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ARTICLE
Pollinator type strongly impacts gene flow within
and among plant populations for six Neotropical species
Diana Gamba | Nathan Muchhala
Department of Biology, University of
Missouri at Saint Louis, Saint Louis,
Missouri, USA
Correspondence
Diana Gamba
Email: dgamba333@gmail.com
Present address
Diana Gamba, Department of Biology,
The Pennsylvania State University,
University Park, Pennsylvania, USA.
Funding information
American Society of Plant Taxonomists;
Whitney R. Harris World Ecology Center
Handling Editor: Ian MacGregor-Fors
Abstract
Animal pollinators directly affect plant gene flow by transferring pollen grains
between individuals. Pollinators with restricted mobility are predicted to limit
gene flow within and among populations, whereas pollinators that fly longer
distances are likely to promote genetic cohesion. These predictions, however,
remain poorly tested. We examined population genetic structure and fine-scale
spatial genetic structure (FSGS) in six perennial understory angiosperms
in Andean cloud forests of northwestern Ecuador. Species belong to three
families (Gesneriaceae, Melastomataceae, and Rubiaceae), and within each
family we paired one insect-pollinated with one hummingbird-pollinated
species, predicting that insect-pollinated species have greater population
differentiation (as quantified with the F
ST
statistic) and stronger FSGS
(as quantified with the S
P
statistic) than hummingbird-pollinated species. We
confirmed putative pollinators through a literature review and fieldwork, and
inferred population genetic parameters with a genome-wide genotyping
approach. In two of the three species pairs, insect-pollinated species had much
greater (>2-fold) population-level genetic differentiation and correspondingly
steeper declines in fine-scale genetic relatedness. In the Gesneriaceae pair,
however, F
ST
and S
P
values were similar between species and to those of the
other hummingbird-pollinated plants. In this pair, the insect pollinators are
euglossine bees (as opposed to small bees and flies in the other pairs), which
are thought to forage over large areas, and therefore may provide similar levels
of gene flow as hummingbirds. Overall, our results shed light on how different
animal pollination modes influence the spatial scale of plant gene flow,
suggesting that small insects strongly decrease genetic cohesion.
KEYWORDS
2b-RAD sequencing, Andean cloud forest understory, fine-scale spatial genetic structure,
hummingbird pollination, insect pollination, neotropical plants, population genetic structure
INTRODUCTION
Understanding how plant mutualists influence spatial
patterns of genetic diversity is central to plant biology,
especially in the present scenario of biodiversity decline
due to human-accelerated environmental change (Aguilar
et al., 2008,2019; Dick et al., 2008; Hardy et al., 2006).
Animal pollinators directly affect gene flow within and
Received: 10 December 2021 Revised: 13 June 2022 Accepted: 23 June 2022
DOI: 10.1002/ecy.3845
Ecology. 2022;e3845. https://onlinelibrary.wiley.com/r/ecy © 2022 The Ecological Society of America. 1of12
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among flowering plant populations via the transfer of pollen
grains (Hamrick et al., 1992;Loveless&Hamrick,1984).
Early reviews on patterns of genetic structure in plants
foundthatwindtendstohomogenizeplantgene
pools, whereas animal pollination is associated with higher
population genetic differentiation (Duminil et al., 2007;
Hamrick & Godt, 1996)aswellasstrongerfine-scale
spatial genetic structure (FSGS; i.e., the nonrandom spatial
distribution of closely related individuals) (Dick et al., 2008;
Gelmi-Candusso et al., 2017). However, those studies
lumped together all animals, overlooking the effect of differ-
ent pollinators on gene flow dynamics within and among
plant populations. More recently, global reviews on the
effects of various factors on population genetic differentia-
tion for 337 plant species (Gamba & Muchhala, 2020)and
on the strength of FSGS for 147 plant species (Gamba and
Muchhala, unpublished manuscript) found that plants
pollinated by small insects have a greater genetic structure
than plants pollinated by large insects and vertebrates.
These findings are consistent with differences in pollen
dispersal among different types of animal pollinators.
Pollen dispersal ultimately depends on the foraging
behavior and pollen carryover capacity of pollinators
(Levin, 1979). Pollinators with large foraging areas can
carry pollen long distances, potentially enhancing gene
flow within and among plant populations, while pollina-
tors with local foraging behavior may reduce gene flow.
This trend has been predicted in seminal reviews
(Levin, 1981; Loveless & Hamrick, 1984), and supported
in empirical studies of temperate and subtropical plants
(Breed et al., 2015; Kramer et al., 2011; Linhart
et al., 1987; Linhart & Grant, 1996), and in a recent study
in a set of neotropical Merianieae (Dellinger et al., 2022).
Studies of pollinator movement show that small
insects, such as flies, solitary bees, and small beetles,
generally forage in relatively small areas, visiting most
flowers in a single plant and then moving to nearby
plants (Campbell, 1985; Escaravage & Wagner, 2004;
Hasegawa et al., 2015). Conversely, large insects such as
moths, butterflies, and large bees have larger foraging
areas, frequently associated with traplining behavior
(i.e., repeatedly visiting a sequence of flowers over several
locations) (Levin, 1979; Murawski & Gilbert, 1986;Rhodes
et al., 2017;Schmitt,1980). Similarly, volant vertebrates
such as nonterritorial hummingbirds and bats also follow a
traplining foraging behavior (Fleming, 1982; Lemke, 1984,
1985; Tello-Ramos et al., 2015), potentially covering
even greater distances than large insects (Campbell &
Dooley, 1992; Castellanos et al., 2003; Linhart, 1973;
Melampy, 1987;Sahley,2001; Serrano-Serrano et al., 2017;
Webb & Bawa, 1983), and flying across fragmented habitats
(Breed et al., 2015; Byrne et al., 2007;Hadley&Betts,2009;
Krauss et al., 2017;Levin,1979;Machadoetal.,1998;
Sahley, 2001; Solís-Hern
andez & Fuchs, 2019; Southerton
et al., 2004). Therefore, pollination by volant vertebrates
should increase the spatial scale of intraspecific gene flow,
resulting in larger genetic plant neighborhoods (sensu
Webb, 1984,Wright,1946), relative to pollination by insects
(Bezemer et al., 2016;Karronetal.,1995; Krauss, 2000;
Krauss et al., 2009).
In this study we examined if, relative to hummingbird
pollination, insect pollination is in fact associated with:
(1) greater genetic differentiation between populations,
and (2) stronger FSGS structure within populations. We
focused on six frequent and locally abundant perennial
understory angiosperms in the Andean cloud forest of
northwestern Ecuador, a highly diverse but threatened
ecosystem. Species belong to three families, and within
each family we paired one insect-pollinated species
(euglossine bees, or small buzzing bees, or hoverflies and
wasps) with one species predominantly pollinated by
traplining hummingbirds (Table 1). All six focal species
share a similar geographic range, are putatively
outcrossing, and mostly similar in their seed dispersal
(see Methods: Study species and pollinators). Therefore,
we expect that any trend of variation in population
TABLE 1 Characteristics of studied species and sites where they were sampled.
Species Growth form Pollinators (source) Fruit type Sites
Drymonia brochidodroma (Gesneriaceae) Herbaceous Euglossine bees (this study) Fleshy capsule SL, T
Drymonia tenuis (Gesneriaceae) Subshrub Traplining hummingbirds
a
Fleshy capsule SL, P, B
Miconia rubescens (Melastomataceae) Shrub Small buzzing bees
b
Berry SL, P, B
Meriania tomentosa (Melastomataceae) Shrub Traplining hummingbirds/bats
a,c
Dry capsule SL, P, B
Notopleura longipedunculoides (Rubiaceae) Subshrub Wasps/flies/bees (this study) Berry SL, P, B
Palicourea demissa (Rubiaceae) Shrub Traplining hummingbirds
a
Berry SL, B
Abbreviations: B, Bellavista; P, El Pahuma; SL, Santa Lucía; T: Las T
angaras.
a
Weinstein & Graham, 2017.
b
Renner, 1989; Gamba & Almeda, 2014.
c
Muchhala & Jarrin-V, 2002; Dellinger et al., 2019.
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genetic differentiation and FSGS across species will be
due primarily to pollination mode. We confirmed puta-
tive pollinators through fieldwork, and we used a
genome-wide genotyping approach to obtain data for esti-
mates of genetic structure.
METHODS
Study sites
We performed this study in Santa Lucía (0.12 N, 78.6 W),
El Pahuma (0.02 N, 78.6 W), Bellavista (0.01 S, 78.7 W),
and Las T
angaras (0.08 S, 78.8 W), four private reserves
located on the northwestern slope of the Andean cordillera
of Ecuador, in the province of Pichincha ~40 km northwest
of Quito. Sites are 5–23 km apart, historically connected by
continuous forest that is now selectively logged, composed
of secondary and primary cloud forest ranging from 1800
to 2500 m in elevation, and part of the southern end of the
“biogeographic Choco”(Mordecai et al., 2009). Because
they are nearby and similar in elevation, they share many
species, yet the distance between them potentially imposes
a physical barrier for the movement of pollinators, making
them ideal for studying the effect of different animal polli-
nators on plant gene flow.
Study species and pollinators
To select our focal species, we compiled a list of species
occurring at all sites using the Tropicos.org database of the
Missouri Botanical Garden and visited the sites to observe
abundances. We selected six perennial understory angio-
sperms from three families, based on their high abundance
and frequency along transects of the reserves. We chose one
insect-pollinated and one hummingbird-pollinated species
per family, including Drymonia brochidodroma Wiehler
and Drymonia tenuis (Benth.) J.L.Clark (Gesneriaceae),
Miconia rubescens (Triana) Gamba & Almeda and
Meriania tomentosa (Cogn.) Wurdack (Melastomataceae),
and Notopleura longipedunculoides (C.M.Taylor) C.M.Taylor
and Palicourea demissa Standl. (Rubiaceae; with the
hummingbird-pollinated species listed second in each case).
Pairing by family allowed us to account for phylogenetic
autocorrelation when comparing F
ST
and S
P
values between
insect-pollinated vs hummingbird-pollinated plants, although
we note that pairs differed in how closely related they
were to each other: the Gesneriaceae species pair was the
most closely related (same genus: Drymonia), followed by
the Rubiaceae species pair (same tribe: Palicoureeae), and
last by the Melastomataceae species pair (same subfamily:
Melastomatoideae).
We obtained information on pollination mode from
peer-reviewed literature (Clark et al., 2015; Dellinger
et al., 2019; Gamba & Almeda, 2014;Muchhala&
Jarrin-V, 2002;Renner,1989; Weinstein & Graham, 2017),
and by videotaping plants in the field (Table 1). Specifically,
for species with little information on pollination mode
(D. brochidodroma and N. longipedunculoides), we con-
firmed putative pollinators by videotaping flowers with four
high-definition Sony digital camcorders for 4 days at each
site. Cameras simultaneously videotaped four individuals
per day (one species per day, eight individuals per species
per site). Flowers were videotaped in the morning (6:30 AM
to 11:30 AM) and in the afternoon (01:30 PM to 06:30 PM).
Among hummingbird-pollinated species, M. tomentosa is
also pollinated by nectar bats (Muchhala & Jarrin-V, 2002)
and, along with D. tenuis and P. demissa, can also be
visited by territorial hummingbirds (Dellinger et al., 2019,
Weinstein & Graham, 2017).
Based on our field observations, the spatial distribution
of all six species appeared widespread and consistent within
sites, with occasional clusters of conspecifics. Geographic
distributions are also similar; all species occur along western
Ecuador, with our study sites near the center of their ranges
(Global Biodiversity Information Facility). Little information
is known about their seed dispersal and floral biology,
although fruit and floral morphology and previous field
studies in closely related species gave some clues. Most study
species have fleshy fruits (Table 1)thatarepresumably
consumed by understory birds, as reported for M. rubescens
(Kessler-Rios & Kattan, 2012) and closely related species
(Loiselle & Blake, 1999), as well as for Psychotria,which
is related to Palicourea and similar in habit and habitats
(Loiselle et al., 1995;Loiselle&Blake,1993;Theim
et al., 2014). Drymonia have fleshy capsules, often termed
“display-capsules”in understory Gesneriaceae, because of
their presumed role in animal attraction (Clark et al., 2012).
The limited reports suggest these are also consumed by
understory birds, as well as frugivorous bats and monkeys
(Wiehler, 1983). The capsular fruits of M. tomentosa
probably have wind- or gravity-dispersed seeds, as in many
understory Melastomataceaewiththesametypeoffruit
(Renner, 1989), potentially making this species the most
limited in seed dispersal. All six species have mechanisms to
reduce selfing, either via marked herkogamy (i.e., spatial
separation of stigma and anthers via style elongation) in the
Melastomataceae (Renner, 1989), protandry (i.e., temporal
separation of male and female phases, with anthers
releasing pollen and dying-off before stigma is receptive)
in the Gesneriaceae (Clark et al., 2012;Wiehler,1983), or
distyly (i.e., polymorphism in style length within a popula-
tion in which flowers in one individual are monomorphic)
in the Rubiaceae (Bawa & Beach, 1983). Self-incompatibility
(via intramorph incompatibility) is common in the
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Rubiaceae (Bawa & Beach, 1983), but less clear in
the Gesneriaceae and Melastomataceae, where both self-
incompatibility and self-compatibility have been docum-
ented (Ramírez-Aguirre et al., 2016; Renner, 1989).
Molecular work and genotyping
We collected leaf tissue and extracted DNA from
20 individuals per species from each of the three study
sites (please refer to Table 1for sampled sites per spe-
cies). We largely followed available trails in the reserves,
making sure sampled individuals were at least 20 m apart
from each other, and taking GPS coordinates for each.
We used a genome-wide restriction site-associated DNA
sequencing technique termed 2b-RAD (Wang et al., 2012)
to build loci de novo (Catchen et al., 2013) and obtain
100–1000 of unlinked SNPs (please refer to Appendix S1:
Sections S1 and S2). For estimating population genetic
parameters, we removed ~20% of total individuals
genotyped due to >50% missing data (2–17 individuals
per species; Appendix S1: Table S1). Please refer to
Gamba and Muchhala (2022) for all geographic and
genetic data.
Inference of population genetic parameters
We used the program GenoDive v3.0 (Meirmans & Van
Tienderen, 2004) to calculate genetic diversity statistics
for each species. We assessed population genetic struc-
ture using the F-statistics derived from an Analysis of
Molecular Variance (AMOVA; Excoffier et al., 1992).
AMOVA determines the proportion of genetic variance
partitioned within individuals, among individuals within
subpopulations, and among subpopulations. Related
F-statistics were obtained with an infinite allele model;
therefore, they are equivalent to G-statistics (Nei, 1973;
Nei & Chesser, 1983). These include F
IT
(the mean
reduction in heterozygosity of an individual relative to the
total population), F
IS
(the inbreeding coefficient among
individuals within sites), and F
ST
(the global genetic
differentiation among sampled sites). The statistical signifi-
cance of these diversity statistics was assessed using 1000
random permutations of the data, while their standard
deviations were obtained by jackknifing over loci.
To visualize population genetic structure for each
species, we used principal component analyses (PCA).
After SNP calling and filtering, we obtained a VCF for
each species with the final set of SNPs from the program
“populations”on our pipeline (Appendix S1: Section S2).
We then used the R program (Core Team, 2018)
SNPRelate (Zheng et al., 2012) to convert the VCF to a
GDS file with snpgdsVCF2GDS and to compute PCA on
each species’SNP set with snpgdsPCA.
Inference of fine-scale spatial genetic
structure
We evaluated FSGS for each species via spatial auto-
correlation analyses at the individual level (Vekemans &
Hardy, 2004) using the program SPAGeDi v.1.3a (Hardy &
Vekemans, 2002). We first transformed individuals’
decimal degree coordinates into the Universal Transverse
Mercator coordinate system, which is compatible with
the SPAGeDi version we used. We then assessed genetic
relatedness between all pairs of individuals iand jwith
Nason’s kinship coefficient, F
ij
(Loiselle et al., 1995). We
specified five distance intervals for each species and
allowed the program to define their maximal distance such
that the number of pairwise comparisons within each
interval was kept approximately constant. F
ij
values were
regressed on the natural logarithm of the spatial distance
separating pairs of individuals, ln(d
ij
), to quantify regres-
sion slopes, b. To test for significant fine-scale spatial
structure, spatial positions of individuals were permuted
1000 times to obtain a frequency distribution of bunder
the null hypothesis that F
ij
and ln(d
ij
) are not correlated.
We quantified the strength of FSGS with the S
P
statistic
(Vekemans & Hardy, 2004), which is calculated as
b/(1 F
1
), where F
1
is the mean F
ij
between all pairs of
individuals in the first distance interval containing nearest
neighbors (< ~1 km for all species). The S
P
statistic mainly
depends on the slope of the kinship–distance curve,
allowing direct comparisons of FSGS among species
(Vekemans & Hardy, 2004). Standard errors of all
FSGS statistics were obtained by jackknifing over loci. To
visualize FSGS, we plotted the mean F
ij
at each distance
interval over the five distance intervals for each species.
RESULTS
Pollinators
We recorded, in total, 10 individuals and 30 h (i.e.,
~3 h/individual) for D. brochidodroma, and 12 individuals
and 35 h (i.e., ~2.9 h/individual) for N. longipedunculoides.
From these videos, we observed that D. brochidodroma was
exclusively visited by euglossine bees (also please refer to
Clark et al., 2015), with five bee visits lasting ~10 s each,
whereas N. longipeduncoloides was visited by wasps,
hoverflies, and small bees. We recorded 18 wasp visits last-
ing ~60 s each, 10 hoverfly visits ~30 s each, and five bees
visits ~15 s each. Although we did not record pollinators for
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M. rubescens, their anther morphology and small
flowers conformed to the buzz-pollination syndrome
common to this genus, adapting them to small buzzing
bees that shake anthers to release pollen from
tiny apical pores (Brito et al., 2016). Drymonia tenuis,
M. tomentosa,andP. demissa are primarily pollinated
by traplining hummingbirds; for a complete list please
refer to Weinstein and Graham (2017).
Filtered genetic datasets
After SNP calling and quality control using different
filtering procedures, we obtained a mean of 2,797,308
SNP loci per species (1,091,949 SD; range:
879,138–4,151,836), with average coverage ranging from
14.0–95.1 read depth per locus across species
(Appendix S1: Table S1). After removing individuals with
>50% missing data, final sample sizes of individuals per
species per study site ranged from 8–18 (mean =
13 3 SD), and the number of variant loci ranged from
1044–4907 (mean =2699 1427 SD) across species, with
missing data across species ranging from 24%–38%
(mean =33% 5 SD) (Appendix S1: Tables S2 and S3).
Gene diversity was similar across species; total
expected heterozygosity (H
T
) ranged from 0.21–0.25
(mean =0.23 0.02; Appendix S1: Table S2) and mean
expected heterozygosity within sites (H
S
) ranged from
0.17–0.26 (mean =0.22 0.02). Additionally, all species
showed statistically significant levels of inbreeding, as
indicated by significant G
IS
values depending on whether
these were pooled across sites (mean =0.30 0.14 SD;
Appendix S1: Table S2) or analyzed separately by site
(mean =0.32 0.16 SD; Appendix S1: Table S3).
Population-level genetic structure
AMOVA results revealed that, in all species, most of the
genetic diversity resides within populations/sites, whereas
less genetic diversity resides among sites (Appendix S1:
Table S4). AMOVA F
IT
showed that for most species a
large proportion of individuals across study sites were out
of Hardy–Weinberg equilibrium, and this was likely to be
due to inbreeding. In fact, AMOVA F
IS
was significant for
all species, congruent with our G
IS
estimates above, and
confirming that there was substantial inbreeding within
sites across studied species. Furthermore, AMOVA F
ST
was variable (range =0.03–0.21, average =0.10 0.06)
but significant for all species, demonstrating considerable
genetic differentiation among study sites (Table 2).
Regarding pollination systems, for two of the three pairs of
species (Melastomataceae and Rubiaceae), F
ST
values were
more than twice as high for the insect-pollinated species,
while in the final pair (Gesneriaceae), F
ST
values were
comparable for the insect- and hummingbird-pollinated
species (Table 2,Figure1). A PCA of filtered SNPs showed
some separation of individuals following their site of
origin (Appendix S1: Figure S1), but the percentage varia-
tion explained by PC1 and PC2 was generally <15%,
suggesting admixture between sites. In M. rubescens and
N. longipedunculoides, however, PC1 and PC2 explained
~20 and 35%, respectively, of the SNP variation, in accor-
dance with their higher F
ST
values.
Fine-scale spatial genetic structure
FSGS was significant for all studied species, in that
regression slopes bof pairwise kinship coefficients on
the natural logarithm of spatial distance were always
significantly negative (Table 3). The extent of FSGS as
quantified with the S
P
statistic varied by an order of
magnitude across species, ranging from 0.009 to 0.089
(mean =0.04 0.03 SD). This variation is evident in our
FSGS visualizations (Figure 2;AppendixS1:TablesS5–S10),
which showed that species pollinated by insects tended to
have steeper average kinship–distance slopes (Figure 2a,c,e)
than species pollinated by hummingbirds (Figure 2 b,d,f).
Given that standard errors associated with each average F
ij
are vanishingly small (Appendix S1: Tables S5–S10), they
are not observable in Figure 2.S
P
values were higher for all
insect-pollinated species relative to hummingbird-pollinated
ones (average =0.054 0.03 SD vs. 0.017 0.01 SD).
Among species pairs, this pattern was most pronounced in
the Melastomataceae and Rubiaceae pairs, with little differ-
ence in the Gesneriaceae pair (Table 3,Figure1).
DISCUSSION
The contrasting effect of different pollinators on plant
gene flow has remained largely unexplored, especially
in the Neotropics (Wessinger, 2021, but please refer
to Dellinger et al., 2022). Our study highlights that
pollinator type can have a strong impact on genetic
structure: among our species pairs, two of the three species
pollinated by insects had greater levels of population
genetic differentiation and stronger FSGS than their
hummingbird-pollinated counterparts (Tables 2and 3,
Figure 1). Our findings support the idea that pollinator
movement during foraging affects the spatial scale of
intraspecific plant gene flow, with the limited movement
of small insects restricting gene flow within and among
populations, and the traplining behavior of hummingbirds
promoting genetic cohesion.
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Our chosen study species allowed us to control for
other factors that might impact plant population
genetic structure and FSGS, increasing the probability
that differences in F
ST
and S
P
values are in fact due
directly to animal pollination mode rather than a
confounding variable. For example, pairing species
within families allowed us to control for phylogenetic
autocorrelation in our dataset. Furthermore, all
species belong to cloud forest understory sites inside
the southern end of the Choco Andean corridor
TABLE 2 Estimates of population genetic structure for each studied species.
Species Ntotal Nloci AMOVA F
IT
(SE) AMOVA F
IS
(SE) AMOVA F
ST
(SE)
Drymonia brochidodroma 35 4907 0.42 (0.007) 0.37 (0.007) 0.08 (0.004)
Drymonia tenuis 29 1044 0.56 (0.014) 0.51 (0.015) 0.10 (0.010)
Miconia rubescens 34 2171 0.50 (0.009) 0.43 (0.010) 0.13 (0.005)
Meriania tomentosa 32 3883 0.29 (0.008) 0.24 (0.008) 0.06 (0.003)
Notopleura longipedunculoides 41 1815 0.35 (0.013) 0.17 (0.014) 0.21 (0.008)
Palicourea demissa 30 2376 0.22 (0.012) 0.19 (0.012) 0.03 (0.003)
Note:Ntotal, number of genotyped individuals in the final genetic dataset; Nloci, number of variant loci in the final genetic dataset; AMOVA F
IT
represents
the deviation from Hardy–Weinberg equilibrium within individuals relative to the expected heterozygosity in the total population; AMOVA F
IS
represents the
inbreeding coefficient among individuals within sites; AMOVA F
ST
represents the global genetic differentiation among sampled sites. Significance of statistics
(F
IS
and F
ST
) is denoted in bold (p=0.001) and is based on 1000 permutations of the data. The insect-pollinated species is listed first for each pair.
(a) (b)
FIGURE 1 Genetic parameters evaluated in three insect-pollinated vs three hummingbird-pollinated plants paired by taxonomic
family, corresponding to (a) AMOVA F
ST
values and (b) S
P
values. Error bars surrounding dots correspond to standard errors obtained
through jackknifing over loci. Lines connect species pairs by family: solid line for the Rubiaceae, dashed line for the Melastomataceae, and
dotted line for the Gesneriaceae.
TABLE 3 Estimates of FSGS parameters for each studied species.
Species Npairs F
1
(SE) bln(distance) S
P
(SE)
Drymonia brochidodroma 595 0.053 (0.003) 0.024 (0.001) 0.025 (0.001)
Drymonia tenuis 406 0.044 (0.007) 0.021 (0.002) 0.022 (0.002)
Miconia rubescens 561 0.105 (0.005) 0.043 (0.002) 0.048 (0.002)
Meriania tomentosa 496 0.051 (0.002) 0.018 (0.001) 0.019 (0.001)
Notopleura longipedunculoides 820 0.180 (0.006) 0.073 (0.003) 0.089 (0.003)
Palicourea demissa 435 0.018 (0.002) 0.009 (0.001) 0.009 (0.001)
Note:Npairs, number of comparisons between all pairs of conspecific individuals; F
1
, kinship coefficient between individuals in the first distance interval
(separated by <1 km); bln(distance), slope of the regression of kinship coefficients on the natural logarithm of spatial distance; S
P
, intensity of FSGS for each
species. Standard errors (SE) were obtained through jackknifing over loci. Significance of parameters (F
1
and b) is denoted in bold (p< 0.01) and is based on
1000 permutations of individual locations. The insect-pollinated species is listed first for each pair.
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(Mordecai et al., 2009) that are relatively well
connected by a continuous corridor of forests.
Therefore, pollinator movement between sites for all
speciesshouldbeconstrainedbythesamegeographic
barriers. Similarly, the geographic distribution of our
study species greatly overlaps, especially in Ecuador
and Colombia, and study sites are always well within
their distributions (rather than at the edges, which
might affect genetic structure; Global Biodiversity
Information Facility). Miconia rubescens has the
widest distribution, Notopleura longipedunculoides
extends to Panama, Meriania tomentosa and
Palicourea demissa to Peru (the former also to
Venezuela), whereas the two Drymonia are restricted
to Ecuador and Colombia. Seed dispersal across spe-
cies is likely to be similar; seeds either fall under
mother plants (Noé, E. Toapanta, personal
observation, March 2016) or are predominantly con-
sumed by understory frugivores (observed by birders
and guides in the study sites). Additionally, most species
pairs have the same type of fruit: D. brochidodroma and
D. tenuis have fleshy capsules, and N. longipedunculoides
and P. demissa have berries. The exception is the
Melastomataceae pair, in which M. tomentosa has dry
capsules and M. rubescens has fleshy berries. We would
expect capsular seeds to be dispersal limited and there-
fore correspond with higher F
ST
and S
P
values than a spe-
cies with fleshy berries, which is likely to be dispersed by
animals. Our data instead found that M. tomentosa has
lower F
ST
and S
P
values than M. rubescens, suggesting
that vertebrate pollination (by hummingbirds and bats)
in this species overrides any dispersal limitation
imposed by the dry capsules. Furthermore, all species
exhibited occasional clusters of individuals in our
FIGURE 2 Average kinship–ln(distance) curves of each studied species. Filled symbols represent significant (p< 0.05) average kinship
coefficient values based on 1000 permutations of individual spatial locations among all individuals. Open symbols represent non-significant
(p> 0.05) average kinship coefficient values. Dotted lines correspond to linear regressions. For associated standard errors of average F
ij
at each
distance interval refer to Appendix S1: Tables S5–S10. (a) Drymonia brochidodroma.(b)Drymonia tenuis.(c)Miconia rubescens.(d)Meriania
tomentosa.(e)Notopleura longipedunculoides.(f)Palicourea demissa. Photographs by Diana Gamba.
ECOLOGY 7of12
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study sites. In fleshy fruited plants, this clustering is
often associated with the foraging behavior of under-
story birds that aggregate around preferred food
sources (Kessler-Rios & Kattan, 2012;Loiselle&
Blake, 1993;Smith,2001) therefore potentially limiting
gene flow via seed dispersal.
Our study species have various mechanisms to
reduce autogamy (via protandry, herkogamy, or distyly;
see Methods: Study species and pollinators), yet they all
exhibited significant levels of inbreeding as evidenced by
their F
IS
values (Table 2). This could be due to spatial
distributions and mating between close relatives, or to
pollinators transferring pollen between flowers on the
same plant (geitonogamy), as all species typically have
multiple flowers open at any given time. Interestingly,
the Rubiaceae species showed the lowest F
IS
values,
which makes sense given that the distyly and
intramorph incompatibility exhibited by these species
(Bawa & Beach, 1983) is likely to be a more effective
mechanism at preventing geitonogamy than protandry
or herkogamy, given that individual plants are either
short or long styled (i.e., all flowers on a plant have the
same morphology). Observed differences in inbreeding
levels, however, do not seem to underlie the differences
we found in population genetic differentiation or strength
of FSGS. Inbreeding can increase genetic structure by
increasing genetic drift (Duminil et al., 2007; Vekemans &
Hardy, 2004) however, among our focal species,
inbreeding coefficients (AMOVA F
IS
in Table 2)werenot
correlated with AMOVA F
ST
(r=0.06, t=0.11, p=0.9)
nor with S
P
(r=0.25, t=0.52, p=0.6).
We note that differences in F
ST
and S
P
values were
more pronounced between the Rubiaceae species pair
(7-fold and 10-fold, respectively), followed by the
Melastomataceae pair (2.2-fold and 2.5-fold, respec-
tively), and last by the Gesneriaceae pair (almost equiv-
alent values; Tables 2and 3,Figure1). Notopleura
longipedunculoides (Rubiaceae) is largely pollinated by
tinywaspsandhoverfliesthatprobemostflowersin
the same individual and stay among nearby plants (D.
Gamba, personal observation, January 2018), consistent with
it having the greatest observed F
ST
and S
P
values. Miconia
rubescens (Melastomataceae) is pollinatedbyrelativelysmall
pollen-collecting bees (e.g., Melipona and Trigona;
Renner, 1989), consistent with the intermediate F
ST
and S
P
values. Finally, D. brochidodroma (Gesneriaceae) is polli-
nated by euglossine bees, which are larger and have been
reported to fly long distances (Janzen, 1971;L
opez-Uribe
et al., 2008), in line with D. brochidodroma having the
smallest F
ST
and S
P
values among our insect-pollinated
plants. Therefore, differences between insect pollinators may
explain this pattern. Among our vertebrate-pollinated
species, P. demissa is visited by ~15 hummingbird species,
M. tomentosa is visited by ~eight hummingbird species and
by nectar bats (Muchhala & Jarrin-V, 2002), and D. tenuis is
visited by ~seven hummingbird species (Weinstein &
Graham, 2017). Some of these hummingbirds are territorial,
but most are traplining (Weinstein & Graham, 2017), there-
fore the latter should override the potential isolating effect of
theformer.ThefactthatthetwoDrymonia species had such
similar F
ST
and S
P
values suggests that euglossine bees and
hummingbirds may be similar in their pollen dispersal abil-
ity. Overall, our genetic structure results are also consistent
with direct measures of pollen dispersal based on paternity
analyses, in that bats and hummingbirds can transport pol-
len for several kilometers, large insects such as euglossine
bees for more than 600 m, while insects smaller than a hon-
eybee rarely transfer pollen more than 300 m (Dick
et al., 2008;Webb&Bawa,1983).
We might also expect different vertebrates to vary in
pollen dispersal ability in the same way that insects
do. For instance, foraging behavior among humming-
birds can strongly impact plant gene flow (Cuevas
et al., 2018;Murawski&Gilbert,1986; Schmidt-Lebuhn
et al., 2019), as evidenced by the fact that territorial
hummingbirds move pollen much shorter distances than
traplining hummingbirds (Betts et al., 2015; Ohashi &
Thomson, 2009; Wolowski et al., 2013). Hummingbirds
and bats may also differ, as the latter have been
found to carry pollen more efficiently (Muchhala &
Thomson, 2010) and to longer distances than humming-
birds (Lemke, 1984,1985; Tello-Ramos et al., 2015). We
encourage future work to look more in depth at how
plant gene flow is affected by behavioral differences
within pollinator guilds. For example, foraging ranges of
pollinators might predict the spatial scale of plant gene
flow, but this could be complicated by behaviors such as
grooming or differences in pollen retention on fur,
feathers, and insect hairs. A larger sample with details
on pollinator behavior would clarify the effects of these
differences on plant population structure.
Our study provides new evidence on the contrasting
effect that different animal pollinators can have on the
spatial scale of intraspecific plant gene flow. We found
that plants pollinated by small insects have considerably
higher population genetic differentiation and stronger
FSGS than hummingbird-pollinated plants. Our results
also suggest that large insects, such as euglossine bees,
can connect plant populations as effectively as traplining
hummingbirds. Therefore, the effect of different animal
pollinators on neotropical plant gene flow can be signifi-
cantly different at local (within populations) and regional
(among populations) scales (e.g., Dellinger et al., 2022).
Our results are also relevant to conservation efforts,
suggesting that plants pollinated by small insects are
likely to be very susceptible to habitat fragmentation
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(more so than vertebrate-pollinated plants, e.g., Côrtes
et al., 2013), as this can further isolate populations and
result in the loss of genetic variability due to increased
genetic drift (Aguilar et al., 2008,2019). Nevertheless,
focal studies show that plants pollinated by humming-
birds and bats can also experience detrimental effects due
to habitat fragmentation (Hadley et al., 2018; Hadley &
Betts, 2009; Nunes et al., 2017; Wanderley et al., 2020).
Future studies should seek to compare how animal
foraging behavior, animal flying distances, and their
related effect on plant gene flow might be altered due to
anthropogenic disturbance.
AUTHOR CONTRIBUTIONS
Diana Gamba and Nathan Muchhala planned and
designed the research. Diana Gamba collected and ana-
lyzed the data. Diana Gamba wrote the initial draft of
the manuscript. Diana Gamba and Nathan Muchhala
contributed equally to substantial revisions of the
manuscript.
ACKNOWLEDGMENTS
Thanks to Nora Oleas and Paola Peña for help with the
research permit in Ecuador (MAE-DNB-CM-2015-017).
Robert Ricklefs, Christine Edwards, and Carmen
Ulloa provided advice in this study. We also thank field
assistants An Nguyen, Carlos Imery, and Alexander
Lascher-Posner for their valuable help. Thanks to fami-
lies at Santa Lucía, Bellavista, El Pahuma, and Las
T
angaras cloud forest reserves for their conservation
efforts and hospitality. Finally, we thank Amanda
Grusz for help with SPAGeDi analyses. This research
was supported by two graduate research grants from
the Whitney R. Harris World Ecology Center at UMSL
and one research grant from the American Society of
Plant Taxonomists to Diana Gamba.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
DATA AVAILABILITY STATEMENT
Data (Gamba & Muchhala, 2022) available from Dryad:
https://doi.org/10.5061/dryad.rr4xgxdbf.
ORCID
Diana Gamba https://orcid.org/0000-0002-0421-6437
Nathan Muchhala https://orcid.org/0000-0002-4423-
5130
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How to cite this article: Gamba, Diana, and
Nathan Muchhala. 2022. “Pollinator Type Strongly
Impacts Gene Flow Within and among Plant
Populations for Six Neotropical Species.”Ecology
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