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The topology of ecological interaction webs holds important information for theories of coevolution, biodiversity, and ecosystem stability . However, most previous network analyses solely counted the number of links and ignored variation in link strength. Because of this crude resolution, results vary with scale and sampling intensity, thus hampering a comparison of network patterns at different levels . We applied a recently developed quantitative and scale-independent analysis based on information theory to 51 mutualistic plant-animal networks, with interaction frequency as measure of link strength. Most networks were highly structured, deviating significantly from random associations. The degree of specialization was independent of network size. Pollination webs were significantly more specialized than seed-dispersal webs, and obligate symbiotic ant-plant mutualisms were more specialized than nectar-mediated facultative ones. Across networks, the average specialization of animal and plants was correlated, but is constrained by the ratio of plant to animal species involved. In pollination webs, rarely visited plants were on average more specialized than frequently attended ones, whereas specialization of pollinators was positively correlated with their interaction frequency. We conclude that quantitative specialization in ecological communities mirrors evolutionary trade-offs and constraints of web architecture. This approach can be easily expanded to other types of biological interactions.
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Current Biology 17, 341–346, February 20, 2007 ª2007 Elsevier Ltd All rights reserved DOI 10.1016/j.cub.2006.12.039
Report
Specialization, Constraints, and
Conflicting Interests
in Mutualistic Networks
Nico Blu
¨thgen,
1,
*Florian Menzel,
1
Thomas Hovestadt,
1,2
Brigitte Fiala,
1
and Nils Blu
¨thgen
3,4
1
Department of Animal Ecology and Tropical Biology
University of Wu¨ rzburg
Wu¨ rzburg, 97074
Germany
2
Field Station Fabrikschleichach
University of Wu¨ rzburg
Rauhenebrach, 96181
Germany
3
Institute of Molecular Neurobiology
Free University of Berlin
Berlin, 14195
Germany
Summary
The topology of ecological interaction webs holds
important information for theories of coevolution, bio-
diversity, and ecosystem stability [1–6]. However,
most previous network analyses solely counted the
number of links and ignored variation in link strength.
Because of this crude resolution, results vary with
scale and sampling intensity, thus hampering a com-
parison of network patterns at different levels [7–9].
We applied a recently developed [10] quantitative and
scale-independent analysis based on information the-
ory to 51 mutualistic plant-animal networks, with inter-
action frequency as measure of link strength. Most net-
works were highly structured, deviating significantly
from random associations. The degree of specializa-
tion was independent of network size. Pollination
webs were significantly more specialized than seed-
dispersal webs, and obligate symbiotic ant-plant mutu-
alisms were more specialized than nectar-mediated
facultative ones. Across networks, the average spe-
cialization of animal and plants was correlated, but is
constrained by the ratio of plant to animal species in-
volved. In pollination webs, rarely visited plants were
on average more specialized than frequently attended
ones, whereas specialization of pollinators was posi-
tively correlated with their interaction frequency. We
conclude that quantitative specialization in ecological
communities mirrors evolutionary trade-offs and con-
straints of web architecture. This approach can be eas-
ily expanded to other types of biological interactions.
Results and Discussion
Ecological specialization in a food web or other interac-
tion networks is commonly defined by the number of
realized ‘‘links.’ For instance, predators are specialized
if they attack only a few prey species, and specialized
flowers are those that are visited by few pollinator spe-
cies only. This concept has been extended to measure
the degree of specialization of entire networks (‘‘con-
nectance’’), where associations are classified as ‘pres-
ent’’ or ‘absent,’’ but all links are considered equally
important [1–3, 6, 8, 11–13]. However, such qualitative
measures ignore the importance of variation in interac-
tion strength for community dynamics [5, 14, 15]. More-
over, they are highly sensitive to sampling intensity and
network size [7–10, 15]. Therefore, weighted links have
been included in quantitative descriptors of different
types of webs [5, 14, 16]. In bipartite ecological net-
works, the frequency of an interaction between two spe-
cies is a meaningful measure of its strength (Figure 1)
and has been shown to represent a suitable surrogate
for mutualistic services such as pollination success
[17]. In this article, we use two measures inspired by
information theory to quantify specialization within and
across networks. Technical properties of these indices
have been explored in a recent methodology article
[10] showing that—in contrast to other quantitative
measures—they are scale independent and largely in-
sensitive to sampling effort. Unlike previous measures,
we define the overall degree of specialization in each
web as the deviation from an expected probability distri-
bution of interactions (evaluated by the standardized
two-dimensional entropy H0
2
), and individual species’
specialization as the deviation from a conformity ex-
pected by the overall utilization of potential partners
(standardized Kullback-Leibler distance, d0
i
)[10]. The
expected null distribution assumes that all species inter-
act with their partners in proportion to their total fre-
quencies, whereas the heterogeneity (evenness) of in-
teractions in previously proposed quantitative metrics
such as diversity indices [16, 18] varies with the partner
availabilities in an uncontrolled way and is thus less suit-
able in the context of network analyses (see also [10,
19]). On the basis of these standardized quantitative
measures, we explored 51 networks, covering four
types of mutualistic plant-animal associations, for pat-
terns of specialization on the level of the entire network
[2, 8], the community of each of the two parties (guild
level) [5], and the level of species [9].
Network Level
Across all networks, the overall degree of specialization
(H0
2
) covered a broad range (Table S1 in the Supplemen-
tal Data available online). All networks showed a signifi-
cantly higher degree of organization than simulated
networks, where partners were associated randomly
(all p %0.001), except for a single network of loosely as-
sociated ants and bromeliads [20] (p = 0.31). Pollination
mutualisms were significantly more specialized than
seed-dispersal mutualisms (Figure 2), corroborating a
previous qualitative analysis [2] and expected on the
basis of evolutionary considerations [21]. Plants may
*Correspondence: bluethgen@biozentrum.uni-wuerzburg.de
4
Present address: Manchester Centre for Integrative Systems Biol-
ogy (MCISB), Manchester Interdisciplinary Biocentre (MIB), Man-
chester M1 7ND, United Kingdom.
benefit disproportionately more from specialized polli-
nators, corresponding to the likelihood that each indi-
vidual pollinator successively visits conspecific plants
to maintain both male and female reproductive success
of a plant, thereby reducing maladaptive heterospecific
pollen transfer ([22, 23], but see [11]). In contrast to pol-
lination, the efficacy of seed dispersal to suitable sites
does not depend on the specialization of the dispersal
agent [21]. A broader spectrum of seed dispersers
may even be profitable from the plant’s perspective to
avoid aggregation of seeds [24] and generate fat-tailed
dispersal kernels [25], which should be favored by natu-
ral selection under many conditions [26]. Correspond-
ingly, obligate specialized mutualisms are known from
a number of pollination systems [23] but seem to be
largely absent in seed-disperser systems [21].
In ant-plant networks, there is an important distinction
between completely facultative associations, based on
extrafloral nectaries, and symbiotic associations, where
ant colonies, often obligatory, inhabit plants (myrmeco-
phytes) [27, 28]. For obligate and symbiotic mutualisms,
a higher degree of specialization is generally expected
[4, 29]. This differentiation is supported by our analysis:
Ant-plant mutualisms involving myrmecophytes were
significantly more specialized than those involving ex-
trafloral nectaries (Figure 2). Obligate associations are
common among myrmecophytic associations, some-
times causing irreversible dependence on a single part-
ner species. Myrmecophytes represent a gradient from
plants that offer neither specific structures nor specific
food rewards to support their facultative ant inhabitants
[20, 28] to cases where only few ant species are adapted
to actively bite small entrance holes into preformed do-
matia and where colonies are fully supplied by nutritious
plant-produced food bodies and never forage outside
their host plants [27, 30]. Obligate-myrmecophytic sym-
bioses represent the most specialized networks across
all systems examined in this study. In contrast to other
networks, such associations often remain uninterrupted
for several generations, opening the opportunity for the
evolution of tight specialization. In contrast, extrafloral
nectaries usually attract a spectrum of largely opportu-
nistic ants, where the accessible nectaries seem to
offer little structural plasticity to facilitate specialization
except for some degree of biochemical differentiation
[31, 32]. This dissimilarity between the two types of
ant-plant mutualisms is particularly evident between
nectary-bearing and myrmecophytic species from the
same genus [27, 32]. The gradient from facultative to
obligate mutualisms is thus largely associated with an
increasing H0
2
.
The degree of specialization did not show a significant
trend across networks of different dimensions (Figure 3)
(Spearman rank correlations for each of the four network
types, all 20.48 %r
S
%20.10, p R0.15). Given that H0
2
is mathematically independent of web size [10], the lack
of a correlation between web size and H0
2
indicates that
species-rich and species-poor real biological systems
(or smaller fractions of a system) do not inherently differ
in their degree of specialization between partners. This
novel finding contrasts with the hyperbolic decline of
Figure 1. Visualization of Two Quantitative Networks
A pollinator web and an ant-plant association are displayed (webs 6
and 37 in Table S1). Widths of links are scaled in relation to interac-
tion frequencies, bar sizes to total interaction frequencies. Both
webs are regarded specialized, but the degree of specialization is
lower in the pollinator web (H0
2
= 0.46) compared to the myrmeco-
phyte web (H0
2
= 0.84). Note that the former web is asymmetric
(more pollinator than plant species), whereas the latter is symmetric.
Figure 2. Network-Level Specialization
Overall specialization (H0
2
) in 51 mutualistic
networks. Box plots show median, quartiles,
and range of the networks analyzed (number
of networks in parentheses). Asterisks show
significant difference between types accord-
ing to a t test (*** p < 0.0001, both tR5.2,
Welsh corrected for unequal variances).
Current Biology
342
the qualitative connectance index over increasing net-
work size in different studies [2, 8, 33, 34], a decline
that was also found if applied to the dataset used here
(see Supplemental Data).
Guild Level
Within mutualistic networks, differences between the
average degree of specialization of both parties (i.e.,
plants versus animals) could be a consequence of con-
flicting interests. Consumers would only benefit from in-
creased specialization if this process went along with
greater resource-use efficacy and/or reduced interspe-
cific competition, e.g., by improved resource detoxifica-
tion, reduced handling effort, or specific search images,
and outweighed the costs of increased foraging time. If
resources were very similar, optimal foraging theory
would thus predict selection for generalization in both
frugivores and pollinators [11, 21, 23]—the latter con-
flicting with the plant’s interest in specialized pollina-
tors. However, both parties did not vary independently
in their degree of specialization, and average specializa-
tion of plants hd0
i
iand animals hd0
j
iwas largely recipro-
cal (Pearson’s r
2
= 0.71, p < 0.0001, n = 51 webs). More-
over, differences between hd0
i
iand hd0
j
iare strongly
predicted by the asymmetry of the matrix (r
2
= 0.62,
p < 0.0001) (Figure 4). In those webs where animal spe-
cies were more numerous than plants, animals showed
a lower degree of specialization (hd0
j
i<hd0
i
i) and vice
versa. This effect was even stronger (r
2
= 0.93) for simu-
lated networks with randomly assigned associations
(Figure S2). Pollinator and ant-nectar webs were
highly asymmetric, involving a much higher number of
Figure 3. Relationship between Network Size
and Specialization
Overall specialization (H0
2
) of 51 networks
plotted over network size (plant plus animal
species, log scale). Networks include pollina-
tion (yellow), seed-dispersal (black), ant-myr-
mecophyte (green), and ant-nectar plant (red)
associations.
Figure 4. Relationship between Network Asymmetry and Specialization
Asymmetry of the number of plant (I) and animal (J) species in each web (network asymmetry) is given as (J2I)/(I+J) and equals zero for bal-
anced webs (same number of animal and plant species). Specialization asymmetry between plants and animals is given as (hd0
j
ihd0
i
i)/(hd0
i
i+
hd0
j
i), based on weighted means across all species (plants ior animals j) in a web. Real networks include pollination (yellow), seed-dispersal
(black), ant-myrmecophyte (green), and ant-nectar plant (red) associations. The regression line is plotted for randomly generated networks (fixed
total interactions per species, mean values from 100 randomizations per web, r=20.97).
Mutualistic Interaction Webs
343
pollinator species (usually insects) or ant species than
plant species (on average 3.6:1 and 3.8:1, respectively).
Consequently, pollinators were significantly less spe-
cialized on plants than plants on pollinators, and ants
were significantly less specialized on plants with nectar-
ies than vice versa (paired t test; pollinators: t= 3.8,
p = 0.001; ants: t= 3.2, p = 0.01). In contrast, networks
involving seed dispersers (mostly vertebrates) as well
as ant-myrmecophyte associations were usually more
symmetric (1.2:1 and 1.6:1, respectively) and did not
show significant unequal specialization of both mutual-
ists (both p R0.38). Hence, the network architecture se-
verely constrains average specialization between two
parties irrespective of the type of association, a result
that is expected given the mathematical relationships
of the indices in their unstandardized form [10]. Such
constraints on specialization have been largely over-
looked so far, but are important in other network metrics
as well, including the ‘‘number of links’ or quantitative
‘‘dependences’ used elsewhere [5] (see Supplemental
Data). However, with architectural constraints ac-
counted for, residual variation from the linear regression
(line shown in Figure 4) depicted differences between
networks depending on the type of association. Pollina-
tors were significantly more specialized than expected
by the asymmetry (mean residuals > 0, t= 4.7,
p < 0.001), whereas ants visiting extrafloral nectaries
were more generalized than expected (residuals < 0,
t=22.4, p < 0.05). In seed-dispersal and ant-myr-
mecophyte networks, differences between animals
and plants in specialization did not deviate significantly
from the expected on the basis of asymmetry (both
pR0.10). The increased residual specialization ob-
served in pollinators, but not seed dispersers, thus
corresponds to the plant’s differential interest in these
types of mutualists.
Species Level
Although the average degree of specialization in a com-
munity may be constrained to a large degree, this does
not apply to single elements of the network, i.e., the local
population of each species. For example, disparities in
specialization of pollinators and plants were particularly
pronounced for the rarely interacting species in a net-
work. Across pollination networks, there was a signifi-
cantly positive correlation between pollinator frequency
and specialization, but a significant negative correlation
between plant frequency and specialization (Table 1).
We also found a significantly positive correlation be-
tween ant frequency and specialization in ant-myrmeco-
phyte webs but not in any of the other networks investi-
gated. Previous qualitative network analyses showed an
invariable negative correlation between frequency and
specialization (estimated as the inverse of the number
of links), a correlation that can be explained by a null
model [9] and is strongly affected by sampling effort.
In contrast, our quantitative analysis demonstrates a
highly variable relationship between frequency and
quantitative specialization, one that differs between net-
work types. Our results suggest that plant populations
with low visitation frequencies, presumably those that
occur in low densities in a community, have a particularly
unconventional spectrum of visitors. Rare plants may be
particularly sensitive for two fitness costs: subsequent
pollen deposition on (more common) plants and clog-
ging of the stigma by pollen from (common) plants
[22]. Increased specialization and reduced overlap
with visitors of common flowers may reduce such costs.
The positive correlation between animal abundance and
specialization indicates that resource partitioning is par-
ticularly pronounced among the most active species,
whereas rarely interacting species use their resources
more opportunistically.
Conclusions
Three general conclusions can be drawn from the re-
sults. (1) The network-level specialization is unaffected
by network size and form and depicts biologically mean-
ingful system-specific differences. Our results demon-
strate that the plant’s interest in specialized pollen trans-
fer but generalized fruit dispersal conformed to the
overall specialization of the respective networks. Net-
works involving facultative associations were less spe-
cialized than more obligate ones, particularly in ant-plant
webs. (2) The average degree of specialization of both
network parties is highly reciprocal, i.e., one party cannot
specialize or generalize on the other party without con-
comitant changes in the specialization within the other
party itself. Moreover, differences between network
parties are largely driven by constraints in the network
architecture (unequal species numbers). Such con-
straints cause unequal degrees of specialization as
well as asymmetric dependences between both parties.
Residual differences in specialization still contain mean-
ingful information, e.g., pollinators were more special-
ized than expected from architectural constraints only.
(3) Species-level specialization is less affected by these
constraints and may indicate differential roles of rare
and common species in a network. Such patterns may
potentially unveil density-dependent selection pres-
sures or feedback mechanisms between frequency and
specialization.
The hypothesis that natural selection drives speciali-
zation between interacting mutualists or antagonists
has been debated for a long time [4, 11, 35]. Whereas
generalists are obviously much less limited by resource
or partner availability, specialists are usually better
adapted to effectively use their selected resources. For
antagonistic relationships (e.g., predator-prey, host-
parasite, and plant-herbivore interactions), defensive
Table 1. Relationship between Frequency and Specialization of
Plant and Animal Species
Plants Animals
Pollination 20.20* (20.30 220.11)
(n = 20)
0.27* (0.15 20.37)
(n = 21)
Seed dispersal 0.06 (20.19 20.23)
(n = 7)
0.00 (20.27 20.24)
(n = 8)
Ant-myrmecophyte 0.14 (20.16 20.40)
(n = 14)
0.51* (0.24 20.71)
(n = 13)
Ant-nectar plant 20.10 (20.23 20.02)
(n = 7)
20.04 (20.27 20.16)
(n = 8)
Effect sizes derived from linear correlation coefficients for each net-
work by using meta analysis based on Fisher’s z-transformation.
Mean back-transformed rvalues are shown with range of 95% boot-
strap confidence intervals and number of webs (n) in parentheses.
Asterisks indicate significant deviation from r=0.
Current Biology
344
mechanisms of hosts or prey substantially constrain the
choices of their enemies, enforcing specialization [36].
Trade-offs between specialization and generalization
may occur in food webs [6], but are also complex among
mutualists [37], where selective pressures on partner
choices may be variable and shaped by coevolutionary
complementarity or convergence [4]. Refined analyses
and more fine-grained empirical data, particularly at
the level of individuals, may reveal additional insights
into the evolution of a broad spectrum of interaction
webs and their ecological fragility.
Experimental Procedures
We analyzed the degree of specialization for 51 published and un-
published interaction webs that included frequency data, represent-
ing a broad range of mutualistic relationships between plant-based
resources and their consumers or inhabitants and covering six con-
tinents (Supplemental Data). Although all webs were obviously dom-
inated by mutualists, several datasets may contain nonmutualistic
species, e.g., nectar robbers and seed predators. Twenty-seven da-
tasets were obtained from the Interaction Web Database (http://
www.nceas.ucsb.edu/interactionweb). For each network containing
a total of Iplant and Janimal species, we obtained the two-dimen-
sional Shannon entropy for the observed association matrix [10] as
H2=2X
I
i=1 X
J
j=1pij ,ln pij ;with X
I
i=1 X
J
j=1
pij =1:
In this equation, irepresents one plant species and jone animal
species. The number of interactions between iand j(a
ij
), e.g., the
number of recorded visits of pollinator jon plant i, is divided by
the total interaction frequencies recorded for the entire web, thus
pij =aijX
I
i=1 X
J
j=1
aij:
Our specialization index H0
2
normalized H
2
between the minimum
and maximum entropy for associations leading to the same matrix
row and column totals as
H0
2=H2max 2H2
H2max 2H2min
:
For quantification of the degree of specialization of each species
(say plant i), the proportional distribution of the interactions with
each animal (j), p0
ij
, was compared with the proportion of the total
number of interactions where jwas involved, q
j
, by using the Kull-
back-Leibler measure
di=X
J
j=1p0
ij,ln p0
ij
qj;
where p0
ij =aij=X
J
j=1
aij;thus X
J
j=1
p0
ij =1;
and qj=X
I
i=1
aij=X
I
i=1 X
J
j=1
aij;thus X
J
j=1
qj=1:
This measure was normalized as
d0
i=di2dmin
dmax 2dmin
:
Specialization of the plant community (guild level) was obtained as
the weighted mean hd0
i
i, for which each plant species iwas weighted
by its total number of interactions. Specialization of animals was cal-
culated in the same way (d0
j
and hd0
j
i). Maximum and minimum
values for H
2
,d
i
, and d
j
were computed algorithmically by using
the fixed total number of interactions of each species as a constraint
[10]. Resulting H0
2
,d0
i
, and d0
j
range between 0.0 for extreme gener-
alization and 1.0 for extreme specialization. For each network, H
2
was compared to a null model (randomly associating all species
with the total number of interactions being fixed per species, 10
4
permutations) by using an established algorithm ([38], see [10]).
Fixed marginals have been advocated as suitable constraints for
null hypotheses in qualitative webs [6, 39]. In addition, we suggest
that total interaction frequencies may better reflect variation in ani-
mal activity or plant resource availability for the actual associations
than would external estimates of local population densities [10].
Such independent measures of the species’ local abundances for
both parties have not been provided by most empirical studies so
far. All calculations can be performed online at http://itb.biologie.
hu-berlin.de/wnils/stat/.
To analyze the relationship between specialization and interaction
frequency at the species level, we calculated linear correlation coef-
ficients between log(total number of interactions) and arcsin(Od0
i
)
across all species of a guild per network and then quantified the
combined mean effect size from all networks of the same type by
using standard meta-analysis tools (MetaWin 2.0; Fisher’s z-trans-
formation, sample size as number of species, fixed effects); 95%
confidence intervals were based on bootstrapping with 999 itera-
tions, bias-corrected. To reduce a bias due to single, very large net-
works, we removed, prior to analysis, datasets where the number of
species was more than twice as large as in the second-largest
network (four cases).
Supplemental Data
Supplemental Data include additional results and data sources,
three figures, and one table and are available with this article online
at: http://www.current-biology.com/cgi/content/full/17/4/341/DC1/.
Acknowledgments
We thank D. Va
´zquez, K. Fiedler, and K.E. Linsenmair for discussion
and helpful comments on earlier versions of the manuscript and the
Interaction Web Database for providing several of the networks
analyzed here. Field work of the N.B., T.H., and B.F. was supported
by the German Research Foundation (DFG).
Received: October 25, 2006
Revised: December 6, 2006
Accepted: December 6, 2006
Published online: February 1, 2007
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Supplemental Data S1
Specialization, Constraints, and
Conflicting Interests
in Mutualistic Networks
Nico Blu
¨thgen, Florian Menzel, Thomas Hovestadt,
Brigitte Fiala, and Nils Blu
¨thgen
Supplemental Results and Data Sources
All 51 mutualistic networks used in this analysis and their
sources are listed in Table S1. Previous analyses invari-
ably demonstrated a hyperbolic decline of the qualita-
tive ‘‘connectance’ index with increasing network size,
a pattern that has considerably constrained the useful-
ness of this qualitative measure [S1]. Connectance has
been defined as the number of realized links divided
by the number of cells in the association matrix (plant
species 3animal species) [S2, S3]. For the dataset
used here, connectance declined significantly with in-
creasing matrix size within each of the network types
(all Spearman r
S
%20.64, p %0.04) except for the small
set of ant-nectar webs (r
S
=20.59, p = 0.13) (Figure S1).
Asymmetries in the average quantitative specializa-
tion of plants and animals are a function of the network
form (ratio of plant to animal species), an effect that is
particularly pronounced in random associations (Fig-
ure S2). Neither the reciprocity of average specialization
levels between guilds nor the effect of architectural con-
straints on specialization is confined to the quantitative
metrics used here. Specialization as defined in the tradi-
tional, qualitative sense (i.e., number of partner species)
is strictly dependent on the web architecture: In bal-
anced webs, when an equal number of animal species
(J) and plant species (I) is involved (I=J), the mean num-
ber of associated partners (links) for each animal (LJ)
equals that for plants (LI). Consequently, qualitative spe-
cialization is a direct function of the network asymmetry,
as LJ=LI=I=J. Differences in the number of partner spe-
cies also affect quantitative ‘‘dependences’ between
plants and animals that were used in previous analyses
by Bascompte et al. [S4], an effect that has not been
shown previously. The dependence of plant ion animal
j(b
ij
) and the reciprocal dependence of jon i(b
ji
) is esti-
mated from of the interaction frequency (a
ij
) between
them as
bij =aij
P
J
q=1
aiq
and bji =aij
P
I
p=1
apj
:
It can be shown that the average dependence of a
guild across all putative interactions (I$J, including all
cases where a
ij
= 0) is a simple function of the number
of species, because
bij =1=ðIJÞ
J=1
Jand bji =1=ðIJÞ
I=1
I:
Consequently, in square matrices (I=J), expected av-
erage differences between the two parties (b
ij
2b
ji
) are
zero, but become stronger with increasing asymmetry
in rectangular networks in both directions (I>Jor J>
I). This effect is also evident across empirical webs
(Figure S3).
Supplemental References
S1. Blu¨ thgen, N., Menzel, F., and Blu¨thgen, N. (2006). Meas uring
specialization in species interaction networks. BMC Ecol. 6,9.
S2. Jordano, P. (1987). Patterns of mutualistic interactions in polli-
nation and seed dispersal: Connectance, dependence asym-
metries, and coevolution. Am. Nat. 129, 657–677.
S3. Olesen, J.M., and Jordano, P. (2002). Geographic patterns in
plant-pollinator mutualistic networks. Ecology 83, 2416–2424.
Figure S1. Relationship between Network Size and Connectance
Qualitative connectance (proportion of realized links of the total number of possible links) of 51 networks plotted over network size (plant plus
animal species, log scale). Networks include pollination (yellow), seed-dispersal (black), ant-myrmecophyte (green), and ant-nectar plant (red)
associations.
Figure S2. Relationship between Web Asymmetry and Specialization
Each point represents the mean value (6standard deviation [SD]) of 100 randomized networks simulated from the set of 51 natural networks
(maintaining the same total interaction frequencies per species). Asymmetry of the number of pla nt (I) and animal (J) species in each web is given
as (J2I)/(I+J), asymmetry in specialization betw eenplants iand animals jas (hd0
j
i2hd0
i
i)/(hd0
j
i+hd0
i
i). Regression line (r=20.97) was used for
Figure 4 in the main text and for calculating residuals of real networks.
Figure S3. Relationship between Web Asymmetry and Dependence
Asymmetry of the number of plant (I) and animal (J) species in each web is given as (J2I)/(I+J), and asymmetry in dependence between plants i
and animals jis given as (b
ji
2b
ij
)/(b
ij
+b
ji
). Data were obtained from 26 networks [S4], including pollination (yellow) and seed-dispersal (black)
associations (means and 95% confidence intervals for all realized interactions). The mean dependence asymmetry across all realized interac-
tions of a web (a
ij
> 0) is strongly linearly predicted by network asymmetry (r= 0.97, p < 0.0001).
S2
Table S1. Mutualistic Networks Analyzed
Number Reference Taxonomic Focus Location Plants Animals mhd0
Plants
ihd0
Animals
iH0
2
Pollination
1 Barrett and Helenurm [S5] (several families) Canada 12 102 550 0.61 0.40 0.55
2 Elberling and Olesen [S6] (several families) Sweden 23 118 383 0.48 0.29 0.33
3 Inouye and Pyke [S7] (several families) Australia 42 91 1459 0.54 0.59 0.60
4 Kato et al. [S8] (several families) Japan 91 679 2392 0.65 0.37 0.48
5 Memmott [S9] (several families) Britain 25 79 2183 0.27 0.16 0.24
6 Mosquin and Martin [S10] (several families) Canada 11 18 134 0.51 0.36 0.46
7 Motten [S11] (several families) USA 13 44 2225 0.43 0.34 0.43
8 Olesen et al. [S12] (several families) Azores 10 12 1139 0.50 0.46 0.53
9 Olesen et al. [S12] (several families) Mauritius 14 13 1512 0.19 0.25 0.38
10 Ollerton et al. [S13] Asclepiadaceae South Africa 9 56 594 0.43 0.27 0.43
11 Schemske et al. [S14] (several families) USA 7 32 299 0.33 0.18 0.34
12 Small [S15] (several families) Canada 13 34 992 0.54 0.39 0.55
13 Ssymank [S16] Syrphidae Germany 88 75 4837 0.45 0.47 0.47
14 Va
´zquez and Simberloff [S17] (several families) Argentina 10 29 677 0.65 0.63 0.71
15 Va
´zquez and Simberloff [S17] (several families) Argentina 9 33 613 0.64 0.55 0.78
16 Va
´zquez and Simberloff [S17] (several families) Argentina 9 27 1130 0.90 0.65 0.85
17 Va
´zquez and Simberloff [S17] (several families) Argentina 10 29 515 0.56 0.39 0.60
18 Va
´zquez and Simberloff [S17] (several families) Argentina 8 35 719 0.53 0.26 0.57
19 Va
´zquez and Simberloff [S17] (several families) Argentina 8 26 286 0.78 0.69 0.74
20 Va
´zquez and Simberloff [S17] (several families) Argentina 7 24 761 0.65 0.84 0.79
21 Va
´zquez and Simberloff [S17] (several families) Argentina 8 27 592 0.50 0.52 0.70
Seed dispersal
22 Beehler [S18] Birds Papua N.G. 31 9 1189 0.22 0.28 0.26
23 Engel [S19] Mammals Kenya 219 33 3730 0.20 0.43 0.39
24 Hovestadt [S20] Birds, Mammals Ivory Coast 34 48 17575 0.16 0.15 0.18
25 Kaufmann [S21] Ants West Malaysia 33 51 448 0.27 0.28 0.24
26 Poulin et al. [S22] Birds, Miconia,
Psychotria
Panama 17 20 492 0.16 0.17 0.21
27 Snow and Snow [S23] Birds Trinidad 65 14 2180 0.20 0.28 0.30
28 Snow and Snow [S24] Birds Britain 29 19 19946 0.21 0.29 0.30
29 Sorensen [S25] Birds Britain 11 14 7434 0.38 0.21 0.47
Ant-myrmecophyte
30 Blu¨thgen et al. [S26] Bromeliaceae Venezuela 4 13 39 0.23 0.14 0.23
31 N.B., unpublished data Melastomataceae Ecuador 5 5 71 0.16 0.23 0.27
32 Cabrera and Jaffe
´[S27] Melastomataceae Venezuela 7 14 111 0.44 0.23 0.40
33 Davidson et al. [S28] (several families) Peru 8 18 242 0.89 0.76 0.89
34 Dejean et al. [S29] Bromeliaceae,
Orchidaceae
Mexico 9 51 388 0.51 0.26 0.47
35 Fiala et al. [S30] Macaranga Borneo 9 7 349 0.72 0.77 0.80
36 Fiala et al. [S30] Macaranga Borneo 10 8 173 0.74 0.87 0.86
37 Fiala et al. [S30] Macaranga Borneo 6 6 98 0.74 0.76 0.84
38 Fiala et al. [S30] Macaranga Sumatra 7 4 78 0.57 0.79 0.80
39 Fiala et al. [S30] Macaranga West Malaysia 4 5 183 0.71 0.77 1.00
40 B.F., unpublished data Macaranga Borneo 6 7 88 0.96 0.97 0.99
41 B.F., unpublished data Macaranga Borneo 7 5 88 0.53 0.72 0.83
42 Fonseca and Ganade [S31] (several families) Brazil 16 25 417 0.72 0.78 0.80
43 Yu and Davidson [S32] Cecropia Peru 7 4 155 0.45 0.54 0.61
Ant-nectar plant
44 Blu¨thgen et al. [S33] Philodendron, Dioclea Venezuela 6 53 180 0.36 0.11 0.31
45 Blu¨thgen et al. [S34] (several fam.), incl.
flowers
Australia 51 41 644 0.18 0.20 0.13
46 B.F., unpublished data (several families) Borneo 15 14 267 0.14 0.17 0.19
48 B.F., unpublished data (several families) Borneo 22 28 324 0.34 0.21 0.23
47 B.F., unpublished data (several families) West Malaysia 11 16 121 0.37 0.26 0.33
49 B.F., unpublished data (several families) West Malaysia 24 35 315 0.31 0.19 0.21
50 Hossaert-McKey et al. [S35] Passiflora, Mimosa French Guiana 3 37 1661 0.24 0.08 0.23
51 Whalen and Mackay [S36] Euphorbiaceae Papua N.G. 5 17 246 0.22 0.13 0.24
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... The range of modularity values is 0-1, where 0 represents networks with clustering not different from random, whiles 1 indicates networks that have perfect separation between modules. 4. Specialisation Network-level specialisation was quantified by calculating the specialisation index H2', which is given as the deviation from an expected probability distribution of interactions (Blüthgen et al. 2007). This analysis was performed with H2fun function. ...
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Aim: Given the influence of seasonality on most ecological systems, an emerging research area attempts to understand how community network structure is shaped by seasonal climatic variations. To do so, most researchers conduct their analyses using open networks due to the high cost associated with constructing their own community networks. However, unwanted structural differences from the unique sampling and construction methods used to create each open network likely make comparing these networks a difficult task. Here, with the largest set of open bipartite networks collected to date, we test whether seasonal climatic variations explain network structure while additionally accounting for construction/sampling differences between networks. Location: Trying to approach global. Time period: Contemporary. Major taxa studied: Plants and animals. Methods: Using 723 open bipartite networks, we test whether temperature and/or precipitation seasonality explains (un)weighted metrics of nestedness, modularity or specialization across plant–pollinator, seed-dispersal, plant–ant, host–parasite or plant–herbivore systems. Results: Generally, seasonality only weakly explained network structure: at most 16% of the variation in weighted metrics and 5% of the variation in unweighted metrics. Instead, a control for sampling bias in networks, sampling intensity, often better explained many of the network structural metrics. When limiting our analyses to only intensely sampled networks, however, about 33% of the variation in weighted modularity and specialization was explained by seasonality, but only in plant–pollinator networks. Main conclusions: Altogether, we do not find strong evidence that seasonality explains network structure. Our study also highlights the large amount of structural differences in open networks, likely from the many different sampling and network construction techniques adopted by researchers when constructing networks. Hence, a definitive test for the relationship between network structure and seasonality across large spatial extents will require a dataset free from sampling and other biases, where networks are derived from a consistent sampling protocol that appropriately characterizes communities.
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Eryngium maritimum L. (Apiaceae) is a geophyte that inhabits in the dunes of the Mediterranean and Atlantic. Although it is a highly entomophilous species, there is little literature on its pollinator assemblage. The aim of this study is to analyze the role played by E. maritimum in the dune pollination network of the Balearic Islands, where there is an intense anthropogenic impact in its habitat. For this purpose, two populations located in the North and South of Mallorca were chosen, in which diurnal transects were carried out to observe and capture pollinators on 15 plant species during the anthesis period of E. maritimum. The flowering period of 10 plant species flowering at the same period than E. maritimum was analyzed to identify periods of competition. A total of 71 pollinator species were found, belonging to 30 different families. Eryngium maritimum is a strongly generalist species, with a total of 45 pollinator species. Two new species, Odice blandula and Leucospis gigas, were found for the first time in Mallorca. In terms of pollinators, Teucrium dunense and Helichrysum stoechas are the most similar species to E. maritimum. However, analysis of phenology suggests that these three species have been able to decouple their blooms to avoid competition. The present study shows that E. maritimum plays an important role in the dune pollination network, being its anthesis located at the end of the dune flowering season, when there are no functionally similar species in flower. Eryngium maritimum (L.) plays a key role in the dune pollination network of the Balearic islands. It behaves as an opportunistic species and is visited by more than 80 different species. Its conservation is vital to maintain the complex ecological network of this coastal habitat.
Thesis
The intensification of agriculture with intensive use of inputs, simplification of the landscape, and reduction of semi-natural habitats, is known to contribute to the decline of arthropods. However, arthropods provide essential ecosystem functions and services in agroecosystems and for agricultural activities such as natural regulation of pests and weeds, and pollination. Increasing plant diversity in cultivated fields through the implementation of agroecological practices and infrastructures is a promising approach to promote the presence of arthropods and their associated ecosystem services. The overall objective of the thesis project was to design and experiment an innovative agroecological practice in maize cropping systems, which is easy to insert into existing cropping systems, and which provides an undisturbed habitat for ground-dwelling arthropods and supplementary floral resources for pollinators. The idea of the proposed practice was to capitalize on an already well known practice, the implementation of winter cover crops, by keeping a strip of a winter cover crop in the middle of the field during the whole maize cultivation period. Therefore, two research objectives were defined: i) to measure the impact of the practice on activity-density and diversity of ground-dwelling arthropods, on their dispersion in the cultivated area (spillover), and on the potential pest regulation in the adjacent cultivated area, and ii) to measure the interest of the practice for the conservation of wild pollinators in intensively cultivated landscapes. Field experiments took place on 12 commercial fields of volunteer farmers in 2019 and 2020, in order to take into account the technical and regulatory constraints of farmers in a conventional arable cropping system. Different species groups were surveyed: communities of ground-dwelling arthropods (carabids, spiders, staphylinids and harvestmen), slugs (the main maize pest in the study area), and pollinating insects (bees and hoverflies). Spatio-temporal dynamics of the different natural enemy groups were analysed, predation rates measured with sentinel prey, and the composition of carabid and wild bee communities investigated. Results show that the undestroyed cover crop strips constitute reservoirs of biodiversity, in particular for carabids, spiders, and bees. In the cropped area, no clear effect of the distance from the strip was detected for the different groups of ground-dwelling arthropods, thus no indication of a potential spillover of arthropods into the crop. However, two main carabid species (Poecilus cupreus and Pterostichus melanarius) were more abundant in the vicinity of the strip (10 meters), but not inside the strip, indicating a potential phenomenon of aggregation of these species towards the strip. Predation rates were higher in the strip and seemed to decrease with increasing distance from the strip into the cropped area. Moreover, carabid and bee communities showed to be different from one habitat to another, as well as the distribution of their ecological traits. Thus, the strips can provide complementary habitat and resources for natural enemies and pollinators. Finally, the spontaneous plants of field margins appeared to be essential for oligolectic and less common bees. The results of this thesis show that the conservation of a cover crop strip in the middle of cropped fields can be an effective practice for the conservation of beneficial arthropods in agricultural landscapes, but can also enhance ecosystem services such as pest regulation. Additionally, the results highlight the importance of preserving or even extending perennial semi-natural habitats such as field margins to contribute to biodiversity conservation in arable cropping systems and landscapes.
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The potential of insects for forensic investigations has been known for more than 700 years. However, arthropods such as mites could also play a role in these investigations. The information obtained from insects, together with their phoretic mites, is of special interest in terms of estimating the time and geographical location of death. This paper presents the first interaction network between phoretic mites and their host insects in Navarra. It also reports the first time that an interaction network was applied to animal remains of forensic relevance. The data reveal the degrees of specificity of the interactions established, the biological and ecological characteristics of the mites at the time of association, and factors that played important roles in the mites’ dispersion. Fauna was collected using 657 traps baited with 20 g of pig carrion over a year. Only 0.6% of insects collected carried phoretic mites. The network comprised 312 insects (275 beetles, 37 flies) and 1533 mites and was analyzed using various packages of the R programming language. We contribute new host insect records for 15 mites, 3 new records of insects as hosts, 5 new mite records for the Iberian Peninsula, and 2 new mites records and 8 new insect records for Navarra.
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Land-use change in terrestrial environments is one of the main threats to biodiversity. The study of ant-plant networks has increased our knowledge of the diversity of interactions and structure of these communities; however, little is known about how land-use change affects ant-plant networks. Here we determine whether the change in land use, from native oak forest to induced grassland, affected the network properties of ant-plant networks in a temperate forest in Mexico. We hypothesize that the disturbed vegetation will be more nested and generalized due to the addition of generalist species to the network. The oak forest network comprises 47 plant species and 11 ant species, while the induced grassland network has 35 and 13, respectively. Floral nectar was the resource used most intensely by the ants in both vegetation types. The ant-plant network of the induced grassland was significantly more nested and generalist than that of the oak forest; however, none of the networks were nested when considering the frequency of interaction. In both vegetation types, the ants were more specialized than the plants, and niche overlap was low. This could be related to the dominant species present in each type of vegetation: Prenolepis imparis in the oak forest and Camponotus rubrithorax in the grassland. The central core of cold climate ant species in the oak forest was replaced by a central core of subordinate Camponotini and tropical specialists in the induced grassland. These results suggest that the increase in nestedness and generalization in the grassland may be related to the loss of the cold climate specialists from the core of the oak forest network. Our findings provide evidence that land-use change increases the level of generalization in the ant-plant interaction networks of temperate forests.
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Many species‐rich ecological communities emerge from adaptive radiation events. Yet the effects of adaptive radiation on community assembly remain poorly understood. Here, we explore the well‐documented radiations of African cichlid fishes and their interactions with the flatworm gill parasites Cichlidogyrus spp., including 10,529 reported infections and 477 different host–parasite combinations collected through a survey of peer‐reviewed literature. We assess how evolutionary, ecological, and morphological parameters determine host–parasite meta‐communities affected by adaptive radiation events through network metrics, host repertoire measures, and network link prediction. The hosts' evolutionary history mostly determined host repertoires of the parasites. Ecological and evolutionary parameters predicted host–parasite interactions. Generally, ecological opportunity and fitting have shaped cichlid‐Cichlidogyrus meta‐communities suggesting an invasive potential for hosts used in aquaculture. Meta‐communities affected by adaptive radiations are increasingly specialised with higher environmental stability. These trends should be verified across other systems to infer generalities in the evolution of species‐rich host–parasite networks. Many species‐rich ecological communities result from adaptive radiation events. We investigate interactions of African cichlids and their flatworm parasites belonging to Cichlidogyrus (a) through network analyses (b), host repertoire estimation, and network link prediction (heatmaps) (c). The hosts’ evolutionary history and environment determine observed host repertoires and network structure (b) but cichlid radiations in Eastern Africa have formed more specialised host‐parasite communities (c).
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In this investigation of orchids, first published in 1862, Darwin expands on a point made in On the Origin of Species that he felt required further explanation, namely that he believes it to be 'a universal law of nature that organic beings require an occasional cross with another individual'. Darwin explains the method by which orchids are fertilised by insects, and argues that the intricate structure of their flowers evolved to favour cross pollination because of its advantages to the species. The book is written in Darwin's usual precise and elegant style, accessible despite its intricate detail. It includes a brief explanation of botanical terms and is illustrated with 34 woodcuts.
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I studied fruit-feeding by nine species of birds of paradise in Papua New Guinea from July 1978 through November 1980 and gathered 1,187 records of foraging at 31 species of trees and vines from 14 botanical families. Fruit consumed was consistently small-to moderate-sized (mean: 1 cm diameter), but fruit of different species of plants showed high morphological diversity. I classify the fruit of 31 plant species into three morphological groups: capsule, fig, and drupe/berry. Each of the primarily frugivorous birds of paradise was recorded taking fruits from 10-21 plant species, including representatives from each class. The monogamous Trumpet Manucode and Crinkle-collared Manucode were fig specialists. More than 80% of their diet was figs. The polygamous species of paradisaeids were more "generalized" fruit-feeders and took significant amounts of fruit from all three morphological categories. The most important types of fruit among the polygamous birds were capsular species (49% of diet). While fig species were visited by birds from many families, most nonfig trees hosted a narrower range of foragers, and two species of trees, Chisocheton weinlandii (Meliaceae) and Gastonia spectabilis (Araliaceae), were visited only by birds of paradise. The frugivorous habits of birds of paradise are similar in several respects to those of the neotropical cotingids and manakins. It is argued that while frugivory is an important component of the evolution of polygamous arena display in these birds, it cannot, by itself, explain why some birds are polygamous and others monogamous. Frugivory in the tropics is a complex syndrome that offers a number of ecological alternatives that, in turn, promote different behavioral adaptations.
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The initial spatial pattern of seed deposition influences plant population and community structure, particularly when that pattern persists through recruitment. In a vertebrate-dispersed rain forest tree, Virola calophylla, we found that spatially aggregated seed deposition strongly influenced the spatial structure of later stages. Seed dispersion was clumped, and seed densities were highest underneath V. calophylla females and the sleeping sites of spider monkeys (Ateles paniscus), the key dispersal agent. Although these site types had the lowest per capita seed-to-seedling survival, they had the highest seedling/sapling densities. Conversely, seed and seedling/sapling densities were lowest, and seed survival was highest, at sites of diurnal seed dispersal by spider monkeys. Negative density-dependent and positive distance-dependent seed survival thinned seed clumps. Nonetheless, the clumped dispersion at sleeping and parental sites persisted to the seedling/sapling stage because differences in seed deposition were large enough to offset differences in seed survival among these site types.