to donate less pollen to networks, while the reverse was true for invasive species. There was no effect of the predictor variables proportional abundance or species origin on degree out or weighted degree out (Table 4a). Species degree in and weighted degree in (a measure of pollen receipt within the network) were positively correlated with style length, as well as being native to Hawaii, but these variables also interacted (Table 4a). Invasive species with longer styles received more pollen, while native species with longer styles received slightly less pollen (Fig. 3c,d). There was no effect of the predictor variables stigma area, stigma enclosure, corolla width and proportional abundance on degree in or weighted degree in (Table 4a). The proportion of heterospecific pollen in stigmatic pollen loads was not explained by any of the factors in the full model, and the null model was found to be the best fit (Table 4b). The quantity of heterospecific pollen received by species, however, was significantly positively related to style length. Additionally, native species received more heterospecific pollen than invasive species (Table 4b). The interaction between species origin and stigma area and style length was also significant in the model: while invasive species received uniformly low amounts of heterospecific pollen, regardless of stigma area, native species with larger stigmas received more heterospecific pollen (Fig. 4a). Invasive species with longer styles received slightly more heterospecific pollen, but native species showed little change in heterospecific pollen loads with style length (Fig. 4b). The factors corolla width, stigma area, stigma enclosure and proportional abundance, however, did not significantly explain the amount of heterospecific pollen received (Table 4b). Conspecific pollen quantity received was positively related to corolla width and style length, as well as being native to Hawaii (Table 4b). Additionally, stigma area and corolla width interacted with species origin: native species with larger corollas received less conspecific pollen while the reverse was true for invasive species (Fig. 4c). Invasive species with larger stigmas received more conspecific pollen, while native species with larger stigmas received slightly less conspecific pollen (Fig. 4d). Stigma area, stigma enclosure and proportional abundances did not impact the amount of conspecific pollen received (Table 4b). We also modelled species contextual roles in networks (centrality, hub or authority positions), but found that neither species origin, proportional abundance nor the interaction between the two explained any of the variation, and thus the null model was the best fit for all (Table S4). Discussion This study adds significantly to our understanding of how the structure of pollen transfer networks varies not only across sites (Emer et al., 2015; Tur et al., 2016), but also in response to shifts

148 Research Phytologist Fig. 1 Pollen transfer networks in more invaded dry forest sites were significantly less connected by pollen transfer than sites that were dominated by native species, after running linear mixed models containing site elevation as a random effect. Shaded area represents 95% confidence interval. Representative images of pollen transfer networks from sites located across the observed invasion gradient are represented along the bottom. Site codes for each depicted network describe general location (PTA, Pohakuloa Training Area; PWW, Pu u Wa awa a Forest Reserve) and plot number within site; see the Supporting Information (Fig. S1; Table S1, S2) for maps and detailed plot information. In each network image, the size of the vertices is proportional to the number of heterospecific pollen grains donated or received. Vertices are also colour-coded based on species origin; white, species native to Hawaiian dry forest; grey, introduced species; black, pollen grains were unidentified and/or came from species not present within plot boundaries. This final category also contains pollen from grasses (i.e. Pennisetum setaceum), for which no stigmas were collected. Vertices lacking connections in images indicate species which did not exchange heterospecific pollen with any other species at the site. Edges indicate direction that pollen flows, and the width of each edge is proportional to amount of pollen grains which are moving in that direction. *, P < 0.05. Table 2 Results from linear mixed models testing for relationships between invasive cover at sites and network structural parameters, while controlling for random effects from altitude Network Parameter Slope df v 2 cover Invasive Connectivity 0.02 4 6.32 0.01* Linkage density 0.08 4 3.74 0.05* Network size 0.27 4 0.68 0.41 Modularity 0.01 4 0.37 0.54 Number of modules 0.41 4 1.67 0.2 Nestedness 0.8 4 1.2 0.27 Slope and df column reports slope of full model containing invasive cover and full model degrees of freedom. v 2 and P-values are given for likelihood ratio tests comparing full model to a null model containing just random effects, to test whether including invasive cover at sites significantly improves model fit. *, P < 0.05, significance indicated by bold values. in a major ecological disruptor here, a plant invasion gradient. We demonstrated that pollen transfer network connectivity decreased as sites became more invaded, contrary to our expectations. This shift in network structure also translated into variation in the quantity and quality of pollen which individual species received in different communities across the landscape. Much of this site-to-site variation is attributable to the dominant introduced generalist pollinator, A. mellifera, supporting the assertion that pollinator foraging behaviour is a key mediator of the impact of coflowering species in a community on one another via pollen transfer (Carvallo & Medel, 2016; Fang & Huang, 2016). Individual plant species, however, were differentially incorporated into pollen transfer networks and their roles depended more on floral traits than their proportional abundance within sites, perhaps facilitated by the coinvasion of super-generalist A. mellifera. Intriguingly, however, the relationship of floral traits with species roles within networks often depends on species origin. Overall, our study provides evidence that incorporating explicit measures of pollen transfer and variation in floral functional traits can improve our ability to identify which introduced plant species will have strong impacts on pollination of native plants and which native species will be most strongly impacted by their introduction. Shifts in interspecific pollen transfer network structure and pollination quality with invasion We observed a decrease in connectivity and linkage density in pollen transfer networks with increasing plant community

Phytologist Research 149 Fig. 2 Ordination results visualizing the significant fit between the composition of pollen transfer networks at each site (points and ordination space) and composition of pollen collected from Apis mellifera at each site, as determined through Procrustes rotation. Sites are shaded to represent the proportion of invasive floral cover present at each site. Vectors in black represent species in A. mellifera pollen loads which were significantly correlated with the ordination of site pollen transfer networks (two native species, SAPA, MEPO; one introduced species, SEMA; one pollen morphospecies we were unable to identify; see species codes in Table 1) while labelled vectors in grey represent species from A. mellifera pollen loads which were not significantly related to variation in site pollen transfer network composition. Table 3 Results from linear mixed models testing for relationships between invasive cover at sites and the quantity of pollen received on floral stigmas, while controlling for random effects from altitude and recipient species identity Pollen quantity variable Slope df v 2 Invasive cover Total HP 0.18 217.1 2.94 0.08 Total CP 0.37 204.1 0.06 0.81 Proportion of HP 0 183 1.32 0.25 Total HP, invasive donors 0.08 217.1 2.62 0.11 Total HP, native donors 0.09 217.8 1.29 0.26 Proportion of HP, invasive donors 0.02 216.5 4.8 0.03* HP, heterospecific pollen; CP, conspecific pollen. Slope and df column reports slope of full model containing invasive cover and full model degrees of freedom. v 2 and P-values are given for likelihood ratio tests comparing full model to a null model containing just random effects, to test whether including invasive cover at sites significantly improves model fit. *, P < 0.05, Significance indicated by bold values. invasion level. This finding follows patterns observed for pollinator visitation networks sampled along invasion gradients on other tropical islands (Kaiser-Bunbury et al., 2010, 2011), but similar results have not been shown in mainland pollinator visitation networks (e.g. Stouffer et al., 2014). This may be explained in part by the fact that island floras tend to have more generalized pollination syndromes than mainland floras (Barrett et al., 1996) and lower pollinator richness, leading to more initially connected and generalized networks. The relatively connected native-dominated sites that we observed support findings that invasive species are more easily integrated into island pollination networks than mainland networks (Padron et al., 2009; Kaiser-Bunbury et al., 2011). While native species that are central to island pollination networks may already be somewhat tolerant to receipt of heterospecific pollen from coevolved native flora, they may also be more susceptible to novel pressures from introduced plant species which function as strong pollen donors. This is potentially more likely in systems such as we studied, which are already dominated by an introduced generalist pollinator. Unlike studies of mainland plant communities, we found that the invasive plant species were not more central to network structure than native species (Albrecht et al., 2014). We also found most of the site-specific networks were significantly more nested than expected by chance alone, which also matches results from other types of mutualistic interaction networks. There was little evidence of modularity in these networks, though, unlike the findings of a study of pollen transfer networks in invaded and uninvaded sites (Emer et al., 2015). This divergence from other studies could potentially be driven by the fact that all sites, even those that remained locally dominated by native flowering species, were still visited by the abundant super-generalist introduced A. mellifera, preventing species from separating into discrete interaction modules. Additional empirical studies that combine visitation with estimates of pollen transfer (e.g. Alarcon, 2010; Ballantyne et al., 2015) will also assist in determining the degree to which patterns of pollen transfer predictably match patterns of pollinator foraging and help to tie structural network changes in pollen transfer to both shifts in pollinator visitation and to pollination services to plants (e.g. Burkle & Alarcon, 2011; Kaiser-Bunbury et al., 2017).

150 Research Phytologist Table 4 Results from generalized linear mixed models, testing the relationship between plant characteristics (floral morphology, proportional abundances at site and species origin) and (a) network roles as well as estimates of (b) the quantity of pollen received (a) Network roles Degree out Weighted degree out Degree in Weighted degree in ΔAIC = 2 Kept full model Kept full model ΔAIC = 5.95 n = 107 n = 107 n = 107 n = 107 Family = poisson Family = negative Family = poisson Family = negative binomial binomial Random effects = 1 Species:Site Random effects = 1 Species:Site Random effects = 1 Species:Site Random effects = 1 Species: Site + 1 ID Intercept 3.23 (1.58)* 3.10 (1.46)* 1.02 (0.56) 2.95 (0.72)*** Stamen length 6.63 (2.26)** 15.1 (5.39)** NC NC Corolla width 5.54 (2.31)* 10.68 (4.99)* 1.33 (1.44) 1.61 (0.89) Stigma area NC NC 0.72 (1.45) 0.73 (0.81) Style length NC NC 1.72 (0.7)* 3.37 (1.46)* Stigma enclosure NC NC 0.87 (1.20) 1.34 (2.32) Proportional abundance 1.18 (0.61) 0.04 (3.44) 0.51 (0.57) Species origin 0.62 (0.71) 1.28 (1.55) 1.26 (0.61)* 1.90 (0.76)* Stamen length 9 Species origin 8.25 (2.34)*** 17.45 (5.50)** NC NC Corolla width 9 Species origin 6.97 (2.42)** 12.32 (5.14)* 0.91 (1.51) Stigma area 9 Species origin NC NC 1.27 (1.58) 3.64 (3.18) Style length 9 Species origin NC NC 2.15 (0.91)* 4.50 (1.89)* Stigma enclosure 9 NC NC 0.92 (1.28) 1.09 (2.43) Species origin Proportional abundance 9 Species origin 1.84 (3.63) (b) Pollen quantity Heterospecific pollen proportion Heterospecific pollen quantity Conspecific pollen quantity Null model stronger than fitted model ΔAIC = 7.7 Kept full model n = 107 n = 107 n = 107 Family = negative binomial Family = negative binomial Family = negative binomial Random effects = 1 Species:Site Random effects = 1 Species:Site + 1 ID Random effects = 1 Species:Site Intercept 3.44 (0.59)*** 0.01 (0.54) Stamen length NC NC NC Corolla width 1.22 (0.82) 7.11 (1.42)*** Stigma area 1.28 (1.10) 1.50 (0.86) Style length 2.96 (0.84)*** 2.28 (0.83)** Stigma enclosure 0.52 (0.73) 0.02 (0.86) Proportional abundance 1.52 (1.59) Species origin 1.91 (0.63)** 2.99 (0.62)*** Stamen length 9 Species origin NC NC NC Corolla width 9 Species origin 0.11 (1.56)*** Stigma area 9 Species origin 4.08 (1.39)** 6.47 (1.25)*** Style length 9 Species origin 4.05 (1.21)*** 1.09 (1.11) Stigma enclosure 9 Species origin 1.67 (1.15) Proportional abundance 9 Species origin 2.61 (1.79) ΔAIC refers to the difference in AIC between the original full model and the final model. When removing variables did not improve model fit, the original full model was kept. When the full model did not explain relationships better than a null model containing just random effects, no variables were retained; when models were overdispersed, an additional random effect term was included to better account for individual errors. For each variable, the estimate(se) is reported. *, P < 0.05; **, P < 0.01; ***, P < 0.001. Dashes indicate variables not included in the final model; NC reflects variables not considered in a specific model. Significance indicated by bold values. Role of A. mellifera in pollen transfer dynamics Turnover in pollen load composition from A. mellifera was strongly correlated with site-to-site variation in interspecific pollen transfer network composition, suggesting that much of the interspecific pollen transfer was driven by A. mellifera visitation patterns. Thus, while A. mellifera may be filling open functional niches left by declining native pollinators, and maintaining

Phytologist Research 151 (a) (b) (c) (d) Fig. 3 Significant interactions between traits and species origin, extracted from generalized linear mixed models (GLMMs) explaining how species characteristics relate to species roles in pollination networks, with 95% confidence intervals. Solid blue lines, invasive species; dashed pink lines, native species. All traits are range standardized between 0 and 1. Degree out and weighted degree out showed qualitatively similar relationships with stamen length and corolla width, so only degree out is represented in this figure. (a) Relationship between degree out and stamen length, (b) relationship between degree out and corolla width, (c) style length and degree in and (d) style length and weighted degree in. (a) (b) (c) (d) Fig. 4 Significant interactions between traits and species origin, extracted from generalized linear mixed models (GLMMs) explaining how species characteristics relate to quantity of pollen received by species, with 95% confidence intervals. Solid blue lines, invasive species; dashed pink lines, native species. All traits are range standardized between 0 and 1. (a) Stigma area and heterospecific pollen quantity, (b) style length and heterospecific pollen quantity, (c) corolla width and conspecific pollen quantity and (d) stigma area and conspecific pollen quantity.

152 Research Phytologist pollination function to remnant native plant species, this service is likely to come at a cost. Honeybees are a commonly introduced pollinator in natural systems, and feral colonies have become central to many natural area pollination networks (e.g. Padron et al., 2009; Kaiser-Bunbury et al., 2010; Aslan et al., 2016). They tend to forage from a mix of both native and invasive flowering species, as was indicated by the pollen load composition recorded here. Bees in the genus Hylaeus, the only native bee genera in the Hawaiian islands, are specialized and tend to carry pure loads of conspecific pollen almost exclusively collected from native flowering plants (Miller et al., 2015; Kuppler et al., 2017). These native bees, however, are experiencing steep declines in the regions of Hawaii where the present study was conducted (Magnacca & King, 2013). Indeed, while working in the field, only a handful of instances of Hylaeus visitation to flowers were observed at any of the sites (A. L. Johnson, pers. obs.). We similarly did not observe any native avian pollinators, although we did observe the introduced Japanese white-eye visiting flowers of some species (A. L. Johnson, pers. obs.). Functional replacement of missing native mutualistic partners by invasive species with similar niches is well documented, both in Hawaii and in other tropical island systems (e.g. Kaiser- Bunbury et al., 2010; Pejchar, 2015; Kuppler et al., 2017). Replacement of lost native function, however, is not always perfect; for example, Aslan et al. (2014) found that in birdpollinated Clermontia species, the introduced Japanese white-eye was only able to replace native honeycreepers as an effective pollinator for two out of three observed Clermontia species. In our system, while conspecific pollen appears to still be consistently delivered to native species, the quality of pollen loads is reduced by cotransfer of heterospecific pollen. Even in almost entirely native-dominated sites, invasive pollen was still being transferred to native stigmas (Table 2), potentially as a result of the fragmented nature of Hawaiian dry forest as well as the large foraging range of A. mellifera (Beekman & Ratnieks, 2000). This suggests that negative consequences for native reproduction (Arceo- Gomez & Ashman, 2016) could be far reaching, even in locally native-dominated plant communities. For instance, one of the primary drivers of the correlation between honeybee pollen and the composition of pollen transfer networks at sites (Fig. 2) was Senecio madagascariensis, a recent invader to the Hawaiian islands (Le Roux et al., 2006), closely related to species with allelopathic pollen (Irwin et al., 2014). A combination of observation of pollen transfer dynamics as well as more focused field experiments is necessary to determine whether benefits outweigh the costs of A. mellifera as a primary pollinator of native dry forest species. Impacts of nativity and other species characteristics on roles within networks The plant communities we studied represented novel communities, in that they were constructed of a suite of coexisting and interacting introduced and endemic plant and pollinator species. One particularly interesting result was the observation that invasive plant species fulfilled significantly different roles than native coflowering species in pollen transfer networks: native plant species received more heterospecific pollen from more species (Table 4a) than invasive species did. Moreover, floral traits appeared to differentially drive network roles for invasive and native species (Fig. 3a), suggesting that not only are invasive species in this system potentially filling in open functional niches in the community (e.g. Aslan et al., 2014) and integrating into native pollination networks (e.g. Oleson et al., 2002), but also that their floral traits (possibly selected along different axes or towards different optima in their original ranges) were leading to qualitatively different relationships between floral morphology and species roles in pollen transfer networks in their introduced location. This functional difference in phenotype might be more likely for invaders to oceanic island systems, with phylogenetically distinct floras and where unique phenotypes evolve (Losos & Ricklefs, 2009). In the Hawaiian dry forest, introduced species were from a variety of families (Table 1), some of which are not represented in the native flora (e.g. Verbenaceae, Proteaceae). Empirical studies that quantify relationships between functional traits and species roles in pollen transfer networks remain scarce, so the generality of the patterns we observed is not yet clear. For example, in our study, native species with longer stamens but narrower corolla widths were stronger pollen donors, while the opposite was true for invasive species. There was a weak negative relationship between native species style length and pollen receipt, but invasive species with longer styles tended to receive more pollen. We know of few other community-level studies that demonstrate that floral traits determine the degree of pollen donation or receipt; Fang & Huang (2013) did not find correlations between corolla width and stigma traits on pollen donation, but did observe, like us, that species with longer styles received more heterospecific pollen. Montgomery & Rathcke (2012) observed, as we did for native species but not introduced species, that flowers with larger stigma areas received more heterospecific pollen than those with smaller stigmas. Our study uniquely demonstrates, however, that the effect of traits on pollen transfer depends on native versus introduced status, suggesting that there is more at play than just absolute trait values. Conclusions Our results reveal that, much like the structure of pollinator visitation networks, the structure of interspecific pollen transfer networks responds to disturbances and can be a valuable indicator of changes in pollination services, even in systems already disturbed by the introduction of abundant non-native plants and pollinators. The dynamics of pollen transfer may provide crucial insight into the relationship between pollinator visitation and seed set (e.g. de Waal et al., 2015), as well as of the link between pollen transfer and types of interference on the stigma (Arceo-Gomez & Ashman, 2016; Charlebois & Sargent, 2017). Future empirical work is needed, particularly that which explores how functional traits mediate pollen transfer and determine the reproductive outcomes of interactions between co-occurring native and introduced plant species.