R E S E A R C H Open Access
Life-history strategy, resource dispersion
and phylogenetic associations shape
dispersal of a fig wasp community
Vignesh Venkateswaran, Amitabh Shrivastava, Anusha L. K. Kumble and Renee M. Borges
Background: The combined influence of life-history strategy and resource dispersion on dispersal evolution of a
biological community, and by extension, on community assemblage, has received sparse attention. Highly specialized
fig wasp communities are ideal for addressing this question since the life-history strategies that affect their pace of life
and the dispersion of their oviposition resources vary. We compared dispersal capacities of the wasp community of a
widespread tropical fig, Ficus racemosa, by measuring flight durations, somatic lipid content and resting metabolic rates.
Results: Wasp species exhibiting greater flight durations had higher energy reserves and resting metabolic rates.
“Fast”-paced species showed higher dispersal capacities reflecting requirements for rapid resource location within
short adult lifespans. Longer-lived “slow”-paced species exhibited lower dispersal capacities. Most dispersal traits
were negatively related with resource dispersion while their variances were positively related with this variable,
suggesting that resource dispersion selects for dispersal capacity. Dispersal traits exhibited a phylogenetic signal.
Conclusions: Using a combination of phylogeny, trait functionality and community features, we explain how
dispersal traits may have co-evolved with life-history strategiesinfigwaspsandinfluencedapredispositionfor
dispersal. We speculate how processes influencing dispersal trait expression of community members may affect
resource occupancy and community assemblage.
Keywords: Community ecology, Dispersal, Fig wasps, Flight fuel, Insect flight, Life history, Metabolic rate,
The study of dispersal is important since the ability to
disperse can influence the population dynamics of a
species, its global distribution, population genetic structure,
its evolutionary trajectory, and ultimately its membership
within a community . Dispersal capacities have rarely
been studied in the context of life-history strategies. One
approach to understanding the relationships between
life history and dispersal traits in biological communi-
ties has been the conceptual framework of competition/
colonization trade-offs . However, this framework is
helpful only when community members occupy the same
guild and compete for the same resource, and fails to cap-
ture the complexities of community assemblages within
ephemeral microcosms with complicated developmental
Spatial dispersion of resources can select for dispersal
traits of community members . In this paper, we use
the terms dispersion exclusively to characterize spatial
spread of resources and dispersal to indicate the dispersal
capacity of members of a community. When resources
appear in a stochastic fashion in space, temporal differ-
ences in resource availability can change effective spatial
resource dispersion, thereby selecting for corresponding
dispersal abilities in community members [3–5]. Specifically,
with shorter temporal availability of stochastically occurring
resources, the effective spatial resource dispersion increases,
selecting for increased dispersal abilities (Fig. 1). Examples
of such resource availabilities are found in invertebrate
communities that inhabit ephemeral resources such as
dung pats, moss patches, phytotelmata, or the enclosed
microcosms of fig inflorescences called syconia [6–8].
* Correspondence: email@example.com
Centre for Ecological Sciences, Indian Institute of Science, Bangalore 560012,
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Venkateswaran et al. Movement Ecology (2017) 5:25
Although the capacity for dispersal has been recognized
as crucially important for membership in such communities
, no study has attempted to investigate or explain the
differences in dispersal capacities of community members.
Further, the life-history strategy governing dispersal
syndromes in these community members may influence
the predisposition to colonize an ephemeral resource/
habitat, which may in turn dictate community assemblage
Life-history strategies often fall along a fast–slow
continuum [10, 11]. Because a “fast”-paced life history
implies time limitation, it may be associated with higher
dispersal capacities to reach resource destinations [12,
13]. Broad-scale patterns reveal that traits associated with
a“fast”-paced life history (earlier reproductive investment
and reduced lifespans) co-occur with high dispersal abil-
ities in bacteria, cancer cells, vertebrates and particularly in
aerial ectotherms [14–17]. In insects, a fast-paced strategy
is often linked with earlier investment in reproduction as
revealed by their ovigeny index (OI): ratio of number of
mature to total eggs at eclosion [12, 18]. Often, “fast”-
paced life histories are also associated with reduced or
complete lack of feeding during adult dispersal stages, with
a high reliance on the energy capital acquired during previ-
ous life stages [19, 20]. Such co-occurring trait expressions
can be viewed as examples of life-history trait syndromes
associated with dispersal [21, 22].
Adequately quantifying dispersal traits that dictate
dispersal capacity (locomotor capabilities) is essential for
understanding dispersal. Estimating realized dispersal
abilities in small aerial insects (i.e. < 2 mm in length) is
challenging. However, their dispersal capacities can be
assessed by measuring dispersal behavior, somatic energy
reserves and metabolic rates all of which are dispersal-
related life-history traits which, henceforth, we refer to
as dispersal traits [23, 24]. Tethered flight performances
can also be indicative of flight capacities [25–27]. Capital
energy stores (non-polar lipids in the soma) reflect the
amount of fuel for flight post eclosion and are especially
important for insects incapable of feeding during adult
dispersal stages [20, 28]. The mass-specific resting meta-
bolic rate (sRMR) is positively correlated with sustained
activity and reflects dispersal flight capacity [29–33].
Variances associated with dispersal traits against the
background of ecological selection pressures are informative
about the intensity of selection on traits . Therefore,
species tracking stochastically appearing resources that
are ephemeral and therefore more spread out (higher
dispersion) should show higher dispersal trait values and
lower associated trait variances compared to species
Fig. 1 A hypothetical scenario wherein two insect species have oviposition resources on trees that are available for different periods of time
(oviposition window). An insect species that can oviposit only during a small time duration (black circles) will have to locate its resources (trees)
that are few and dispersed and therefore would require high dispersal capacities. However, an insect species that can oviposit over a larger time
duration (dark-grey circles) will locate resources that are more abundant and less dispersed and would require lower dispersal capacities. Thus,
the underlying resource dispersion is governed by the length of the oviposition window (length of time during which the tree serves as a
resource) despite the same spatial distribution of the host trees
Venkateswaran et al. Movement Ecology (2017) 5:25 Page 2 of 11
tracking such resources that are less ephemeral and there-
fore spatially more clumped (lower dispersion). Few studies
have measured two or more dispersal traits simultaneously,
have studied how they correlate with each other across
community members, or have examined the influence of
life-history traits in conjunction with resource dispersion
within the context of a community (however, see  for
A valuable model system within which questions about
dispersal can be addressed in the context of resource
dispersion, life-history strategies and community assem-
blage is the microcosm of the fig syconium, which is a
globular enclosed inflorescence that hosts developing fig
wasps. These communities are comprised of wasp
species obligately dependent on a single host fig (Ficus)
species [6, 36]. They consist of a pollinating and a set
of non-pollinating wasp species that vary in their life-
history traits and oviposition resources within the syconial
microcosm [37, 38]. Female wasps oviposit into the syco-
nium, where their offspring develop and mature into
adults. Wingless males die after mating within syconia;
winged females leave natal syconia and disperse to locate
host plants with syconia suitable for oviposition. Tropical
fig plants produce syconial crops year-round; they usually
exhibit reproductive synchrony (all syconia exhibit the
same ontogenetic stage) within plants . Natal plants
do not bear oviposition resources when adult females
emerge and wasps thus leave their natal plants in search
of suitable syconia for oviposition on other fig plants.
Different wasp species utilize different niches within the
syconium; the earliest arriving wasps use syconium wall
tissues and undifferentiated flowers as egg deposition sites;
wasps (such as the pollinator) that arrive at the pollen-
receptive stage of the syconium oviposit into mature
flowers and wasps that arrive after pollen receptivity
are parasitoid wasps or inquilines on specific larval/
pupal species within the syconium [38, 40]. Each wasp
species oviposits into the syconium within a specific time
period when the syconium is suitable as an oviposition
resource; this is referred to as the oviposition window
[37, 41] (Additional file 1: Figure S1). Shorter oviposition
windows translate to a smaller proportion of plants
bearing suitable syconia of the corresponding ontogenetic
stage in a population (Fig. 1). This causes relatively
increased oviposition-resource dispersion, which could
increase the selection pressure for dispersal and decrease
dispersal trait variances compared to longer windows.
Therefore, the length of the oviposition window is an
important dimension that can affect dispersal abilities.
The fig system therefore provides excellent material for an
interspecific study of fig-associated wasps—this is due to
the differences between wasp species only in the ephem-
erality of the particular oviposition resources appropriate
for each species on the same exploited fig species (Fig. 1).
The context for dispersal in such systems is clear:
female fig wasps, after mating within the syconium,
disperse to locate specific oviposition resources of different
availabilities, offered by a single host species. While wind
dispersal is believed to be important for fig wasps, they
could be additionally propelling their dispersal through
their own dispersal capacities [42–44]. However, there is
no knowledge of the active flight capacities of a fig wasp
community and their contribution to dispersal. Fig wasps
also encounter high mortality during dispersal through
predation and temperature/desiccation effects [44, 45].
Therefore, there is likely a high selection pressure for
successful dispersal in fig wasp communities. Fig wasp
community members also exhibit varying degrees of
evolutionary relatedness, thereby allowing the comparative
examination of dispersal traits within a phylogenetic
context. Fig wasps therefore provide an excellent platform
to understand the combined implications of the pace of life
and ephemeral resource dispersion on dispersal abilities.
We asked the following questions in a fig wasp
1) Do fig wasp species that exhibit a “fast”-paced life-history
strategy express traits associated with enhanced dispersal
capacities (as shown by longer flight durations, higher
somatic lipid content, and greater sRMR) compared to
species with a “slow”-paced strategy?
2) Are dispersal capacities negatively related with
resource availability in time, i.e. lengths of the
oviposition window? Do dispersal trait variances
relate positively with this resource availability?
3) How are trait correlations influenced when
accounting for phylogenetic relatedness among species?
Do dispersal traits exhibit a phylogenetic signal?
The fruiting phenology of the cluster fig Ficus racemosa
shows little seasonality and trees exhibit high degrees of
within-tree reproductive synchrony but population-level
reproductive asynchrony throughout the year [46, 47].
Syconia of Ficus racemosa progress through several
developmental stages: a) the pre-receptive phase, which
constitutes the primordial stages of syconium develop-
ment and the stages before pollen receptivity; b) the
pollen-receptive stage, when pollinators enter syconia to
pollinate flowers; c) the post-pollination stage, or the
developmental stage when wasps and seeds develop in
the syconia; d) the emergence phase, when adult winged
female wasps disperse in search of oviposition sites; e)
the fruit ripening stage when seeds are dispersed; and f )
a gap phase when no syconia are present on the host
plant  (Additional file 1: Figure S1). The life-history
traits, oviposition resource availabilities, trophic position,
Venkateswaran et al. Movement Ecology (2017) 5:25 Page 3 of 11
and niche specialization of all seven wasp species associated
with F. racemosa are known [37, 48]. Hierarchical clustering
methods can be employed to analyze life-history traits as
input variables in order to group species based on similarity
. Using agglomerative hierarchical clustering and K-
means clustering of lifespans and OIs, these wasps can
be categorised into two groups that have fast-paced and
slow-paced life-history strategies (referred to as “fast”
and “slow”respectively); these metrics adequately capture
longevities and reproductive effort over their lifespans
(Additional file 1: Figure S2). Five wasp species (Cerato-
solen fusciceps,Sycophaga stratheni, Sycophaga testacea,
Sycophaga fusca and Sycophaga agraensis) cluster in the
“fast”group (OI = 1, short lifespans, high fecundity, poor
or no feeding abilities) and two wasp species (Apocrypta
westwoodi,Apocrypta species 2) are within the “slow”
group (OI = 0.4, long lifespans, low fecundity, feeding
abilities) . Their oviposition windows are staggered
over syconium ontogeny (Additional file 1: Figure S1).
Oviposition window length values were obtained from
, and vary from (4–19) days in the slow species to
(1–5) days in the fast species.
Syconia in late C-phase, i.e. just prior to wasp emer-
gence, were collected from F. racemosa plants (n= 46)
between 2013 and 2015 at the Indian Institute of Science
Campus, Bangalore, India (12°58′N, 77°35′E). Wasps were
allowed to emerge naturally. If for some reason, wasps did
not naturally exit the fig, the syconia was carefully cut
open to allow the wasps to exit. Dispersal traits were
assessed at the onset of wasp emergence from natal
Dispersal traits: Measurement of flight durations
Freshly emerging fig wasps of each species (~2 mm in
length) were immobilized on a cool surface and, using a
non-toxic synthetic adhesive, were tethered at their thorax
at an angle of ~ 45
under a microscope. Upon tethered-
flight initiation, wasps were positioned to enable intercep-
tion of their beating wings by a laser beam of a custom-built
optical tachometer (Additional file 1: Figure S3a) whose
design was based on . Tethering for flight measurements
were performed between 10:00–12:00 h since wasps fly
during daytime . Wasps were allowed to perform
flight till exhaustion (irreversible immobility). After
recording the data in WAV format using commercially
available sound cards, the signal was subjected to Fast
Fourier Transformation using an audio-processing soft-
ware to produce spectrograms of the recorded signal.
Preliminary analyses of wing-beat frequencies that were
conducted before these experiments using stroboscopic
and high-speed videography analysis had revealed that
the frequency range for wing beats for the different species
ranged from 150 Hz–250 Hz. This was used to discriminate
the wing-beat signal from spectral noise.
Dispersal traits: Energy stores in somatic modules
Wasps show considerable variation in size within and
across species. Freshly killed frozen wasps of each spe-
cies were weighed in groups of five. The lipid content in
eggs and other reproductive organs reflects reproductive
investment . Therefore, all body contents except eggs
and organs associated with reproduction such as venom
sacs and spermathecae were used for somatic lipid
estimation. Five freshly frozen wasps per species were
weighed. Afterwards, the somatic and reproductive
modules were separated (Additional file 1: Figure S3b)
under a drop of phosphate buffer (30 μL) on a glass
slide. Then, the somatic components were homoge-
nized with a cold pestle and transferred to a glass vial.
Lysis buffer (50 μL) was used to wash the pestle. The
non-polar lipid content in the homogenate was estimated
using a modification of Foray’s procedure . Organic
solvents were handled using Hamilton’s syringes only. To
80 μL of homogenate, 1.4 ml of chloroform:methanol (2:1)
solution was added and vortexed for an hour in glass vials.
Then, NaCl (200 μL, 0.88%) was added and the mixture
was vortexed again for 10 min to allow for the thorough
partitioning between aqueous and organic layers . The
aqueous layer along with the interstitial fluff was carefully
siphoned off, leaving behind the organic layer containing
dissolved lipids which was subsequently dried in a vacuum
desiccator; 200 μL of chloroform was added and vortexed
to allow for lipid solubilization. This solution was used to
estimate non-polar lipid content. Tungstosilicic acid
(20 mg, dried overnight at 89 °C) was added to 100 μLof
this solution and vortexed. Then, the mixture was trans-
ferred to a glass insert and centrifuged (9000 rpm, 0 °C,
10 min) to separate the tungstosilicic acid. The chloro-
form containing the non-polar lipids was then transferred
to a vial, dried in a vacuum desiccator, and re-suspended
in 100 μL chloroform. Aliquots of this solution were used
to estimate non-polar lipid content in somatic modules
using the sulpho-phospho-vanillin assay . In a glass
vial, 50 μL of the lipid extract was dried in a vacuum
desiccator. To this, H
(50 μL) was added, vortexed
for 10s and placed in a hot water bath at 90 °C for 2 min.
Then, the reaction was arrested by placing the material on
ice for 5 min and allowing it to attain room temperature
for 5 min after which vanillin reagent (200 μL) was added,
refluxed using a micro-pipette and was allowed to settle
for 5 more min until the development of a stable pink/
magenta color. The contents were transferred to a 96-well
glass plate, and optical density was recorded by a spectro-
photometer at 525 nm. For each reading (representative of
five wasps pooled), two technical replicates were obtained,
and the mean was used to estimate lipid content of the
homogenate. Standard curves were obtained using pure
glyceryl trioleate (Sigma-India) stock solutions. The action
of tungstosilicic acid was confirmed by performing
Venkateswaran et al. Movement Ecology (2017) 5:25 Page 4 of 11
qualitative (thin layer chromatography) and quantitative
(vanillin assay) tests in chloroform mixtures containing
known amounts of glyceryl trioleate (non-polar lipid) and
phosphatidylcholine (polar lipid) with appropriate con-
trols. Ten measurements were performed per species. For
S. stratheni, three wasps were used for every homogenate
owing to their large sizes (sufficient lipid quantities were
present for reliable measurements) and their extreme
rarity. Lipid values were divided by the sum of the weights
of wasps in the pool to obtain values on a per-wasp basis
(μg/unit wet weight).
Dispersal traits: Metabolic rate measurements
Wasps of each species, in groups of 30, were weighed to
obtain wet weights before the estimation of sRMR which
was measured using flow-through respirometry . Briefly,
gas analyzer was calibrated with
known percentages of CO
duced into a 20 ml metabolic chamber (an air-tight
polystyrene container) (Additional file 1: Figure S3c).
The gas from the metabolic chamber was scrubbed
with a dry silica column and passed through two Blue
Balston™air filters before entering the CO
which was regularly calibrated against a standard gas
mixture (538 ppm CO
). For every recording, 30 wasps
per species were placed in three perforated PCR vials
(10 wasps per vial). Vial perforations were adequate to
allow for quick diffusion of gases while small enough to
prevent wasp escape. The vials with wasps were then
placed inside the larger metabolic chamber which was
placed in the dark (wasps reduced movement in the
dark, aiding the measurement of sRMR). Afterwards,
the readings were taken for 30 min with a 15 min baseline
recording before each experiment. Mean CO
subtracted from the average baseline value and was
considered the CO
output (Additional file 1: Figure S3c).
Only for the rare species S. stratheni, one to six wasps
were used to obtain CO
values based on their availabilities
(number of respective samples indicated in parenthesis: 1
wasp (2), two wasps (2), three wasps (1), four wasps (2)
and six wasps (1)).
values were normalized per wasp and to average
wet weight to obtain sRMR values , which are
expressed as ml CO
/g/h. Experiments were conducted
at room temperature (26 °C–28 °C) during the day
(8:00 am–12:00 pm). Fifteen readings were obtained per
wasp species except for S. stratheni for which only eight
readings were possible.
Volume of CO
produced was calculated as the prod-
uct of the flow rate of the gas and the difference
between the fractional concentrations of CO
and exiting the chamber . The respiratory quotient
for all wasps was assumed to be the same, and volume
measured was used directly to make cross-species
sRMR comparisons .
Statistical and phylogenetic analysis
To test for statistical differences in the measured dispersal-
related life-history traits between the ‘fast’and ‘slow’wasp
groups, we performed a Mann-Whitney-Wilcoxon test by
using pooled trait values of all samples for the “fast”and
“slow”species ignoring species identity. We then compared
trait values across species using Kruskal-Wallis tests,
followed by Dunn’s test to conduct multiple pair-wise
comparisons (owing to the underlying non-normality in
the residuals revealed using Shapiro-Wilk tests). The
significance was tested at an adjusted alpha level of p=
0.05 with Bonferroni correction. Next, the trait values
were log-transformed and the medians, median abso-
lute deviations, and the coefficient of variation (CV) for
each trait were calculated. Linear regression analyses
were performed between the log-transformed values of
flight duration with somatic lipid content, sRMR, and
length of the oviposition window. Linear regressions
were also conducted between log-transformed CVs for
each dispersal trait and log-transformed oviposition
window length. The software R (version 3.2.3) was used
for all statistical analyses.
The evolutionary relationships of the F. racemosa
wasp community were inferred from recent published
phylogenetic studies. Chalcidoidea phylogenies have
undergone revisions [57–60]; Ceratosolen is placed
within the Agaonidae, Sycophaga within the Sycophagi-
nae, and Apocrypta within the Sycoryctinae. In order
to infer the evolutionary relationships of the three
wasp genera, we used a recent classification of
Chalcidoidea in which Sycophaginae are more closely
related to Agaonidae than to Sycoryctinae .
Additionally, to infer between-species evolutionary
relationships of species in genus Sycophaga we used
information from . The phylogenetic independence
was accounted for by calculating phylogenetic general-
ized least squares (PGLS) . PGLS values were
calculated using the ape package in R (version 3.2.3).
The PGLS values of flight duration were regressed
against the PGLS values of lipid content and sRMR.
The oviposition window was also considered as a trait
(see ), and the PGLS values for the oviposition window
were calculated and regressed against those of flight
duration. Finally, in order to test for a phylogenetic
signal, Blomberg’sKwas chosen because it is based on
an underlying Brownian evolution of traits and is well
suited for analyses with small sample sizes . The
packages ape,phylosignal,pgls and phytools in R
(version 3.2.3) were used to perform the phylogenetic
and associated statistical tests.
Venkateswaran et al. Movement Ecology (2017) 5:25 Page 5 of 11
Life-history strategies and dispersal traits
Trait values for flight duration, somatic lipid content,
and sRMR for each species are provided in Additional
file 1: Table S1 (supplementary). The “fast”wasp species
had significantly greater flight duration, somatic lipid
content (normalized for wet weight), and sRMR than the
“slow”wasp species (Flight duration: U= 1004, p< 0.001;
Lipid content: U= 846, p< 0.001; Metabolic rate: U= 1616,
p< 0.001, Fig. 2a–c).
Pairwise comparisons of dispersal parameter values using
Dunn’s test (following significant K-W tests at p<0.05)
revealed that flight durations between the two “slow”wasp
species (Apocrypta sp. 2 and A. westwoodi)werenotsignifi-
cantly different from each other (Fig. 2a). The three
fast wasp species, Sycophaga stratheni,S. testacea and
Fig. 2 Measured dispersal trait values for fig wasp species along with corrections for phylogeny. a,band cdenote the flight duration, somatic
lipid content and sRMR values across species respectively. The black dots indicate data points. The triangles indicate outliers. The horizontal lines
in box plots indicate the median. The bottom and top of the box indicate 25th and 75th percentiles respectively while the whiskers indicate
either the maximum value or 1.5 times the interquartile range, whichever is smaller. Alphabets indicate significant differences as detected by
Dunn’s test for multiple comparisons. The horizontal dotted lines indicate the median value for the groups with fast-paced and slow-paced life-history
strategies. d,eand fdepict correlations between the log transformed values of time of flight vs. lipid content, sRMR and oviposition window respectively.
Plotted are the median values of the transformed parameters with their median absolute deviations represented as line-segments. Solid regression lines
indicate associations with the log transformed data, while dashed regression lines indicate the PGLS trends. Species abbreviations: AS-Apocrypta species 2,
AW-Apocrypta westwoodi,SS-Sycophaga stratheni,ST-Sycophaga testacea, SF-Sycophaga fusca,SA-Sycophaga agraensis,CF-Ceratosolen fusciceps.“Fast”and
Venkateswaran et al. Movement Ecology (2017) 5:25 Page 6 of 11
S. agraensis, had significantly higher median flight
S. testacea having the longest flight durations. Syco-
phaga fusca and Ceratosolen fusciceps had intermediate
flight durations, being neither significantly different
from the “slow”wasp species or the other three wasp
species in the “fast”group (Fig. 2a). The two species in
the “slow”group exhibited somatic lipid content values
that were similar to each other. Among the species in the
“fast”group, S. stratheni had the highest lipid content; S.
testacea,S. fusca, and S. agraensis had lipid content values
that were not different from those of S. stratheni or
Apocrypta sp. 2 but were significantly greater than
those of A. westwoodi.Ceratosolen fusciceps had lipid
content significantly lower than that of S. stratheni but
indistinguishable from those of other wasp species (Fig.
Species in the “slow”group had sRMR values that were
mostly indistinguishable from each other but on the whole
had lower sRMR values than species in the “fast”group.
The highest sRMR values were for C. fusciceps and S.
stratheni. Ceratosolen fusciceps expressed an sRMR value
significantly higher than for all other species except S.
stratheni.Sycophaga agraensis and S. fusca expressed simi-
lar sRMR values (statistically indistinguishable). Sycophaga
stratheni exhibited intermediate values but statistically
indistinguishable from either C. fusciceps, S. agraensis or
S. fusca.Sycophaga testacea expressed sRMR values sig-
nificantly lower than those for C. fusciceps or S. stratheni.
Apocrypta westwoodi had significantly lower sRMR values
than those for C. fusciceps,S. agraensis and S. stratheni
Dispersal capacity and resource availability
Time engaged in flight and somatic lipid content were
significantly positively related (Fig. 2d, R
= 0.7, p= 0.01).
sRMR and time engaged in flight were weakly but positively
associated (Fig. 2e, R
=−0.73, p= 0.48). Flight duration
and oviposition window were negatively related as expected
although this was not significant (Fig. 2f, R
p= 0.21). Slope values of the regressions are in Table 1.
Log-transformed CVs for flight durations correlated
positively with log-transformed oviposition window length
as expected although this was not significant (slope = 0.18;
=0.34, p= 0.10, Fig. 3a). Log-transformed CVs for
somatic lipid content correlated positively and signifi-
cantly with log-transformed length of the oviposition
window (slope = 0.28; R
=0.53, p= 0.04, Fig. 3b). The
log-transformed CVs for sRMR, however, were negatively
but weakly correlated with oviposition window length
(slope = −0.08; R
=−0.13, p= 0.62, Fig. 3c).
Phylogenetic relationships and independence of dispersal
The trend directions of the PGLS regressions were the
same as in the linear models for flight durations with
lipid content and with oviposition window length; their
confidence intervals were also comparable (Additional
file 1: Figure S4, Table 1). A phylogenetic signal was ob-
served for flight duration and lipid content, as indicated
by Blomberg’sKvalues, which were greater than 1.0 and
significant (flight duration: Blomberg’sK= 1.56, p= 0.04;
lipid content: Blomberg’sK=1.93,p= 0.0001). Blomberg’s
Kvalue was also close to 1.0 but not significant for meta-
bolic rates (Blomberg’sK=0.99,p=0.152).
Life-history and dispersal traits
Fig wasp species differ in their dispersal capacities.
“Fast”-paced (time-limited) species displayed significantly
higher flight durations, higher somatic lipid content and
higher sRMR values than “slow”-paced (longer-lived)
species. The duration of the oviposition window (resource
availability) was negatively correlated with flight durations.
Trait variances of flight durations and lipid content were
positively correlated with the length of the oviposition
A positive association of flight duration with somatic
lipid content (Fig. 2d) suggests a functional role for lipids
in aiding flight as observed in other insects . The
higher median sRMR values for the “fast”relative to the
“slow”wasp species is suggestive of their association with
higher dispersal capacities [24, 63]. sRMR values measured
are comparable to those published for insects of similar
sizes . High sRMR values can lead to the increased ac-
cumulation of reactive oxygen species (ROS), thereby de-
creasing species lifespans [33, 55]; indeed, sRMR values
and lifespan are negatively correlated in many insect
orders [55, 64]. The highest sRMR values were exhibited
by C. fusciceps and S. stratheni, species that have the
Table 1 Regression parameters for linear regressions and phylogenetic generalized least square (PGLS) models
Linear model Phylogenetic generalized least squares
Intercept Slope tvalue Pvalue 95% confidence
Intercept Slope tvalue Pvalue 95% confidence
Flight duration ~ lipid content 0.63 1.79 3.88 0.01 0.60–2.97 1.12 1.26 1.5 0.19 −0.39 –2.9
Flight duration ~ sRMR 1.82 0.73 0.77 0.48 −1.72 –3.18 2.3 −0.02 −0.03 0.98 −1.64 –1.59
Flight duration ~ Oviposition window 2.48 −0.40 −1.42 0.21 −1.11 –0.31 2.36 −0.26 −1.59 0.17 −0.59 –0.06
Venkateswaran et al. Movement Ecology (2017) 5:25 Page 7 of 11
shortest lifespans (1 day)  and the shortest ovipos-
ition windows (1–2 days) (Additional file 1: Figure S1),
therefore requiring the highest dispersal capacities. Our
results suggest a novel potential negative relationship
between dispersal capacity and adult lifespan through
sRMR. Life-history strategies, through time limitation,
could influence intrinsic dispersal capacities and conse-
quently impact realized dispersal.
Increased dispersal capacities coupled with high OIs
(often also coupled with short lifespans and hence time
limitation) are optimal when locating highly stochastic
resources [12, 19, 65]. The opposite is expected for
“slow”species that express OI values less than 1, have
longer lifespans, and are presumably less time-limited.
For the “fast”wasp species, the necessity to locate
ephemeral oviposition resources, coupled with the inability
to feed during dispersal stages (reliance on capital energy
reserves), and greater time limitation (owing to shorter
lifespans), could require higher dispersal capacities, as
indicated by greater pre-dispersal energy reserves, lon-
ger flight durations, and higher sRMR values compared
to the “slow”ones. Such patterns of life-history and
dispersal trait expression are common in many aerial
ectotherms [13, 17, 21].
Dispersal capacity and resource availability
The predicted negative association between flight dura-
tions and oviposition window, albeit non-significant,
suggests that the latter potentially selects for dispersal
traits in fig wasp communities. The non-significance is
likely due to the small sample size since there are only
seven species in the community. However, the negative
slope does suggest that the length of the oviposition
window is negatively correlated with dispersal capacities
and, therefore, may select for dispersal capacities. Since
our study is the first of its kind, we believe that the func-
tion of our linear regressions at this stage should be
assessed in a descriptive rather than in an inferential
manner. More such studies are required to confirm our
hypothesis. Such a confirmation could add to our under-
standing of a relatively unexplored aspect of dispersal
evolution in spatially and temporally dynamic resource
landscapes. Additionally, the positive correlation between
the variances of somatic lipid content and flight durations
with the oviposition window suggests relaxed selection
when resources are less ephemeral; species with larger ovi-
position windows exhibited greater dispersal trait variance.
Since fig wasps are known to be also passively wind
Fig. 3 Association of the trait variances (the coefficient of variation)
of dispersal trait parameters with oviposition window length for
each species. Dashed lines indicate a lack of significance while solid
lines indicate significance. Abbreviations of species names are the
same as in Fig. 2
Venkateswaran et al. Movement Ecology (2017) 5:25 Page 8 of 11
dispersed, it is likely that their dispersal success is governed
by both their intrinsic dispersal capacities as well as disper-
sal conferred by wind. Therefore, dispersal by wind could
contribute partly to the observed variance in dispersal
traits; however, the impact of wind dispersal on these traits
is as yet unknown. Despite this source of unaccounted
variance, the trend indicates that dispersal capacity is
negatively related to the length of the oviposition window.
The correlation between the variance of sRMR with the
length of the oviposition window was negative. Metabolic
rates are influenced by many functions such as growth,
reproduction, age, and maintenance of competent immune
systems and may be influenced by myriad selection
Phylogenetic relationships and phylogenetic signal
PGLS revealed trends similar to the trends obtained from
ordinary least square regressions. Specifically, the trends
between flight durations, lipid content and oviposition
window remained positive and were consistent with
expectations. The weakest associations were between
metabolic rates and flight durations; the reasons for this
may be owing to the same considerations discussed above.
A phylogenetic signal for flight duration and lipid content
suggests that these dispersal traits are influenced by phylo-
From dispersal capacities to realized dispersal
Realized dispersal in fig wasps can be governed by an
active (dispersal capacity) and a passive element (e.g.
wind-assisted movement). Aerial sampling has revealed
that fig wasps of monoecious figs (such as the wasp
community of F. racemosa) are passively wind-dispersed
over long distances [42–44]. Population genetic studies
show that C. fusciceps and F. racemosa form a single,
largely genetically homogenous population of fig wasps
and figs in southeast Asia through long-distance move-
ment of pollen and pollinator genes . Evidence from
pollen gene flow suggests that Ceratosolen arabicus, the
pollinator of Ficus sycomorus, can be wind-dispersed
over 160 km within its short lifespan of a single day .
Investigations on relative dispersal of fig wasps of a
community are also few; a population genetic study in
Ficus rubiginosa showed that the parasitoid Sycoscapter
of its pollinator Pleistodontes imperialis disperses further
than the pollinator . An investigation using wing
loading values as surrogates for dispersal abilities indi-
cated that dispersal–reproduction trade-offs in fig wasps
occupying the same trophic guild enabled community
co-existence . We demonstrate, for the first time,
that intrinsic dispersal capacities of a fig wasp community
are likely influenced by resource availabilities. Our results
indicate that intrinsic dispersal capacities (movement
owing to active flight and locomotion) are likely vital in
conjunction with passive (wind-assisted) dispersal.
Implications of the dispersal syndrome for community
In evolutionary time, fig wasp communities assemble
with the association of a wasp species with the host
shifts [71, 72]. Such associations with the microcosm of
the syconium commence with the pollinator followed
by the non-pollinators. Fig wasp communities across
the tropics also exhibit commonalities in community
structure [73–75] and are often unsaturated, especially
in the tropics . Unsaturation in fig wasp communities
has been attributed to a combination of phylogenetic
constraints, co-speciation with hosts and constraints in
the ability to colonize ephemeral resources . There-
fore, features of dispersal-related life-history traits and
effective dispersal may also be common across fig wasp
communities. The fast–slow continuum in life-history
trait expressions reveals early reproductive investment
and short lifespan on one hand, and delayed reproduction
and long lifespan on the other. The expression of alternate
combinations of such traits (e.g. early reproductive invest-
ment and long lifespans) is uncommon , possibly
because of incompatibilities in trait expression, linked trait
expressions or pleiotropy [77–81]. Such processes can lead
to the expression of a suite of linked traits and can have
implications for the evolution and maintenance of dispersal.
The linked expression of traits may reduce the freedom for
dispersal trait evolution which can influence community
assemblage and subsequent niche shifts or host shifts
through dispersal-dependent niche exploitation. This may
also explain why fig wasp communities remain unsaturated.
We show that for the wasp community, flight durations
and lipid content are potentially more reliable predictors
of dispersal than metabolic rates. We demonstrate that
the availability of oviposition resources selects for dis-
persal traits and influences the associated trait variances.
We suggest that dispersal-related life-history traits can
be selected for by differences in the dispersion of re-
sources for each species and infer that these small wasp
species are capable of propelling their dispersal despite
passive dispersal agents like the wind. Through trait co-
expression patterns both in fig wasps and in other organ-
isms, we posit the operation of trait syndromes that may
constrain dispersal-related life-history traits. Finally, we in-
dicate how phylogenetic conservatism of dispersal traits
may exist in the wasp community. This coupled with con-
strained niche shifts or host shifts point towards two pos-
sible scenarios: a) species sorting followed by ecological
niche fitting, or b) adaptation in response to selection,
Venkateswaran et al. Movement Ecology (2017) 5:25 Page 9 of 11
that shapes the dispersal traits of each species in the
community . The predisposition of certain wasps to
exhibit a particular dispersal syndrome (due to con-
strained trait co-expression) may have restricted them to
occupy niches of a suitable resource dispersion character-
istic. Therefore, the expression of a particular type of dis-
persal characteristic or capacity may be key in fig wasp
occupancy of available niches within an ephemeral
Additional file 1: Table S1. Dispersal-trait parameter values
(untransformed means and standard deviations) for each fig wasp species
in the Ficus racemosa community. Figure S1. Length of oviposition
windows associated with each fig wasp species in relation to the
developmental ontogeny of the syconium. Figure S2. Results of the
phenogram generated using cluster analysis. Figure S3. Methods for
quantifying dispersal capacity of fig wasps. Figure S4. Putative
phylogenetic relationships of wasp species of F. racemosa. (DOC 778 kb)
We are grateful to Kavita Isvaran, Sandeep Pulla, H.N. Nagaraja, and Praveen
Karanth for inputs on statistics, phylogenetics and data visualization, Maria
Thaker for unrestricted access to equipment, the Department of Molecular
Reproduction, Development and Genetics for access to their micro-weighing
balance, and Doyle McKey for comments on the manuscript. Simon Segar
provided useful suggestions for tree building as well as data analysis and
representation. G Yathiraj, Anuja Mittal, Srinivasan Kasinathan and D Sathish
helped with fig collection.
The project utilized funds from the Department of Science and Technology
(DST), DST-FIST, Department of Biotechnology, and Ministry of Environment,
Forests & Climate Change, Government of India.
Availability of data and materials
The datasets used and analyzed during the current study are available from
the corresponding author on request.
VV and RMB conceived the study; AS constructed the optical tachometer;
ALK and VV performed experiments and collected data; VV analyzed the
data; VV and RMB wrote the manuscript. All authors read and approved the
Ethics approval and consent to participate
Our experiments comply with regulations for animal care in India.
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Received: 20 September 2017 Accepted: 22 November 2017
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