# Floral trait similarity at the community-level increases reproductive success suggesting facilitation through pollinator sharing

Marsal D De Amorim, Pedro J Bergamo, Elisa Thébault, Luís G S Perugini, Sabrina A Lopes, André R Rech, Pietro K M Maruyama

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Marsal D De Amorim, Pedro J Bergamo, Elisa Thébault, Luís G S Perugini, Sabrina A Lopes, et al. Floral trait similarity at the community-level increases reproductive success suggesting facilitation through pollinator sharing. Oikos, In press, pp.e11810. 10.1002/oik.11810. hal-05398667

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OIKOS

Research article

Floral trait similarity at the community-level increases reproductive success suggesting facilitation through pollinator sharing

Marsal D. De Amorim<fnref n="1" />,<fnref n="2" />, Pedro J. Bergamo<fnref n="2" />, Elisa Thébault<fnref n="3" />, Luís G. S. Perugini<fnref n="4" />, Sabrina A. Lopes<fnref n="4" />, André R. Rech<fnref n="5" /> and Pietro K. M. Maruyama<fnref n="6" />

**Correspondence:** Marsal D. De Amorim (marsaldanrlei@gmail.com)

Oikos

2025: e11810

doi: 10.1002/oik.11810

Subject Editor: Benoit Gauzens

Editor-in-Chief: Pedro Peres-Neto

Accepted 27 October 2025

<figure><img src="image_3.png" /></figure>

The ability of plants to attract pollinators is context-dependent, influenced by floral traits, abundance, and resources from the plant community. Indirect interactions through shared pollinators, from competition to facilitation, may lead to varied reproductive outputs in plants, and the mechanisms behind these interactions remain to be fully elucidated in complex ecological communities. We aimed to disentangle the mechanisms by which the floral community may impact pollinator sharing and plant reproductive success in the highly biodiverse Campo Rupestre from Brazil. To do so, we investigated the relationships among species traits, ecological networks, pollen deposition and reproductive output (seed set) in variable community contexts, using a piecewise structural equation modeling (SEM) approach. Plant species with similar flowers in relation to its community showed higher seed set, indicating facilitation. In contrast, species with high flower abundance showed decreased visitation rates per flower and conspecific pollen deposition, suggesting intraspecific competition. Our study reveals that, while there is an interplay between facilitation and competition, the former had a stronger influence on the reproductive output of plants sharing pollinators in a highly diverse tropical community. These results show that traits and abundance mediate complex indirect interactions in plant-pollinator communities.

**Keywords:** flower diversity, network analysis, plant-pollinator community; plant reproduction, pollen deposition; seed set.

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www.oikosjournal.org

© 2025 The Author(s). Oikos published by John Wiley & Sons Ltd on behalf of Nordic Society Oikos.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

<footnote n="1">¹Programa de Pós-Graduação em Ecologia, Conservação e Manejo da Vida Silvestre, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil</footnote>

<footnote n="2">²Departamento de Biodiversidade, Instituto de Biociências, Universidade Estadual Paulista, campus Rio Claro, Rio Claro, SP, Brazil</footnote>

<footnote n="3">³Sorbonne Université, CNRS, IRD, INRAE, Université Paris Est Créteil, Université Paris Cité, Institute of Ecology and Environmental Sciences (iEES-Paris), Paris, France</footnote>

<footnote n="4">⁴Programa de Pós-Graduação em Ciência Florestal, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Diamantina, Minas Gerais, Brazil</footnote>

<footnote n="5">⁵Programas de Pós-Graduação em Biologia Animal, Ciências Florestais e Estudos Rurais, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Diamantina, MG, Brazil</footnote>

<footnote n="6">⁶Centro de Síntese Ecológica e Conservação, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil</footnote>
Introduction

Most flowering plants require biotic pollination to ensure
reproduction (Tong et al. 2023). In this context, pollinators
constitute an important reproductive resource for plants,
which are shared among individuals and species within com-
munities (Pauw 2013). The indirect interactions through
shared pollinators influence plant reproductive success, and
vary from competition to facilitation (Sargent and Ackerly
2008). While competition for pollinators among plants in
a community causes less attractive plants to receive reduced
visitation and decrease their reproductive success (Ha et al.
2021, Johnson et al. 2022), facilitation has the oppo-
site effect, as it increases overall attractiveness and repro-
ductive success (Tur et al. 2016, Bergamo et al. 2024, De
Amorim et al. 2025a). Understanding the mechanisms driv-
ing the relative importance of competition and facilitation
in plant-pollinator communities is particularly important
because this balance is a key driver of species coexistence and
stability in plant communities (Pauw 2013, Benadi 2015,
Guimarães et al. 2017, Duchenne et al. 2021).

Plants attract pollinators providing resources such as pol-
len and nectar, and advertise these resources via floral traits
including color and shape (Dudash et al. 2011). Moreover,
the abundance of flowers and individuals also influence pol-
linator attraction (Peuker et al. 2020). For instance, plant
species with longer flowering periods and greater floral abun-
dance tend to interact with more pollinators and experience
higher reproductive success (Lázaro et al. 2020). However,
the success in attracting pollinators is also context-dependent
because floral traits, abundance, and the resources provided by
the plant community also affect the plant's capacity to attract
pollinators (Shibata and Kudo 2020, Sritongchuay et al.
2021). In situations of low abundance of pollinators and
plants, facilitation might predominate leading to greater pol-
linator attraction and reproductive success for plant species
with higher trait similarity and phenological overlap with
plant communities (Bergamo et al. 2020, Lopes et al. 2022).
On the other hand, competition may prevail when plants
are abundant and pollinators become scarce (Rathcke 1983,
Ye et al. 2023).

Quantifying the role that each plant species plays in the
community according to their interaction with pollinators is
a challenge, but this may be accessed by using species-level
network metrics, such as specialization and partner diversity,
which measure how plants distribute their interactions across
multiple partners (Blüthgen et al. 2006, Dormann 2011).
However, these metrics do not directly represent the influ-
ence that plants have on each other by sharing pollinators,
i.e. indirect interactions. Therefore, metrics that are based on
quantification of pollinator sharing may perform better to
explain the influence that one plant species should have on
or receives from others (Lázaro et al. 2020, Bergamo et al.
2022). By linking such metrics with estimates of plants
reproductive success, we can assess how plants affect each
other's fitness through pollinator sharing (Lázaro et al. 2020,
Bergamo et al. 2022). For instance, target and acting degrees

are network metrics based on the Müller's index, which quantify the potential indirect effects among plant species mediated by shared pollinators (Müller et al. 1999, Bergamo et al. 2022). A high acting degree indicates that a plant species has strong direct interactions with pollinators that also visit other plants, thereby indirectly influencing those co-flowering species. Conversely, a high target degree shows that a plant is indirectly influenced by other plants because its pollinators also strongly depend on them. Bergamo et al. (2021) highlighted that plant species with larger target degree, i.e. that are strongly affected by other plants because their pollinators mainly rely on other plant species, are expected to have greater fitness in facilitation scenarios but lower fitness in competition scenarios. While network metrics have been shown to greatly depend on species abundance and traits (Carvalheiro et al. 2014, Lázaro et al. 2020, Bergamo et al. 2021), disentangling their effects on plant reproductive success is still less explored.

An important functional consequence of indirect inter-
actions among plant species in a community can be mea-
sured by heterospecific pollen deposition (Arceo-Gómez and
Ashman 2014, Thomson et al. 2019). The flow of heterospe-
cific pollen can go multiple ways or be almost unidirectional
when a plant species sends more pollen than it receives (Fang
and Huang 2013, Arceo-Gómez et al. 2020). In this context,
deposition of heterospecific pollen mainly causes negative
effects on plant reproduction (Ashman and Arceo-Gómez
2013). However, a few studies have shown indirect posi-
tive association between heterospecific pollen and seed set
(Streher et al. 2020, Lopes et al. 2022). These positive effects
can be related to generalized and closely related plant species
showing higher tolerance to heterospecific pollen deposition
(Streher et al. 2020). Teasing apart correlation from causa-
tion on the effects of heterospecific pollen deposition is also
important (Ashman et al. 2020), since heterospecific pollen
may suggest that the plant received a higher number of visits
or a greater amount of conspecific pollen deposition concom-
itant with heterospecific pollen, which in turn increases seed
set (Tur et al. 2016, Lopes et al. 2022). However, there are
still few studies that link species traits, ecological networks
and reproductive output at the community context, which
is essential to understand how plant-pollinator interactions
may be linked to ecosystem functioning.

The relationship between community patterns and plant
reproductive success is particularly significant in habi-
tats with high diversity, such as OCBIL (old, climatically
buffered, infertile landscapes) ecosystems (Hopper 2009,
Silveira et al. 2016). Species in these habitats have a long his-
tory of adapting to poor soils and limited climatic buffering
in small areas (Hopper 2009, Hopper et al. 2021). Plants in
OCBIL habitats often have restricted distributions and rely
on long-distance pollinators, such as large bees and hum-
mingbirds for gene flow between populations (Hopper et al.
2021, Monteiro et al. 2021). Brazil's Campo Rupestre is one
of such OCBIL areas, characterized by high species ende-
mism within a confined region (Monteiro et al. 2021). In
Campo Rupestre, plant individuals may occur in variable
floral communities, from dense conspecific patches to highly
diverse co-flowering patches (Loiola et al. 2023). Therefore,
we aimed to understand the influence of the floral commu-
nity on pollinator sharing and on the reproductive success of
plants in this highly biodiverse tropical grassland ecosystem
by characterizing the different process involved (Fig. 1): 1) the
community context, which refers to floral trait similarity, flo-
ral abundance, and phenological overlap with the plant com-
munity; 2) the visitation rates by pollinators and the indirect
effect between species quantified by target degree and acting
degree; 3) heterospecific and conspecific pollen deposition;
4) the response variable representing plants’ reproductive suc-
cess: seed set. Facilitation and competition are expected to
shape different relations between these different components
(Fig. 1A versus 1B).

If facilitation will be a predominant process, we expected
that species with greater functional similarity and phenologi-
cal overlap would lead to higher values of both target and
acting degree and visitation rate per flower, as higher floral
similarity and phenological overlap would mean more shared
pollinators (Bergamo et al. 2020, Lázaro et al. 2020). More
abundant species are expected to receive more pollinators
and, by sharing them with other plants, to show higher acting
degree (Carvalheiro et al. 2014). Conversely, less abundant
species are expected to have a higher target degree because
they will share pollinators that interact frequently with other
plants (Bergamo et al. 2021). Species with a higher target
degree are expected to receive more heterospecific pollen
deposition, but may also be more tolerant to its potential
negative effects (Bergamo et al. 2021). In this context, flow-
ering simultaneously with more abundant species could
be advantageous for rarer plants, as they may benefit from
receiving more visits, even though this incurs more hetero-
specific pollen. If facilitation is predominant, the impact
of heterospecific pollen deposition is expected to be weak
compared to the benefits of sharing pollinators, as sharing
pollinators can increase both pollinator visitation frequency
and the quality of conspecific pollen deposition (Streher et al.
2020, Lopes et al. 2022). Therefore, we anticipated a positive
indirect relationship between heterospecific pollen and seed
set. Heterospecific pollen affects seed set indirectly by being
associated with greater conspecific pollen deposition and by
influencing its quality, since it indicates that visitors also for-
age outside conspecific patches.

On the other hand, if competition predominates, higher
plant functional similarity will lead to reduced visitation for
each plant species (Albor et al. 2022). In this context, more
abundant species are likely to ‘hog’ interactions, meaning
they monopolize pollinators, thus increasing their visitation
rate (Albor et al. 2019, Koptur and Barrios 2020), and acting
degree (Bergamo et al. 2021), while less abundant species will
mostly receive pollinators shared with other plants, increasing
its target degree (Bergamo et al. 2021). Species with greater
phenological overlap are likely to compete more with other
species for pollinators, leading to a reduction in the visitation
rate and an increase in their role in the network (target and
acting degree). Species with a higher visitation rate and acting

degree likely experience higher conspecific pollen deposition
and less heterospecific pollen deposition, since they would
receive most of the visits of their pollinators. Finally, we
expect a direct negative effect of heterospecific pollen depo-
sition on seed set due to the interference of heterospecific
pollen on reproduction (Ashman and Arceo-Gómez 2013).

Material and methods

Area of study and sampling design

Fieldwork was carried out in an area of Campo Rupestre
within the campus of Universidade Federal dos Vales do
Jequitinhonha e Mucuri, Brazil (18°11'48"S, 43°34'08"W),
which has 240 ha of area and is contiguous to the protected
area of Biribiri State Park, with 16 998.66 ha. This region is
situated at an altitude of 1300 m a.s.l. The climate is classified
as a mesothermal, subtropical highland climate, characterized
by humid temperate with dry and rainy seasons (Alvares et al.
2013). Campo Rupestre (mountainous rocky grasslands), a
vegetation within the Cerrado, occupies less than 1% of the
Brazilian territory but encompasses more than 10% of the
country's plant diversity (Silveira et al. 2016). Field sampling
was conducted during the rainy season between October 2022
and April 2023 (INMET 2020) as it is the period with the
highest diversity of plant species in bloom (Monteiro et al.
2021, Luna et al. 2024).

To sample the community of diverse plant species and
their interactions with pollinators, we delimited 32 plots for
the study, aiming to select areas with the greatest environ-
mental heterogeneity (e.g. sandy soil, higher rock density,
greater vegetation cover), each one with an area of 2.5 m².
In each plot, we identified plant individuals using numbered
tags throughout the experiment. To identify plant species, we
collected samples from outside the plots and cross-referenced
them with the herbarium at the Universidade Federal dos
Vales do Jequitinhonha e Mucuri and also consulted special-
ists when necessary. Examples of floral diversity are presented
in Fig. 2. During the study period we conducted sequential
steps involving 15 days of active work in the plots followed
by a one-week break, totalling nine work periods interspersed
with eight breaks. During the 15-days work periods, we col-
lected data on the number of flowers per individual, con-
ducted observation of floral visitors, collected stigmas to
quantify pollen deposition, and marked flowers to estimate
seed set at the end of the study across all 32 plots. During the
breaks, we collected data on the flower traits of the plant spe-
cies, but for this we used individuals from outside of the plots
to avoid disturbing plant-pollinator interactions in the plots.

Floral resources and visitors

To estimate the flower abundance to each species we used the
total number of flowers per species counted during the floral
visitor observations. For species with inflorescences, such as
Asteraceae, we counted these as attractive units instead of the
number of florets (Bergamo et al. 2020). We measured mor-
phological flower traits known to impact interaction with
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Figure 1. (A) Schematic representation of acting degree (+ Acting) and target degree (+ Target). Black lines and line thickness represent the frequency of interactions between plants and pollinators. Plant species with high acting degree (+ Acting) exhibit a higher frequency of interactions with a pollinator shared with other plant species, while plants with high target degree (+ Target) have a lower frequency of interactions with shared pollinators. (B and C) The analytical framework used in this study illustrates the division of variables into four parts and the flow of effects from left to right. The first part shows the community context (floral abundance, phenological overlap and functional similarity). The second part shows the acting and target degree and visitation rate that we used to understand the role of the plant species in the network. The third part displays conspecific pollen deposition and heterospecific pollen deposition, along with their effects on the fourth and final part, reproductive success (seed set). Blue and red arrows represent positive and negative relationships, respectively. (B) the scenarios in the facilitation context, (C) the scenarios in the competition context. The figure was created with Canva. Bee and butterfly illustrations were sourced from free elements provided by Pixabay and Graphixmania (via Canva).
<figure><img src="image_8.png" /><figcaption>Figure 2. Examples of floral diversity found in the study. (A) *Tetrapteryx microphylla* (Malpighiaceae), (B) *Lantana hypoleuca* (Verbenaceae), (C) *Richardia grandiflora* (Rubiaceae), (D) *Cuphea disperma* (Lythraceae), (E) *Evolvulus glomeratus* (Convolvulaceae), (F) *Microlicia* sp. (Melastomataceae), (G) *Xyris* sp. (Xyridaceae), (H) *Borreria verticillata* (Rubiaceae), (I) *Lychnophora pohlii* (Asteraceae). The figure was created with Canva.</figcaption></figure>

pollinators, and thus pollinator sharing: corolla length, diameter of corolla opening, stigma and anther height for all species. Corolla length was considered as the distance from the base of the corolla up to the apex of the corolla. Additionally, each species was categorized according to the floral resource offered: nectar, pollen and/or oil (for Malpighiaceae; Supporting information). As the floral morphology of species may be related to their evolutionary history, we built a

phylogenetic tree based on PhytoPhylo using the 'phytools' package (Revell 2024), and applied the *multiPhylosignal* function from the 'picante' package (Kembel et al. 2010) to test the phylogenetic signal (Blomberg's K) of species' morphology. The results indicate that only corolla length showed moderate phylogenetic signal (K=0.60), while stigma height (K=0.03), anther height (K=0.04), and diameter of the corolla opening (K=0.03) showed very weak phylogenetic
signal. Therefore, we did not include the phylogeny in the subsequent analysis.

For the observation of floral visitors, we arrived at the plots and recorded the number of blooming plants before starting. We then filmed each blooming plant individually within the plot for 30 minutes using video cameras. These observations were conducted between 7 a.m. and 3 p.m. throughout the study period, except on rainy days. By analyzing these recordings, we identified each visitor to the lowest taxonomic level possible, and counted the number of flowers visited. We determined whether the visitor made contact with the reproductive structures of the flowers, and when it did, we categorized these as potential pollinators. We recorded pollinators for 480 h (mean = 15 h and 30 min per species, according to flowering phenology; min = 30 min and max = 74 h). We used the number of observations divided by the time of observation and the number of flowers observed to calculate a visitation rate per flower.

## Characterization of floral community

To characterize how similar each of the plants are in the community regarding functional floral traits, we calculated the functional distinctiveness for each species with interaction with pollinators using the function distinctiveness of the package 'funrar' (Grenié et al. 2017). Functional distinctiveness measures how different plant species are from each other. Thus, species with lower values of functional distinctiveness are more functionally similar to others in the community, whereas species with higher values are more functionally distinct. We constructed a matrix of species × mean floral traits and resources, including corolla length, corolla opening diameter, stigma and anther height, all of which were log transformed, and floral resource type as categorical variables, and another matrix with species abundances to weight their contribution to functional distinctiveness in the ordinal space.

To estimate the flowering overlap between plant species we calculated pairwise phenological overlap between species by adapting the index described by Freitas and Bolmgren (2008). This index incorporates the flowering time and flower abundance to measure the synchrony between pairs of species. The total phenological overlap with community for each plant species was estimated as the sum of the values obtained across all pairwise comparisons (Supporting information).

## Pollen deposition and reproductive success

To quantify pollen deposition on flowers, we collected one stigma from each individual plant across all plots during the 15-day observation period. These stigmas were collected from flowers nearing senescence and transported to the laboratory. The stigmas were then placed on a microscope slide with glycerinated gelatin with fuchsin for pollen staining. In each stigma, we counted the number of conspecific and heterospecific pollen types.

To estimate heterospecific pollen deposition per species we used the following equation (McLernon et al. 1996):

Heterospecific pollen deposition = $\xi(x) / \xi(n)$, where:

$x$ = heterospecific pollen deposited on stigmas to each plant species

$n$ = number of stigmas collected to each plant species

To achieve more standardized conspecific pollen deposition measures, since pollen production varies between species, we used the 'min-max scaling' following equation:

Conspecific pollen deposition = $\sum(\min((x - \min(x))/ (\max(x) - \min(x)))$, where:

$x$ = conspecific pollen deposited on stigmas to each plant species

$\min(x)$ = the minimum conspecific pollen found on the stigma to each plant species

$\max(x)$ = the maximum conspecific pollen found on the stigma to each plant species

For plant reproductive success, we marked open flowers in each individual plant across all plots during the 15-day observation period. These marked flowers were monitored until they developed into fruits. The fruits were then collected and placed in a fruit drying chamber. After drying, we counted the number of seeds per fruit. To compare seed production between species, we employed the same standardization used for conspecific pollen, considering the minimum and maximum seed production per species. Min-max standardization represents a relative reproductive success metric for the plants, useful in our case since we lack data on self-pollination or ovule number for the plant species. With this procedure, species with values closer to zero indicate that most individuals in that species had reproductive success closer to the individual with the fewest seeds, while higher values indicate that many individuals in that species had values closer to the maximum observed.

## Network metrics

We first constructed a plant-pollinator interaction matrix with plant species in the columns and pollinators in the rows, with cells indicating the number of flowers visited by each pollinator. The interaction matrix was built pooling the sampling across all plots. Because it was not always possible to identify pollinators at the species level through recordings, we categorized the pollinators into morphotypes in most cases (Supporting information). Since we were interested in pollinator sharing among plants more than in the importance of specific pollinator species, we assumed that our approach was able to represent the extent to which plants shared similar pollinators. We calculated target degree and acting degree for each plant species (Bergamo et al. 2022), as well as the closeness centrality that measures how one plant species is connected with others throughout pollinators. To calculate the values of target degree and acting degree we used the 'Müller's index' (Müller et al. 1999), that represent the indirect relation for ecological networks:

$$d_{ij} = \sum_{n} \left[ \frac{\bar{\xi}_{ik} \bar{\xi}_{jk}}{\xi_{il} \xi_{mk}} \right]$$
where,

$d_{ij}$ = the effect of *j* plant species in the *i* plant species.

$\alpha_{ik}$ = the frequency of interactions between plant species *i* and pollinator *k*.

$\alpha_{jk}$ = the frequency of interactions between plant species *j* and pollinator *k*.

$\Sigma_{il} \alpha_{il}$ = the total of interactions of plant *i*.

$\Sigma_{m} \alpha_{mk}$ = the total of interactions of pollinator *k*.

*n* = number of samples

Using Müller's index, we obtained a plant–plant matrix, where rows represent the effect of other plants on the focal plant species and columns represent the effect a plant species

had on all other plant species in the network. The target degree is calculated as the sum of the rows in the plant-plant matrix, excluding the focal species itself. It represents the effect of all other plant species on the focal plant species. The values range from 0 to 1, where 0 indicates no effect from the community, and 1 represents the maximum effect of the plant community on the focal plant species. The acting degree is calculated as the sum of the columns in the plant-plant matrix for each species, excluding itself. It represents the effect one plant species has on others. These values range from 0 (indicating no effect on other plants) to *n* − 1 (where *n* is the total number of plant species, minus the focal species itself), representing the maximum effect one plant species

<figure><img src="image_9.png" /><figcaption>Figure 3. (A) Network of plant–pollinator interactions. Pollinators are depicted in green circles and plants in yellow circles. Line thickness represents the interaction frequency. Species codes refer to species names the Supporting information. (B) Results of the SEM analysis. Solid lines represent direct effects (p < 0.05). Dashed lines represent ‘indirect’ and ‘TD’ effects, which refer to results derived from recombination during the SEM analysis (Table 1). Dark blue arrows represent a positive relationship. Dark red arrow represents a negative relationship. Light blue squares represent the relationship of facilitation and light red squares represent the relationship of competition. The figure was created with Canva.</figcaption></figure>
can have on others. However, the acting degree and closeness centrality were correlated ($R^2=0.35$, estimate = 56.24, $p < 0.01$), therefore we chose to focus on acting degree for the analyses. All network indices were calculated with the 'bipartite' R-package (www.r-project.org, Dormann et al. 2009).

## Statistical analysis

To assess the effects of floral abundance, functional distinctiveness, phenological overlap, target and acting degrees, visitation rate, heterospecific and conspecific pollen deposition on reproductive success (seed set), we performed all analyses at the species level within the community. Specifically, we employed a piecewise structural equation model (SEM) with the function *psem* of 'piecewiseSEM' R package (Lefcheck 2016, following Lázaro et al. 2020). We used SEM because it allows the simultaneous evaluation of direct and indirect relationships among variables, enabling an integrated understanding of the system. This method combines predictors across different levels to evaluate their cumulative effects and test the global coherence of the hypothesized model. Additionally, SEM applies the concept of directed separation, which tests whether excluded paths (hypotheses) between variables remain significant, ensuring that the model structure captures essential relationships. The significance of predictor variables in SEM was assessed by examining the p-values of the models. For clarity, the SEM analysis was divided into

four parts (Fig. 1). The first part of SEM included the effects of floral abundance, functional distinctiveness and phenological overlap on species level network metrics acting degree and target degree, as well as visitation rate per flower. For the second part, these variables were also included as predictors of heterospecific and conspecific pollen deposition. The third included all above mentioned variables plus heterospecific and conspecific pollen as predictors of reproductive success (seed set). We used the *simulateResiduals* function from the 'DHARMA' package (Hartig 2016) to stabilize the residuals' variance for better model fit. Log transformations were applied as part of model adjustment, not to achieve normality in the predictors. Therefore, we used log-transformed values for floral abundance and heterospecific pollen deposition. For this analysis, we removed 12 species without complete data (i.e. missing information on visitation rate, pollen deposition and/or seed set, sample size = 19; Supporting information). These checked models were included in the SEM. We also checked whether variables included as predictors were correlated, and proceeded with SEM after checking that they were not. For all models we used linear models with *lm* function and gaussian distribution.

All analyses were conducted using the R software (www.r-project.org) within the RStudio integrated development environment (www.posit.co). The data set used for the analyses is in the Supporting information.

<table><caption>Table 1. Results of the SEM. log(HPD) represents heterospecific pollen deposition log-transformed. Both $R^2$ and DF (degrees of freedom) represent parameters of the models. Bold and '*' mean significant values. Test: 'Direct' refers to results from the models in the SEM, while 'Indirect' and 'TD' refers to results derived from recombination during SEM analysis, not directly tested in the models. Indirect represents the subsequent relationship between variables, for example: visitation rates are affected by phenological overlap and, in turn, affect conspecific pollen deposition. TD refers to tests of directed separation.</caption><thead><tr><th>Dependent</th><th>Independent</th><th>Test</th><th>R<sup>2</sup></th><th>DF</th><th>std estimate</th><th>Crit.value</th><th>p-value</th></tr></thead><tbody><tr><td rowspan="3">Visitation rate</td><td>Functional distinctiveness</td><td>direct</td><td rowspan="3">0.59</td><td rowspan="3">15</td><td>-0.23</td><td>-1.33</td><td>0.20</td></tr><tr><td>log(Floral abundance)</td><td>direct</td><td>-0.57</td><td>-3.20</td><td><strong>&lt; 0.01*</strong></td></tr><tr><td>Phenological overlap</td><td>direct</td><td>-0.35</td><td>-1.87</td><td>0.08</td></tr><tr><td rowspan="3">Acting degree</td><td>Functional distinctiveness</td><td>direct</td><td rowspan="3">0.35</td><td rowspan="3">15</td><td>-0.54</td><td>-2.45</td><td><strong>0.02*</strong></td></tr><tr><td>log(Floral abundance)</td><td>direct</td><td>0.01</td><td>0.05</td><td>0.95</td></tr><tr><td>Phenological overlap</td><td>direct</td><td>0.11</td><td>0.47</td><td>0.64</td></tr><tr><td rowspan="3">Target degree</td><td>Functional distinctiveness</td><td>direct</td><td rowspan="3">0.10</td><td rowspan="3">15</td><td>0.27</td><td>1.06</td><td>0.30</td></tr><tr><td>log(Floral abundance)</td><td>direct</td><td>-0.12</td><td>-0.45</td><td>0.65</td></tr><tr><td>Phenological overlap</td><td>direct</td><td>0.00</td><td>-0.01</td><td>0.98</td></tr><tr><td rowspan="5">log(HPD)</td><td>Visitation rate</td><td>direct</td><td rowspan="5">0.29</td><td rowspan="5">15</td><td>0.33</td><td>1.52</td><td>0.14</td></tr><tr><td>Acting degree</td><td>direct</td><td>0.51</td><td>2.23</td><td><strong>0.04*</strong></td></tr><tr><td>Target degree</td><td>direct</td><td>0.17</td><td>0.78</td><td>0.44</td></tr><tr><td>Functional distinctiveness</td><td>indirect</td><td>-0.27</td><td></td><td></td></tr><tr><td>Visitation rate</td><td>direct</td><td rowspan="4">0.56</td><td rowspan="4">15</td><td>0.68</td><td>3.87</td><td><strong>&lt; 0.01*</strong></td></tr><tr><td>Acting degree</td><td>direct</td><td>0.11</td><td>0.62</td><td>0.54</td></tr><tr><td>Target degree</td><td>direct</td><td>0.39</td><td>2.21</td><td><strong>0.04*</strong></td></tr><tr><td>log(Floral abundance)</td><td>indirect</td><td>-0.38</td><td></td><td></td></tr><tr><td rowspan="3">Conspecific pollen</td><td>Visitation rate</td><td>direct</td><td rowspan="3">0.16</td><td rowspan="3">16</td><td>-0.06</td><td>-0.29</td><td>0.77</td></tr><tr><td>Acting degree</td><td>direct</td><td>0.39</td><td>1.71</td><td>0.10</td></tr><tr><td>Target degree</td><td>indirect</td><td>-0.64</td><td>-2.75</td><td><strong>0.01*</strong></td></tr><tr><td rowspan="3">Seed set</td><td>Conspecific pollen deposition</td><td>direct</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>log(HPD)</td><td>direct</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Functional distinctiveness</td><td>TD</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
## Results

We recorded 404 interactions between 31 plant species and 35 pollinator morphospecies, with less than one visit per hour on average. The most frequent visitor was the honeybee *Apis mellifera* with 143 interactions, followed by stingless bee *Trigona* sp. with 42 interactions (Fig. 3, Supporting information). During the study, species abundance ranged from 24 to over 700 flowers per species, flowering overlap from 0.75 to 8.09, and functional distinctiveness from 0.25 to 0.47 (Supporting information). Visitation rate ranged from 0.001 to 0.09, acting degree from 0.07 to 2.68, and target degree from 0.20 to 0.94 (Supporting information). All plant species received heterospecific pollen (0.3–45 grains per species) and conspecific pollen (6.08–146.58 grains). Reproductive success varied from 0.35 to 181.29 (Supporting information).

The SEM analysis showed good fit with the data (global goodness-of-fit: $C_{32}$=37.70; $p$=0.22; Fig. 3). Visitation rate per flower decreased with floral abundance (Table 1, Fig. 4A) and acting degree decreased with functional distinctiveness (Table 1, Fig. 4B). Target degree did not show relationship with any of the variables (Table 1). Heterospecific pollen increased with acting degree (Table 1, Fig. 5A) and had one indirect interaction: it decreased with functional distinctiveness (SE = -0.27; Table 1, Fig. 5B). Conspecific pollen deposition increased with visitation rate (Table 1, Fig. 5C) and with target degree (Table 1, Fig. 5D). Conspecific pollen deposition also had one indirect interaction: it decreased with floral abundance (SE = -0.38; Fig. 5E). Seed set did not show direct relation with conspecific and heterospecific pollen deposition (Table 1). However, seed set decreased with functional distinctiveness (estimate = -0.64; Table 1, Fig. 6).

## Discussion

Here, we uncovered multiple direct and indirect relationships between species abundance, floral traits and phenology of the plant community, i.e. community context, on plant pollination and reproductive success. The positive effects of floral trait similarity on seed set support that pollination sharing has overall positive effects on plant reproductive success in the Campo Rupestre. This is because plant species exhibiting greater trait similarity tend to attract similar pollinators (Carvalheiro et al. 2014, Venjakob et al. 2016, Arroyo-Correa et al. 2024). Such positive impacts on seed set suggest facilitation as the main process driving pollination in the studied plant community (Ashman et al. 2020, Streher et al. 2020, Lopes et al. 2022, Arroyo-Correa et al. 2024).

The strong positive influence of visitation rate on conspecific pollen deposition was expected but, contrary to our hypotheses, abundant plants were associated with decreasing conspecific pollen and visitation rate per flower (Fig. 1). These negative relationships could be related with intraspecific competition (Wei et al. 2021, Ye et al. 2023), where plant species with high numbers of flowers experience less visits per flower and less conspecific pollen as plant

individuals compete for pollinator attraction (Pauw 2013, Monasterolo et al. 2022). However, the less abundant species, which received more conspecific pollen, did not produce more seeds (Fig. 1). The lack of effect of conspecific pollen could be related to geitonogamy, where species that attract floral visitors end up depositing their own pollen or that of close relatives (Mitchell et al. 2004, Karron et al. 2009). A negative relationship between seed production and geitonogamy makes sense, as Campo Rupestre plants generally are self-incompatible but have low dispersal ability, leading to isolated populations that are genetically similar to each other (Silveira et al. 2016, Monteiro et al. 2021). On the other hand, many plants we found during this study have few ovules, such as Asteraceae plants, *Lantana* and *Palicourea*. Therefore, they would require only a few pollen grains to produce seeds, meaning there would not be a direct correlation between conspecific pollen deposition and seed production.

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

Figure 4. (A) Negative relationships between visitation rate and floral abundance and (B) negative relationships between acting degree and functional distinctiveness. Thus, plants with greater functional similarity (i.e. lower distinctiveness values) shared more pollinators. Plants with a higher acting degree are those that receive more frequent visits from shared pollinators.
<figure><img src="image_12.png" /><figcaption>Figure 5. Relationship between heterospecific and conspecific pollen deposition and their predictors. (A) Positive relationship between heterospecific pollen deposition and acting degree (B) and indirect relationship between heterospecific pollen deposition and functional distinctiveness (SE -0.27), indicating that more functionally similar plants (i.e. lower distinctiveness) receive more heterospecific pollen. Relationship between conspecific pollen deposition and (C) visitation rate and (D) target degree. (E) indirect relationship of conspecific pollen and floral abundance (SE -0.38).</figcaption></figure>

This possibility is further supported by the fact that plants in the Campo Rupestre experience low pollen limitation levels (Lopes et al. 2023), reinforcing that a lack of pollen would not be the factor severely affecting their reproductive success.

We found that species with similar floral traits tended to share more pollinators with other plant species, occupying a more central role in the network and increasing heterospecific

pollen deposition. This result supports our initial hypothesis based on the facilitation ecological process, which predicted that trait similarity would promote greater pollinator sharing among species, ultimately enhancing the transfer of heterospecific pollen (Fig. 1; Arceo-Gómez et al. 2020, Bergamo et al. 2020, Lázaro et al. 2020). However, we found an opposite pattern than expected, as we hypothesized that
<figure><img src="image_13.png" /><figcaption>Figure 6. Indirect relationship between the seed set and functional distinctiveness (SE: -0.64) from tests of directed separation of SEM analysis, indicating that more functionally similar plants (i.e. lower distinctiveness) indirectly achieve higher seed set.</figcaption></figure>

species with a higher acting degree would receive less heterospecific pollen and more conspecific pollen while species with a higher target degree (relying on pollinators that also visit many plants) would receive more of both heterospecific and conspecific pollen (Bergamo et al. 2022). This surprising result could be related to the correlation between acting degree and closeness centrality (Supporting information), as central species in the network, sharing more pollinators with all plant species, are expected to receive more heterospecific pollen. In addition, our results show that acting and target degree metrics reveal directional pollen flow patterns, helping to uncover how species interact through pollinator sharing, even when the effects diverge from initial expectations.

Facilitation is an important strategy for plant survival in environments with low pollination, due to the low abundance of either pollinators or plant species (Ghazoul 2006, Tur et al. 2016, Bergamo et al. 2020, Hederström et al. 2024, Arroyo-Correa et al. 2024). The Campo Rupestre are one of these habitats; besides the high plant endemism, the heterogeneity of soil features restricts the species to small, non connected areas (Silveira et al. 2016). Additionally, generalization in pollination systems is common in Campo Rupestre, where interactions between plant and pollinators appear to be characterized by some opportunism (co-occurrence and co-flowering) and floral abundance than to strict morphological specialization (Carstensen et al. 2014, Lopes et al. 2022, Monteiro et al. 2021, Amorim et al. 2022, De Castro et al. 2025). Therefore, generalized plant species are expected to strongly share pollinators in this ecosystem. In this context, facilitation through

trait similarity may be an important mechanism ensuring reproductive success of co-flowering plant species. On the other hand, both intraspecific competition and tolerance to heterospecific pollen may weaken interspecific competition. High floral abundance appears to reduce flower visitation and conspecific pollen deposition, indicating a cost to producing many flowers simultaneously. Meanwhile, tolerance to heterospecific pollen may benefit species that flower simultaneously with others, as it allows them to share pollinators without suffering strong fitness costs from heterospecific pollen transfer. This tolerance may reduce the selective pressure for temporal or morphological segregation and instead promote co-flowering and trait similarity, ultimately favoring facilitation over competition in this system.

In summary, our study revealed that plant species with high abundance had lower per flower visitation rates, which was associated with reduced conspecific pollen deposition, suggesting intraspecific competition. At the same time, plant species with higher floral morphology similarity in relation to the community produced more seeds, indicating that facilitation predominated over competition at the seed set stage. Specifically under low pollination probability scenarios, these positive interactions between plant species show the potential to increase plant coexistence in the habitat. Therefore, plant diversity in the community and indirect interactions between plant species positively affected the reproduction of plants. To conclude, floral similarity and floral abundance shape the positive and negative indirect effects between plants in the whole pollination process in this highly diverse ecosystem.

**Acknowledgements** – We thank Carlos Alberto Ferreira Junior, Jimi Naoki Nakajima, Marcelo Monge and Thiago José Ornelas Otoni (Herbário Dendrológico Jeanine Felfili) for plant species identification and Letícia Pataca, Ingrid Gomes and Lucas Benício for floral visitors identification. We are also grateful to Patrícia Morellato, Tatiana Cornelissen, Gudryan Barônio and Renata Trevizan for their valuable suggestions to the manuscript. The Article Processing Charge for the publication of this research was funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) (ROR identifier: 00x0ma614).

**Funding** – This study received funding from the Rufford Foundation (Application 280 ID: 36234-1). MDA thanks CAPES (Financial code 001, process no. 88887.626004/2021-00). MDA thanks to CNPq ABELHA (401577/2022-8). ARR and PKM thank FAPEMIG (#APQ-00932-21, #APQ-03100-21, #RED-00039-23, #APQ-02806-22, #APQ-03364-21, #APQ-01822-21), CNPq (#311665/2022-5, #300377/2025-8 ) and CAPES (#88887.837988/2023-00). PJB acknowledges CEPID CBioClima (FAPESP 2021/10639-5). PJB, ARR, PKM thank INCT Pollination (CNPq 406976/2022-8/CAPES 88887.953442/24/FAPERJ).

**Conflict of interest** – The authors declare no conflict of interest.

## Author contributions

**Marsal D. De Amorim:** Conceptualization (equal); Data curation (equal); Methodology (equal); Writing – original draft (equal); Writing – review and editing (equal). **Pedro J.**
**Bergamo:** Conceptualization (equal); Methodology (equal); Supervision (equal); Writing—original draft (equal); Writing—review and editing (equal). **Elisa Thébault:** Conceptualization (equal); Writing—original draft (equal); Writing—review and editing (equal). **Luís G. S. Perugini:** Data curation (equal); Writing—original draft (equal); Writing—review and editing (equal). **Sabrina A. Lopes:** Data curation (equal); Writing—original draft (equal); Writing—review and editing (equal). **André R. Rech:** Methodology (equal); Writing—original draft (equal); Writing—review and editing (equal). **Pietro K. M. Maruyama:** Conceptualization (equal); Methodology (equal); Supervision (equal); Writing—original draft (equal); Writing—review and editing (equal).

**Data availability statement**

Data available on Figshare: https://doi.org/10.6084/m9 figshare.29264300 (De Amorim et al. 2025b).

**Supporting information**

The Supporting information associated with this article is available with the online version.

**References**

Albor, C., García-Franco, J. G., Parra-Tabla, V., Díaz-Castelazo, C. and Arceo-Gómez, G. 2019. Taxonomic and functional diversity of the co-flowering community differentially affect *Cakile edentula* pollination at different spatial scales. – J. Ecol. 107: 2167–2181.

Albor, C., Ashman, T. L., Stanley, A. M., Martel, C. and Arceo-Gómez, G. 2022. Flower colour and flowering phenology mediate plant-pollinator interaction assembly in a diverse co-flowering community. – Funct. Ecol. 36: 2456–2468.

Alvares, C. A., Stape, J. L., Sentelhas, P. C., De Moraes Gonçalves, J. L. and Sparovek, G. 2013. Köppen's climate classification map for Brazil. – Meteorol. Z. 22: 711–728.

Amorim, M. D., Maruyama, P. K., Baronio, G. J., Azevedo, C. S. and Rech, A. R. 2022. Hummingbird contribution to plant reproduction in the rupestrian grasslands is not defined by pollination syndrome. – Oecologia 199: 1–12.

Arceo-Gómez, G. and Ashman, T. L.-L. 2014. Coflowering community context influences female fitness and alters the adaptive value of flower longevity in *Mimulus guttatus*. – Am. Nat. 183: E50–E63.

Arceo-Gómez, G., Barker, D., Stanley, A. M., Watson, T. and Daniels, J. 2020. Plant-pollinator network structural properties differentially affect pollen transfer dynamics and pollination success. – Oecologia 192: 1037–1045.

Arroyo-Correa, B., Bartomeus, I. and Jordano, P. 2024. Flowering synchrony modulates pollinator sharing and places plant individuals along a competition-facilitation continuum. – Oikos 2024: e10477.

Ashman, T. L. and Arceo-Gómez, G. 2013. Toward a predictive understanding of the fitness costs of heterospecific pollen receipt and its importance in co-flowering communities. – Am. J. Bot. 100: 1061–1070.

Ashman, T. L., Alonso, C., Parra-Tabla, V. and Arceo-Gómez, G. 2020. Pollen on stigmas as proxies of pollinator competition and facilitation: complexities, caveats and future directions. – Ann. Bot. 125: 1003–1012.

Benadi, G. 2015. Requirements for plant coexistence through pollination niche partitioning. – Proc. R. Soc. B 282: 20150117.

Bergamo, P. J., Susin Streher, N., Traveset, A., Wolowski, M. and Sazima, M. 2020. Pollination outcomes reveal negative density-dependence coupled with interspecific facilitation among plants. – Ecol. Lett. 23: 129–139.

Bergamo, P. J., Streher, N. S., Wolowski, M. and Sazima, M. 2021. Pollinator-mediated facilitation is associated with floral abundance, trait similarity and enhanced community-level fitness. – J. Ecol. 108: 1334–1346.

Bergamo, P. J., Freitas, L., Sazima, M. and Wolowski, M. 2022. Pollinator-mediated facilitation alleviates pollen limitation in a plant-hummingbird network. – Oecologia 198: 205–217.

Bergamo, P. J., Streher, N. S., Freitas, L., Wolowski, M. and Sazima, M. 2024. Male pollination success and female pollination success are mediated by opposing processes in a coflowering community. – Int. J. Plant Sci. 185: 177–186.

Blüthgen, N., Menzel, F. and Blüthgen, N. 2006. Measuring specialization in species interaction networks. – BMC Ecol. 6: 9.

Carvalheiro, L. G. et al. 2014. The potential for indirect effects between co-flowering plants via shared pollinators depends on resource abundance, accessibility and relatedness. – Ecol. Lett. 17: 1389–1399.

Carstensen, D. W., Sabatino, M., Trøjelsgaard, K. and Morellato, L. P. C. 2014. Beta diversity of plant-pollinator networks and the spatial turnover of pairwise interactions. – PLoS One 9: e112903.

De Amorim, M. D., Borges, J. P. R., Machado, A. C. P., Rech, A. R., Maruyama, P. K. and Bergamo, P. J. 2025a. Neighbourhood flower diversity increases reproductive success of *Lantana hypoleuca* Briq (Verbenaceae). – Plant Biol. 27: 1158–1164.

De Amorim, M. D., Bergamo, P. J., Thébault, E., Perugini, L. G. S., Lopes, S. A., Rech, A. R. and Maruyama, P. K. M. 2025b. Data from: Floral trait similarity at the community-level increases reproductive success suggesting facilitation through pollinator sharing. – Figshare, https://doi.org/10.6084/m9.f igshare.29264300.v1.

De Castro, L. B., Pacheco, M. A., de Sousa Perugini, L. G., Maruyama, P. K. and Rech, A. R. 2025. Phenology is an important driver of hawkmoth-flower interactions in a megadiverse mountain area in Brazil. – J. Appl. Entomol. 149: 914–921.

Dormann, C. F. 2011. How to be a specialist? Quantifying specialization in pollination networks. – Netw. Biol. 1: 1–20.

Dormann, C. F., Fründ, J., Blüthgen, N. and Gruber, B. 2009. Indices, graphs and null models: analyzing bipartite ecological networks. – Open Ecol. J. 2: 7–24.

Duchenne, F., Fontaine, C., Teulière, E. and Thébault, E. 2021. Phenological traits foster persistence of mutualistic networks by promoting facilitation. – Ecol. Lett. 24: 2088–2099.

Dudash, M. R., Hassler, C., Stevens, P. M. and Fenster, C. B. 2011. Experimental floral and inflorescence trait manipulations affect pollinator preference and function in a hummingbird-pollinated plant. – Am. J. Bot. 98: 275–282.

Fang, Q. and Huang, S. Q. 2013. A directed network analysis of heterospecific pollen transfer in a biodiverse community. – Ecology 94: 1176–1185.

Freitas, L. and Bolmgren, K. 2008. Synchrony is more than overlap: measuring phenological synchronization considering time length and intensity. – Rev. Bras. Bot. 31: 721–724.
Grenié, M., Denelle, P., Tucker, C. M., Munoz, F. and Violle, C. 2017. funrar: an R package to characterize functional rarity. – *Divers. Distrib.* 23: 1365–1371.

Guimarães Jr, P. R., Pires, M. M., Jordano, P., Bascompte, J. and Thompson, J. N. 2017. Indirect effects drive coevolution in mutualistic networks. – *Nature* 550: 511–514.

Ghazoul, J. 2006. Floral diversity and the facilitation of pollination. – *J. Ecol.* 94: 295–304.

Ha, M. K., Schneider, S. A. and Adler, L. S. 2021. Facilitative pollinator sharing decreases with floral similarity in multiple systems. – *Oecologia* 195: 273–286.

Hartig, F. 2016. Dharma: residual diagnostics for hierarchical (multi-level/mixed) regression models. – https://cran.r-project.org/web/packages/DHARMa/vignettes/DHARMa.html.

Hederström, V., Ekroos, J., Friberg, M., Krausl, T., Opedal, Ø. H., Persson, A. S., Petrén, H., Quan, Y., Smith, H. G. and Clough, Y. 2024. Pollinator-mediated effects of landscape-scale land use on grassland plant community composition and ecosystem functioning – seven hypotheses. – *Biol. Rev.* 99: 675–698.

Hopper, S. D., Lambers, H., Silveira, F. A. O. and Fiedler, P. L. 2021. OCBIL theory examined: reassessing evolution, ecology and conservation in the world's ancient, climatically buffered and infertile landscapes. – *Biol. J. Linn. Soc.* 133: 266–296.

Hopper, S. D. 2009. OCBIL theory: towards an integrated understanding of the evolution, ecology and conservation of biodiversity on old, climatically buffered, infertile landscapes. – *Plant Soil* 322: 49–86.

INMET – National Institute of Meteorology, Brazil 2020. – www.inmet.gov.br/portal/.

Johnson, C. A., Dutt, P. and Levine, J. M. 2022. Competition for pollinators destabilizes plant coexistence. – *Nature* 607: 721–725.

Karron, J. D., Holmquist, K. G., Flanagan, R. J. and Mitchell, R. J. 2009. Pollinator visitation patterns strongly influence among-flower variation in selfing rate. – *Ann. Bot.* 103: 1379–1383.

Kembel, S. W., Cowan, P. D., Helmus, M. R., Cornwell, W. K., Morlon, H., Ackerly, D. D., Blomberg, S. P. and Webb, C. O. 2010. Picante: R tools for integrating phylogenies and ecology. – *Bioinformatics* 26: 1463–1464.

Koptur, S. and Barrios, B. 2020. Are native palms "pollinator hogs"? A field experiment in pine rocklands of southern Florida. – *Nat. Areas J.* 40: 142–149.

Lázaro, A., Gómez-Martínez, C., Alomar, D., González-Estévez, M. A. and Traveset, A. 2020. Linking species-level network metrics to flower traits and plant fitness. – *J. Ecol.* 108: 1287–1298.

Lefcheck, J. S. 2016. piecewiseSEM: piecewise structural equation modelling in r for ecology, evolution and systematics. – *Methods Ecol. Evol.* 7: 573–579.

Loiola, P. P., Morellato, L. P. C., Camargo, M. G. G., Kamimura, V. A., Mattos, J. S., Streher, A. S. and Le Stradic, S. 2023. Shared-role of vegetation types, elevation and soil affecting plant diversity in an old-tropical mountain hotspot. – *J. Mt. Sci.* 20: 1842–1853.

Lopes, S. A., Bergamo, P. J., Najara Pinho Queiroz, S., Ollerton, J., Santos, T. and Rech, A. R. 2022. Heterospecific pollen deposition is positively associated with reproductive success in a diverse hummingbird-pollinated plant community. – *Oikos* 2022: e08714.

Lopes, S. A., Bergamo, P. J. and Rech, A. R. 2023. Effect of plant traits and network metrics on pollen limitation in humming-bird-pollinated plants from the Brazilian Campos Rupestres. – *Flora* 309: 152404.

Luna, A. L. L., Souza, C. S., Neves, J. G. S., Nunes, Y. R. F., Oliveira, P. E. and de Azevedo, I. F. P. 2024. Temporal and spatial variation of floral resources of woody species in a vereda ecosystem: uniformity and habitat complementarity. – *Flora* 310: 152425.

McLernon, S. M., Murphy, S. D. and Aarssen, L. W. 1996. Heterospecific pollen transfer between sympatric species in a mid successional old-field community. – *Am. J. Bot.* 83: 1168–1174.

Mitchell, R. J., Karron, J. D., Holmquist, K. G. and Bell, J. M. 2004. The influence of *Mimulus ringens* floral display size on pollinator visitation patterns. – *Funct. Ecol.* 18: 116–124.

Monasterolo, M., Poggio, S. L., Medan, D. and Devoto, M. 2022. High flower richness and abundance decrease pollen transfer on individual plants in road verges but increase it in adjacent fields in intensively managed agroecosystems. – *Agric. Ecosyst. Environment* 333: 107952.

Monteiro, B. L., Camargo, M. G. G., Loiola, P. D. P., Carstensen, D. W., Gustafsson, S. and Morellato, L. P. C. 2021. Pollination in the campo rupestre: a test of hypothesis for an ancient tropical mountain vegetation. – *Biol. J. Linn. Soc.* 133: 512–530.

Muller, C. B., Adriaanse, I. C. T., Belshaw, R. and Godfray, H. C. J. 1999. The structure of an aphid–parasitoid community. – *J. Anim. Ecol.* 68: 346–370.

Pauw, A. 2013. Can pollination niches facilitate plant coexistence? – *Trends Ecol. Evol.* 28: 30–37.

Peuker, M. A., Burger, H., Krausch, S., Neumüller, U., Ayasse, M. and Kuppler, J. 2020. Floral traits are associated with the quality but not quantity of heterospecific stigmatic pollen loads. – *BMC Ecol.* 20: 54.

Rathcke, B. 1983. Competition and facilitation among plants for pollination. – *Pollination Biol.* 305: 329.

Revell, L. J. 2024. phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). – *PeerJ* 12: e16505.

Sargent, R. D. and Ackerly, D. D. 2008. Plant–pollinator interactions and the assembly of plant communities. – *Trends Ecol. Evol.* 23: 123–130.

Shibata, A. and Kudo, G. 2020. Floral abundance and bee density affect species-specific foraging patterns of alpine bumble bees. – *Arthropod Plant Interact.* 14: 771–783.

Silveira, F. A. O. et al. 2016. Ecology and evolution of plant diversity in the endangered campo rupestre: a neglected conservation priority. – *Plant Soil* 403: 129–152.

Sritongchuay, T., Wayo, K., Orr, M. C. and Hughes, A. C. 2021. Insufficient native pollinators during artificially induced early flowering decrease yield and long-term economic viability of a tropical fruit crop. – *J. Appl. Ecol.* 58: 80–91.

Streher, N. S., Bergamo, P. J., Ashman, T.-L., Wolowski, M. and Sazima, M. 2020. Effect of heterospecific pollen deposition on pollen tube growth depends on the phylogenetic relatedness between donor and recipient. – *AoB Plants.* 12: plaa016.

Thomson, J. D., Fung, H. F. and Ogilvie, J. E. 2019. Effects of spatial patterning of co-flowering plant species on pollination quantity and purity. – *Ann. Bot.* 123: 303–310.

Tong, Z. Y., Wu, L. Y., Feng, H. H., Zhang, M., Armbruster, W. S., Renner, S. S. and Huang, S. Q. 2023. New calculations indicate that 90% of flowering plant species are animal-pollinated. – *Natl. Sci. Rev.* 10: nwad219.

Tur, C., Sáez, A., Traveset, A. and Aizen, M. A. 2016. Evaluating the effects of pollinator-mediated interactions using pollen transfer networks: evidence of widespread facilitation in south Andean plant communities. – *Ecol. Lett.* 19: 576–586.
Venjakob, C., Klein, A. M., Ebeling, A., Tscharntke, T. and Scher-
ber, C. 2016. Plant diversity increases spatio-temporal niche
complementarity in plant-pollinator interactions. – Ecol. Evol.
6: 2249–2261.

Wei, N., Kaczorowski, R. L., Arceo-Gómez, G., O'Neill, E. M.,
Hayes, R. A. and Ashman, T. L. 2021. Pollinators contribute

to the maintenance of flowering plant diversity. – Nature 597:
688–692.

Ye, Z. M., Jin, X. F., He, Y. D., Cao, Y., Zou, Y., Wang, Q. F., Travel-
set, A., Bergamo, P. J. and Yang, C. F. 2023. The interplay between
scale, pollination niche and floral attractiveness on density-depend-
ent plant-pollinator interactions. – Oecologia 203: 193–204.