ArticlePDF Available

Land-use impacts on plant-pollinator networks: Interaction strength and specialization predict pollinator declines

Authors:

Abstract and Figures

Land use is known to reduce the diversity of species and complexity of biotic interactions. In theory, interaction networks can be used to predict the sensitivity of species against co-extinction, but this has rarely been applied to real ecosystems facing variable land-use impacts. We investigated plant-pollinator networks on 119 grasslands that varied quantitatively in management regime, yielding 25401 visits by 741 pollinator species on 166 plant species. Species-specific plant and pollinator responses to land use were significantly predicted by the weighted average land-use response of each species' partners. Moreover, more specialized pollinators were more vulnerable than generalists. Both predictions are based on the relative interaction strengths provided by the observed interaction network. Losses in flower and pollinator diversity were linked, and mutual dependence between plants and pollinators accelerates the observed parallel declines in response to land-use intensification. Our findings confirm that ecological networks help to predict natural community responses to disturbance and possible secondary extinctions.
Content may be subject to copyright.
Ecology, 95(2), 2014, pp. 466–474
Ó2014 by the Ecological Society of America
Land-use impacts on plant–pollinator networks: interaction
strength and specialization predict pollinator declines
CHRISTIANE NATALIE WEINER,
1
MICHAEL WERNER,
1
KARL EDUARD LINSENMAIR,
1
AND NICO BLU
¨THGEN
1,2,3
1
Department of Animal Ecology and Tropical Biology, University of Wu
¨rzburg, Germany
2
Ecological Networks, Biology, Technische Universita
¨t Darmstadt, Germany
Abstract. Land use is known to reduce the diversity of species and complexity of biotic
interactions. In theory, interaction networks can be used to predict the sensitivity of species
against co-extinction, but this has rarely been applied to real ecosystems facing variable land-
use impacts. We investigated plant–pollinator networks on 119 grasslands that varied
quantitatively in management regime, yielding 25 401 visits by 741 pollinator species on 166
plant species.
Species-specific plant and pollinator responses to land use were significantly predicted by
the weighted average land-use response of each species’ partners. Moreover, more specialized
pollinators were more vulnerable than generalists. Both predictions are based on the relative
interaction strengths provided by the observed interaction network. Losses in flower and
pollinator diversity were linked, and mutual dependence between plants and pollinators
accelerates the observed parallel declines in response to land-use intensification. Our findings
confirm that ecological networks help to predict natural community responses to disturbance
and possible secondary extinctions.
Key words: Biodiversity Exploratories; biodiversity loss; co-extinction; interaction strength; mutualistic
networks; plant–animal interactions; pollination crisis; specialization.
INTRODUCTION
The ongoing large- and small-scale changes in
anthropogenic land use are known to deplete biodiver-
sity (Duraiappah and Naeem 2005). A major goal of
biodiversity research is to understand how complex
networks of functional interactions between species
respond to disturbance and how a gradual loss of
biodiversity may affect overall ecosystem function
(Loreau et al. 2001, Koh 2004, Tylianakis et al. 2007).
These questions are of particular concern for the
pollination of flowering plants since about 87.5%of the
angiosperms, among them many agricultural crops,
depend on animal pollination (Ollerton et al. 2011).
Several studies indicate that agricultural intensification
triggers losses in the diversity of plant and pollinator
communities due to habitat conversion and fragmenta-
tion, fertilization, and pesticide use (Cunningham 2000,
Burkle and Irwin 2010, Brittain and Potts 2011).
Moreover, a high functional diversity of pollinators
may sustain a high plant diversity and lead to higher
pollination success and seed set of individual plants
(Klein et al. 2003, Hoehn et al. 2008). Among-plant
competition for limited pollinators may lead to reduc-
tion in per capita services to plants in relatively dense or
diverse populations (Vamosi et al. 2006 ). On the other
hand, visitors to dense populations are expected to be
more flower constant, increasing the chance of pollen
transfer between conspecifics (Kunin 1997), and polli-
nation may be more reliable in dense plant populations
(Bernhardt et al. 2008). Outcrossing by pollinators is
important in the long term where inbreeding negatively
affects population viability and increases local extinction
risks (Byers 1995). In turn, high plant diversity is
assumed to promote pollinator richness and functional
diversity (Kwaiser and Hendrix 2007). Consequently,
experiments with manipulated plant species diversity
(Ebeling et al. 2008) and comparisons across different
meadows (Fru
¨nd et al. 2010) demonstrated positive
relationships between plant diversity and pollinator
diversity and abundance. Additionally, analyses of
historic data from Britain and the Netherlands revealed
parallel diversity declines in bees and insect-pollinated
plants (Biesmeijer et al. 2006 ).
These results lead to the hypothesis that losses in plant
and flower-visitor diversity might be causally linked,
e.g., a consequence of mutual dependence. Such
dependency on certain partners implies that interaction
partners are specialized to a considerable degree. To
understand land-use effects on interacting species, it is
thus crucial to investigate their degree of specialization
and the identity of each species’ partners. This may
allow predictions of how land-use-induced changes in
species composition would affect natural communities
and their functions. Network analysis provides a useful
framework for characterizing specialization and predict-
Manuscript received 20 March 2013; revised 27 June 2013;
accepted 23 July 2013. Corresponding Editor: B. D. Inouye.
3
Corresponding author.
E-mail: bluethgen@bio.tu-darmstadt.de
466
ing vulnerability of resource–consumer relationships or
mutualisms to species loss (Montoya et al. 2006 ).
Some studies suggested that specialist species are
prone to disturbance, while generalists benefit from it
(McKinney 1997, Aizen et al. 2012; but see Va
´zquez and
Simberloff 2002, Winfree et al. 2007). While some
approaches have predicted the vulnerability of complex
communities based on simulated extinctions or dynamic
population modeling (Memmott et al. 2007, Pocock et
al. 2012), such changes have been rarely tested in real-
world systems. Methods used in modeling approaches
are controversial (Benadi et al. 2012, James et al. 2012),
and conflicting conclusions based on empirical data may
be partly explained by the fact that specialization
metrics differ in their sensitivity to sampling effects
(Blu
¨thgen 2010). Since the number of links (observed
interaction partners) increases with the number of
observations, rarity and specialization are confounded
unless corrected by appropriate network metrics (Blu
¨th-
gen et al. 2007).
In the present study, we focus on specialization and
changes in plant–pollinator interactions in grasslands
along a gradient of increasing land-use intensity. We
hypothesized that (1) land-use intensification triggers a
decline in plant diversity and, consequently, a plant-
mediated decline in the diversity of floral resource
consumers. Moreover, we expected (2) stronger effects
of land-use intensification on specialized plant and
pollinator species, which are more dependent on their
specific partners than generalists are. However, we
assumed that (3) pollinator-mediated declines in plant
species are less pronounced than resource-mediated
declines of pollinators, since many plant species are
not obligatory insect pollinated and are capable of
vegetative reproduction.
METHODS
Study area and land-use intensity
The large-scale Biodiversity Exploratories represent
three bioregions in Germany located in the Schorfheide-
Chorin (Sch), Hainich-Du
¨n (Hai ), and Schwa
¨bische Alb
(Alb) (Fischer et al. 2010). Each of the three Explor-
atories covers a connected area of 422 to ;1300 km
2
of
land and each comprises 50 grassland plots. These plots
are situated within a matrix of agricultural land in use
and measure 50 350 m each. The minimum distance
between the outer edges of two plots is 200 m and each
grassland plot is at least 30 m away from the nearest
forest edge. A detailed description of all selection criteria
for experimental plots is given by Fischer et al. (2010).
The plots represent a broad gradient of land-use
intensity, ranging from near-natural, protected sites to
intensively fertilized, mown, or grazed meadows and
pastures (sheep, horses, cattle).
Qualitative categorization of land use such as
meadow/pasture or fertilized/unfertilized obscures the
variation of intensities within a category, e.g., differenc-
es in grazing intensity or fertilizer application. We
therefore used a continuous land-use-intensity index for
grasslands that incorporates the three variables fertil-
ization, mowing, and grazing intensity (Blu
¨thgen et al.
2012). For each plot k, the land-use intensity L
k
is
defined as the square root of the sum of these three
variables, each of which was standardized by its regional
mean (i.e., the mean of each Exploratory):
L¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Gk
Gmean
þFk
Fmean
þMk
Mmean
r
where F
k
is the fertilization level (kg nitrogenha
1
yr
1
),
M
k
is the frequency of mowing per year, and G
k
is the
livestock density (livestock unitsd
1
ha
1
yr
1
) on the
site. Due to the standardization by ratios, L
k
is
dimensionless. We used the mean L
k
of the three years
2006–2008 for all correlations; although L
k
changed
only to a small degree between years, this mean value
best captures previous and ongoing management which
may both effect plants and pollinators. L
k
has been
shown to predict responses in the vegetation, namely the
plants’ nitrogen indicator values, nitrogen and phos-
phorous contents in plant and soil, as well as plant
diversity (Blu
¨thgen et al. 2012).
Data collection
Between May and August 2008, we investigated
plant–flower-visitor networks on 119 different experi-
mental grassland plots (Alb, 39; Hai, 39; Sch, 41). Of
these, 29 plots were investigated repeatedly, up to four
times (in Alb, 15 plots were surveyed repeatedly, nine
plots two times, three plots three times, and three plots
four times; in Hainich, eight plots were surveyed
repeatedly, four plots two times, four plots three times;
in Schorfheide, six plots were surveyed repeatedly, five
plots two times, one plot three times), resulting in 162
surveys done in total (Alb, 63; Hai, 51; Sch, 48). Each
survey covered a time span of six hours between
morning and afternoon and an area of 200 33m
(length 3width) along the edge of the square
experimental grassland plot. For this transect, which
we walked three times during one survey (three rounds,
two hours each), we documented all plant–flower-visitor
interactions. We recorded each insect that visited a
flower as well as the flower species on which it was
observed, but disregarded those insects that were sitting
on the outer petals obviously not feeding on pollen or
nectar. Specimens that we could not identify in the field
were collected and later identified to species level with
the help of experts (see Acknowledgments).
To gain independent data on flower abundance, we
first counted the number of flowering units per plant
species and transect or, in highly abundant species,
extrapolated it from a smaller area. One ‘‘flowering
unit’’ was defined as a unit of one (e.g., Ranunculaceae)
or more flowers (e.g., Asteraceae) demanding an insect
to fly in order to switch to another unit (Dicks et al.
2002). To incorporate differences in flowering area, we
assessed flower diversity by multiplying the number of
February 2014 467PLANT–POLLINATOR NETWORKS AND LAND-USE
flowering units of a species by its average flowering area
in cm
2
. In zygomorphic flowers, flowering area was
calculated as a rectangle based on flower length and
width, while in actinomorphic flowers flowering area
was calculated as a circle based on the flower diameter.
In umbels, we divided the diameter of a flowering unit
by two before calculating the flowering area, as
flowering units are much less compact here than other
flowers. This is reasonable, since flower display size is
related to pollinator attraction (Grindeland et al. 2005)
and also predicted the pollen volume per flower for a
subset of the investigated plants for which we have
sampled pollen (Pearson, r¼0.62, P¼0.00002; N¼40
plant species; data not shown). We obtained data on
plant species breeding systems i.e., whether a plant
species is potentially self-compatible (autogamous spe-
cies and species with mixed mating) or not (xenogamous
species) from the BiolFlor database (Klotz et al. 2002).
Forty-seven plant species are self-incompatible, 12
species show mixed mating, five are autogamous, and
two species have an apomictic breeding system.
From each survey, a single interaction network was
compiled and analyzed separately. Use of short-term
interaction networks allowed us to record a uniquely
high number of network replicates as well as to avoid
confounding effects by seasonal variation and nonover-
lapping phenology. We analyzed all flower visits from
insect flower visitors belonging to the orders of Diptera,
Hymenoptera, Lepidoptera, and Coleoptera. All these
visitor taxa are generally known to pollinate and are
thus termed ‘‘pollinators’’ in accordance with previous
studies, although they may not pollinate each flower on
which they forage. We excluded generally non-pollinat-
ing taxa (grasshoppers, spiders), but also Nitidulidae
from analysis, as they occurred in particularly high
numbers and are easily overlooked and under-sampled
in structurally complex flowers, which would bias the
analysis.
While in the Hainich and Schorfheide Exploratories
we left a minimum interval of 30 days before repeatedly
surveying a plot, in the Alb Exploratory regarding 13
repeatedly sampled plots, we had conducted a total of 27
surveys within 30 days (12 plots were sampled two times,
one plot three times within 30 days). To avoid
phenologically similar replicates per plot, we calculated
mean values from these surveys per plot for each of the
variables below before correlating them to land use. This
reduced the number of independent replicates on the Alb
to 49 instead of 63. The dissimilarity of plant and
pollinator assemblages across the remaining repeated
surveys from the same plots was high. Repeated surveys
from the same plot showed the same or an even higher
level of species turnover than surveys from different
plots (Appendix: Table A1). Mantel tests (Spearman,
r
M
) based on Bray-Curtis distance and 1 310
5
permutations showed a strong correlation between
plant/insect species composition (based on relative
abundances) and sampling date (plants, all r
M
0.15,
all P0.0003, n¼49 Alb, 51 Hai, and 48 Sch; insects,
all r
M
0.23, all P0.0001, n¼49 Alb, 51 Hai, and 48
Sch). In contrast, the spatial arrangement of the plots
did not affect our data (plants, all r
M
0.04, all P
0.15; pollinators, all r
M
0.03, P0.32). Moreover,
land-use intensity neither correlated with sampling date
nor spatial distance in any Exploratory (all r
M
0.03,
all P0.25). Therefore, despite pronounced temporal
variation, we consider our analyses of land-use effects
unbiased by spatial and temporal effects.
Statistical analysis
Hitherto most studies have investigated specialization
and predicted possible consequences for co-extinctions
based on qualitative metrics, i.e., the number of links of
each species (‘‘species degree’’). Moreover, pooled data
over longer temporal or spatial scales were used (e.g.,
Memmott et al. 2007). Such metrics are prone to
variation in sampling effort (Va
´zquez et al. 2009) and
disregard differences in the proportional distribution of
species. Species with few observations inevitably have
few links, hence specialization of many rare species is
severely overestimated due to several undetected links.
This bias has been demonstrated for pollinators when
other sources of information of flower use were
employed (Dorado et al. 2009). Pooling data over large
areas or over long time periods also produces many
zeros due to ‘‘forbidden links’’ produced by spatial or
temporal nonoverlap, which hampers the interpretation
of specialization. Therefore, it is important to carefully
define specialization based on quantitative metrics
independent of sampling effort and species abundances
(Dormann et al. 2009) in order to compare the species’
responses to disturbance. We thus calculated comple-
mentary specialization of plants and pollinators em-
ploying the information-theoretical indices H0
2and d0
i
(Blu
¨thgen et al. 2006) for each of our short term
networks. H0
2specifies the degree of complementary
specialization in the entire network, while d0
icharacter-
izes the specialization of each species ias its quantitative
non-conformity, e.g., its deviation in flower visitation
from the distribution of all pollinators. Both indices
vary between 0 and 1, with high values corresponding to
more pronounced niche complementarity. While H0
2and
d0
iare mathematically independent of the total observa-
tion frequency per species and per network, due to the
standardization based on marginal totals, other network
metrics such as species degree, dependence, connectance,
and nestedness directly reflect variation in species’ total
frequencies as well as sampling effort (Blu
¨thgen 2010).
This bias is also evident in our dataset, where species
degree and generality strongly increased with number of
observations, whereas d0
iwas unaffected (Appendix: Fig.
A1). H0
2was tested against Patefield’s null model,
running 10 000 randomizations (Blu
¨thgen et al. 2006).
We used the weighted mean d0
iof each species iacross
all networks (weighted by the total interaction records of
iper plot k) as well as a weighted mean d0
ifor taxonomic
CHRISTIANE NATALIE WEINER ET AL.468 Ecology, Vol. 95, No. 2
groups of flower visitors, namely bees, other hymenop-
terans, beetles, butterflies, syrphids, and other dipterans.
To provide a weighted mean for such a group in each
plot k, each species iwas weighted by its total number of
individuals recorded in k. We segregated bees from other
hymenopterans and syrphids from other dipterans, as
both are commonly used bioindicator taxa (Biesmeijer et
al. 2006).
Our goal was to distinguish effects of niche properties,
e.g., specialization and specific partner identity, on
species’ responses to land use from the effects of species
abundances. We thus also tested species abundances
(i.e., total number of individuals observed during flower
visits, or total flower area for plants) for land-use effects
defined below.
For each pollinator species i, we identified their
general response to land-use intensity (r
i
). To quantify
the sign and magnitude of r
i
, we used a Spearman
correlation coefficient (r
S
) between the relative abun-
dance of species iper plot k(percentage of total
individuals) and land-use intensity L
k
across all plots,
including cases where iwas absent. The same method
was applied to quantify the response of each plant
species j(replace iby jabove, see Fig. 1 and Appendix:
Fig. A2).
In addition to the degree of specialization of a species,
the identity of its partners may be important. The land-
use response of an animal may be determined by the
land-use response of its associated plant species,
weighted by the plant’s relative importance for its
partner (interaction frequency) provided in the network.
Each plant species jof Jtotal plant species can be
described by its land-use response r
j
. The average land-
use response of all the food plants frequented by
pollinator species i(E
i
), weighted by the number of
interactions a
ij
between iand j, is then
Ei¼X
J
j¼1
ðrj3aijÞX
J
j¼1
aij:
Inversely, the average land-use responses of all the
pollinator species ivisiting a plant species jis
Ej¼X
I
i¼1
ðri3aijÞX
I
i¼1
aij:
If the partner identities and interaction strengths of
interactions in a network determine the average land-use
response of species in a community, we expect a positive
correlation between actual species responses and the
average responses of their specific partners. Hence, there
should be a positive relation r
i
;E
i
across all Iflower
visitors if plants determine the responses of visitors, and
r
j
;E
j
across all Jplants, if pollinators determine the
responses of plants. We tested the determinants of those
responses r
i
and r
j
using ANCOVA (type II SS)
including the three predictors E
i
,d0
i(both continuous),
and pollinator group (categorical) for pollinators and E
j
,
d0
j(both continuous), and breeding system (categorical)
for plants. Alternatively to data from our flower surveys,
we used binominal vegetation survey data collected on 4
34 m quadrats per plot (see Blu
¨thgen et al. 2012) to
calculate logistic regressions (see Appendix: Fig. A1b)
and used the odds instead of Spearman to calculate r
j
and E
i
. The alternative approach yielded the same
overall results (Fig. A2). All statistics were conducted in
R 2.15.1 (R Development Core Team 2012).
RESULTS
Our networks document 25 401 interactions between
166 plant species and 741 pollinator species. We
identified 115 bee species, including 25 pollen specialists
(oligolectic bees), 48 other hymenopterans, 50 butter-
flies, 104 beetles, 103 syrphids, and 321 other dipteran
species. A full list of species is provided in the Appendix:
Table A2 and A3.
Plant responses.—Plant species richness (Spearman
rank, r
S
¼0.22, P¼0.007, N¼148 networks) and
Shannon diversity (r
S
¼0.21, P¼0.01) declined with
increasing land-use intensity. The average land-use
response of a plant species (r
j
) was predicted by the
weighted response of its pollinator species (E
j
), but
neither differed with plant specialization nor between
self-compatible and self-incompatible plants (Table 1a).
Yet, average specialization in plants was very high (d0
i¼
0.55 60.22 [mean 6SD]).
Moreover, plant responses to land-use intensity were
related to their relative abundance: rare plants (in terms
of their proportional coverage of floral area) showed a
stronger decline with increasing land use than more
abundant ones (r¼0.22, P¼0.005).
Pollinator responses.—Neither total pollinator species
richness (r
S
¼0.08, P¼0.32, N¼148), abundance (r
S
¼
0.001, P¼0.99), or Shannon diversity (r
S
¼0.14, P¼
0.07) was correlated to land-use intensity. Pollinator
species composition corresponded to flower composition
(Mantel tests based on Bray-Curtis distance, all r
M
0.22, P0.0001). Moreover, responses to land-use
intensity were independent of pollinator abundance (r¼
0.035, P¼0.34, N¼741 pollinator species; Appendix:
Fig. A1d).
Responses of pollinators to land use (r
i
) strongly
depend on their association with specific flowers, i.e., the
weighted mean responses of their plant species visited
(E
i
; Table 1b). Pollinator specialization (d0
i) was a
significant predictor of r
i
if treated as the sole variable,
but not in the mixed model, where it significantly
interacted with E
i
(Table 1b). Moreover, pollinator
group identity had a significant influence on pollinator
response (r
i
) to land use (Table 1). Regarding the
interaction term between d0
iand E
i
, land-use responses
of highly (d0
i0.6, n¼38) and intermediately
specialized pollinators (0.2 d0
i,0.6, n¼261) were
more strongly driven by the responses of their preferred
plants than in more generalized pollinators (d0
i,0.2, n¼
442, Fig. 2). However, plant species that support
unspecialized and intermediately specialized pollinators
February 2014 469PLANT–POLLINATOR NETWORKS AND LAND-USE
were more vulnerable to land use than plant species
supporting highly specialized pollinators: there was a
negative relationship between pollinator specialization
and the land-use response of their resources (r
S
¼0.26,
P,0.0001, n¼741). For highly specialized pollinators
the trend had an opposite direction (Appendix: Fig. A4).
Regarding the interaction term between pollinator
group identity and E
i
, bees and other hymenopterans,
butterflies, beetles, and flies (excluding syrphids) strong-
ly reflected the land-use response of the plant species
they visited in their own relative abundances. In
contrast, syrphids seemed to respond to land-use
changes independently from the responses displayed by
the plants they visited (Table 1, Appendix: Fig. A5).
With increasing land-use intensity the proportion of
syrphid species increased, whereas the proportion of
butterfly and hymenopteran species (excluding bees)
decreased. The proportion of bee, beetle, and dipteran
species (excluding syrphids) did not show significant
trends across the Exploratories (Table 2), although bees
significantly declined and dipterans significantly in-
creased with land-use intensity in the Alb (r
S
¼0.38,
P¼0.007 and r
S
¼0.47, P,0.001, respectively).
Plant–pollinator networks deviated significantly from
random associations and were highly structured (mean
network specialization H0
2¼0.63 60.17[mean 6SD], N
¼148). Most networks were significantly different from
Patefield’s null model of random interactions (P,0.001
for 130 networks and P,0.05 for additional nine
FIG. 1. Land-use response of (a) Lotus corniculatus in terms of relative flower cover and (b) one of its visitors, Thymelicus
sylvestris, in terms of relative abundance. In theory, the land-use response of a pollinator may be predicted by the land-use response
of its food plants, if land use affects pollinators mainly indirectly via changes in food resources.
CHRISTIANE NATALIE WEINER ET AL.470 Ecology, Vol. 95, No. 2
TABLE 1. (a) Statistical model to predict species-specific plant responses to land use (r
plants
) based on the weighted average
pollinator response E
j
(weighted r
pollinators
), specialization (d0
j), and breeding system of each plant species and (b) model to
predict pollinator responses (r
pollinators
) based on weighted average plant responses E
i
(weighted r
plants
), specialization (d0
i) and
pollinator group identity.
Effect
Complete model Univariate model
df FPdf FP
a) Species-specific plant responses
E
j
1 19.24 0.00002 1 19.75 0.000016
d0
j1 0.49 0.4857 1 0.49 0.48
Breeding system 1 0.26 0.6140 1 0.23 0.69
E
j
3d0
j1 1.56 0.2141
E
j
3breeding system 1 0.42 0.5178
d0
j3breeding system 1 0.02 0.8817
Error 159 164
b) Pollinator responses
E
i
1 228.28 ,0.00001 1 265.43 ,0.000001
d0
i1 0.00 0.9547 1 13.51 0.000255
Pollinator group 5 4.08 0.0012 5 9.90 ,0.000001
E
i
3d0
i1 6.79 0.0093
E
i
3pollinator group 5 3.89 0.0018
d0
i3pollinator group 5 1.21 0.3030
Error 722 735
Note: Complete model and main factors in three univariate models are shown (ANCOVA; Type II SS).
FIG. 2. Interaction strengths in quantitative networks predict indirect effects of land-use intensification. Pollinator abundances
decrease in response to declines of their most frequently visited plant species. Therefore, for the sensitivity of a species, it is not only
important how specialized it is, but also on whom it is specialized. Regression lines are shown for pollinators with low (d0
i,0.2),
intermediate (0.2 d0
i,0.6), and high (d0
i0.6) degree of specialization.
February 2014 471PLANT–POLLINATOR NETWORKS AND LAND-USE
networks). Network specialization was not consistently
related to land-use intensity (r
S
¼0.11, P¼0.22). Species
specialization d0
idiffered between pollinator groups
(Kruskal-Wallis v
2
¼55.50, P,0.0001). It was
strongest for bees and butterflies, intermediate for
beetles and hymenopterans, and lowest for syrphids
and other dipterans (Table 2).
DISCUSSION
Our results demonstrate four important land-use
effects on plant–pollinator interactions. (1) Land-use
intensification primarily triggers losses in flower diver-
sity, which could lead to nonrandom and resource-
mediated declines in certain pollinators. Overall polli-
nator diversity is not significantly affected by land use,
but pollinator composition is. (2) Although responses of
the pollinators visiting a plant species may also influence
plant abundance, this effect is weaker. (3) Land-use
intensification has a disproportionate impact on the
abundance of more specialized pollinators, (4) but not
on the abundance of specialized plant species.
The linkage between a pollinator’s response and the
response of the plant species it visits potentiates for
specialized pollinators, i.e., specialists on plants that
profit from land use are increasing, while those on
negatively affected plant species decrease accordingly. A
strong dependence of pollinators on a narrow set of
plant species is associated with higher co-extinction risk,
since these plant species cannot be functionally replaced
by others (Praz et al. 2008). Moreover, in communities
characterized by low response diversity and low
functional redundancy, resilience after disturbance and
the ability to buffer environmental changes are reduced
(Elmqvist et al. 2003, Laliberte et al. 2013). Negative
impacts of specialization may be partly compensated by
a higher efficiency of specialists, e.g., specialist bees are
very effective in finding flowers, pollen collection, and
digestion (Strickler 1979, Dobson and Peng 1997), but
the general extent of such compensation is unknown.
Our findings are consistent with the hypothesis that
pollinator declines are driven by the disappearance of
their important host plants, while the reciprocal effects
of pollinators on plants are weaker. In this type of
mutualism, the composition of plant communities may
be relatively robust against losses of particular polli-
nators, at least in the short term covered by our study
(Kalisz et al. 2004 ). Most grassland plants involved in
our study are self-compatible and/or have vegetative
reproduction modes (Klotz et al. 2002) and thus our
surveys may not be suitable to detect effects of reduced
genetic diversity in plant populations that may occur
with pollinator losses. While plant reproductive fitness
and outcrossing may be at risk over longer time spans,
the immediate effects on the fitness and/or local
distribution of pollinator communities may be more
severe when their important floral resources become
unavailable (Biesmeijer et al. 2006, Goulson et al.
2008). The asymmetry in local extinction risks may be
increased by the fact that pollinators typically provide
several times more species per network than plants and
thusalargerbuffer(Blu
¨thgen et al. 2007), also
mirrored in our data (flowering plants, 8.4 64.4
species; visiting pollinators, 31.9 615.2 species; n¼148
networks). The mutual specialization and thus depen-
dence between pollinator and plant species may lead to
parallel regional declines in historical comparisons
(Biesmeijer et al. 2006, Fru
¨nd et al. 2010). Correspond-
ingly, the more generalized syrphids suffered less from
regional extinctions (and often even gained a higher
diversity in some regions) in recent decades than the
more specialized bee species (Biesmeijer et al. 2006,
Jauker et al. 2009). These trends are also reflected in
their responses to land use in our study. Land-use
intensification not only causes a loss in plant diversity,
but also translates into pronounced changes in polli-
nator communities. The changes in pollinator compo-
sition, the dominance of flies and declines in many
other taxa, correspond to a biotic homogenization
(Filippi-Codaccioni et al. 2010) on high-intensity
grasslands. Species richness and abundance of syrphids
was also positively influenced by land-use intensifica-
tion in other studies (Biesmeijer et al. 2006, Ebeling et
al. 2008, Jauker et al. 2009), whereas bee diversity and
abundance declined (Biesmeijer et al. 2006, Le Fe
´on et
al. 2010). This process is easily overlooked when
focusing on total biodiversity only. Land-use intensi-
fication reduces taxonomic breadth and functional
diversity, which could conversely affect plant repro-
ductive success, species richness, and functional diver-
sity (Klein et al. 2003, Hoehn et al. 2008). In a South
African ecosystem, Pauw (2007 ) showed that, among
seven species of orchids, those that were more
specialized suffered severely from the loss of the single
pollinator species.
Dipteran pollinators showed the lowest specialization
for plant species, whereas bees, other hymenopterans,
butterflies, and beetles were more specialized (see also
Weiner et al. 2011), confirming that specialization
represents a risk that renders species more vulnerable
to co-extinction (McKinney 1997, Va
´zquez and Simber-
loff 2002, Winfree et al. 2007, Aizen et al. 2012, Pocock
et al. 2012). Correspondingly, investigations on butter-
flies (Tudor et al. 2004 ), beetles (Kotze and O’Hara
TABLE 2. Land-use responses (changes in species richness with
increasing land-use intensity, Spearman’s r
S
) and flower
specialization (d0
i) of six pollinator groups.
Pollinator group r
S
P
d0
i
Mean SD
Bees 0.04 0.64 0.39 0.22
Other hymenopterans 0.21 0.01 0.28 0.23
Butterflies 0.28 ,0.0005 0.33 0.24
Beetles 0.10 0.24 0.27 0.21
Syrphids 0.21 0.01 0.24 0.16
Other dipterans 0.09 0.26 0.25 0.19
CHRISTIANE NATALIE WEINER ET AL.472 Ecology, Vol. 95, No. 2
2003), and bumblebees (Kleijn and Raemakers 2008)
demonstrated that many specialized species are of
conservation concern and have undergone a consider-
able decline in the last decades.
In addition to indirect effects via flower composition
and availability, land use may affect pollinators directly,
e.g., via disruption of life cycles (Johst et al. 2006 ) or
supply of appropriate nesting resources (Potts et al.
2005) or larval habitats. Many bees and beetles show
preferences for certain environmental conditions, larval
sites, or nesting sites, and their abundance depends on
certain habitats and landscape structures (Gathmann
and Tscharntke 2002). On the other hand, generalized
flower visitors like most syrphids and other dipterans are
not restricted to certain landscape structures and may
profit from diverse larval habitats (Jauker et al. 2009).
Over longer time spans, such direct land-use effects on
pollinators may transform into pollinator-mediated
effects on plant communities. However, in the short
term covered by our study land-use effects on plants and
plant-mediated effects on pollinators played a greater
role than vice versa.
Our findings emphasize how systems based on
mutualism may undergo severe transformation due to
land-use intensification. Agricultural management is a
major factor driving the change of floral and faunal
richness in anthropogenic landscapes. Network analy-
ses, particularly the degree of complementary speciali-
zation and the quantitative interaction strength, may
provide important tools to predict how different species
respond to disturbance and biodiversity changes in
real communities.
ACKNOWLEDGMENTS
For identification of insects, we thank W. Adaschkiewitz, R.
Heiß, G. Merkel-Wallner, B. Merz, V. Michelsen, S. Prescher,
H. G. Rudzinski, A. Stark, K. Szpila, M. Tospann, M. von
Tschirnhaus, and H. P. Tschorsnig (Diptera); D. Doczkal
(Apidae, Syrphidae); M. Fellendorf, M. Hermann, V. Mauss,
and H. Schwenninger (Apidae); K. Horstmann and S.
Klopfstein (Ichneumonidae); L. Hubweber and P. Sprick
(Coleoptera); M. Krauss and B. Wende (Symphyta); R. Schultz
(Formicidae); and M. Wo
¨lfling (Lepidoptera). D. Va
´zquez
provided helpful comments. We thank the managers of the
three Exploratories, S. Renner, S. Gockel, K. Wiesner, and M.
Gorke, for their work in maintaining the plot and project
infrastructure; S. Pfeiffer and C. Fischer for support through
the central office; M. Owonibi for managing the central
database; and M. Fischer, D. Hessenmo
¨ller, J. Nieschulze, D.
Prati, I. Scho
¨ning, F. Buscot, E.-D. Schulze, W. W. Weisser,
and the late E. Kalko for their role in setting up the Biodiversity
Exploratories project. The work has been funded by the DFG
Priority Program 1374 ‘‘Infrastructure-Biodiversity-Explorato-
ries’’ (LI 150/20-1 and BL 960/2-1). Field work permits were
issued by the responsible state environmental offices of Baden-
Wu
¨rttemberg, Thu
¨ringen, and Brandenburg (according to §72
BbgNatSchG).
LITERATURE CITED
Aizen, M. A., M. Sabatiano, and J. M. Tylianakis. 2012.
Specialization and rarity predict nonrandom loss of interac-
tions from mutualist networks. Science 335:1486–1489.
Benadi, G., N. Blu
¨thgen, T. Hovestadt, and H. J. Poethke.
2012. Population dynamics of interacting plant and pollina-
tor communities: stability reconsidered. American Naturalist
179:157–168.
Bernhardt, C. E., R. J. Mitchell, and H. J. Michaels. 2008.
Effects of population size and density on pollinator
visitation, pollinator behavior, and pollen tube abundance
in Lupinus perennis. International Journal of Plant Science
169:944– 953.
Biesmeijer, J. C., et al. 2006. Parallel declines in pollinators and
insect pollinated plants in Britain and the Netherlands.
Science 313:351–354.
Blu
¨thgen, N. 2010. Why network analysis is often disconnected
from community ecology: a critique and an ecologist’s guide.
Basic and Applied Ecology 11:185–195.
Blu
¨thgen, N., et al. 2012. A quantitative index of land-use
intensity in grasslands: Integrating mowing, grazing and
fertilization. Basic and Applied Ecology 13:207–220.
Blu
¨thgen, N., F. Menzel, and N. Blu
¨thgen. 2006. Measuring
specialization in species interaction networks. BMC Ecology
6:9.
Blu
¨thgen, N., F. Menzel, T. Hovestadt, B. Fiala, and N.
Blu
¨thgen. 2007. Specialization, constraints, and conflicting
interests in mutualistic networks. Current Biology 17:341–
346.
Brittain, C., and S. G. Potts. 2011. The potential impacts of
insecticides on the life-history traits of bees and the
consequences for pollination. Basic and Applied Ecology
12:321–331.
Burkle, L. A., and R. E. Irwin. 2010. Beyond biomass:
measuring the effects of community level nitrogen enrich-
ment on floral traits, pollinator visitation and plant
reproduction. Journal of Ecology 98:705–717.
Byers, D. L. 1995. Pollen quantity and quality as explanations
for low seed set in small populations exemplified by
Eupatorium (Asteraceae). American Journal of Botany 82:
1000–1006.
Cunningham, S. A. 2000. Depressed pollination in habitat
fragments causes low fruit set. Proceedings of the Royal
Society B 267:1149–1152.
Dicks, L. V., S. A. Corbet, and R. F. Pywell. 2002.
Compartmentalization in plant–insect flower visitor webs.
Journal of Animal Ecology 71:32–43.
Dobson, H. E. M., and Y.-S. Peng. 1997. Digestion of pollen
components by larvae of the flower-specialist bee Chelostoma
florisomne (Hymenoptera: Megachilidae). Journal of Insect
Physiology 43:89–100.
Dorado, J., D. P. Va
´zquez, E. Stevani, and N. Chacoff. 2009.
Rareness and specialization in plant–pollinator networks.
Ecology 92:19–25.
Dormann, C., J. Fru
¨nd, N. Blu
¨thgen, and B. Gruber. 2009.
Indices, graphs and null models: analysing bipartide ecolog-
ical networks. Open Ecology Journal 2:7–24.
Duraiappah, A., and S. Naeem. 2005. Ecosystems and human
well-being: biodiversity synthesis. World Resources Institute,
Washington, D.C., USA.
Ebeling, A., A.-M. Klein, J. Schumacher, W. W. Weisser, and
T. Tscharntke. 2008. How does plant richness affect
pollinator richness and temporal stability of flower visits?
Oikos 117:1808–1815.
Elmqvist, T., C. Folke, M. Nystro
¨m, G. Peterson, J. Bengtsson,
B. Walker, and J. Norberg. 2003. Response diversity,
ecosystem change, and resilience. Frontiers in Ecology and
the Environment 1:488–494.
Filippi-Codaccioni, O., V. Devictor, Y. Bas, and R. Julliard.
2010. Toward more concern for specialisation and less species
diversity in conserving farmland biodiversity. Biological
Conservation 143:1493–1500.
Fischer, M., et al. 2010. Implementing large-scale and long-
term functional biodiversity research: the Biodiversity
Exploratories. Basic and Applied Ecology 11:473–485.
February 2014 473PLANT–POLLINATOR NETWORKS AND LAND-USE
Fru
¨nd, J., K. E. Linsenmair, and N. Blu
¨thgen. 2010. Pollinator
diversity and specialization in relation to flower diversity.
Oikos 119:1581–1590.
Gathmann, A., and T. Tscharntke. 2002. Foraging ranges of
solitary bees. Journal of Animal Ecology 71:757–764.
Goulson, D., G. C. Lye, and B. Darvill. 2008. The decline and
conservation of bumblebees. Annual Review of Entomology
53:191–208.
Grindeland, J. M., N. Sletvold, and R. A. Ims. 2005. Effects of
floral display size and plant density on pollinator visitation
rate in a natural population of Digitalis purpurea. Functional
Ecology 19:383–390.
Hoehn, P., T. Tscharntke, J. M. Tylianakis, and I. Steffan-
Dewenter. 2008. Functional group diversity of bee pollina-
tors increases crop yield. Proceedings of the Royal Society B
275:2283–2291.
James, A., J. W. Pitchford, and M. J. Plank. 2012. Distangeling
nestedness from models of ecological complexity. Nature
487:227–230.
Jauker, F., T. Dieko
¨tter, F. Schwarzbach, and V. Wolters.
2009. Pollinator dispersal in an agricultural matrix: opposing
responses of wild bees and hoverflies to landscape structure
and distance from main habitat. Landscape Ecology 24:547–
555.
Johst, K., M. Drechsler, J. Thomas, and J. Settele. 2006.
Influence of mowing on the persistence of two endangered
large blue butterfly species. Journal of Applied Ecology 43:
333–342.
Kalisz, S., D. W. Vogler, and K. Hanley. 2004. Context-
dependent autonomous self-fertilization yields reproductive
assurance and mixed mating. Nature 430:884 –887.
Kleijn, D., and I. Raemakers. 2008. A retrospective analysis of
pollen host plant use by stable and declining bumble bee
species. Ecology 89:1811–1823.
Klein, A.-M., I. Steffan-Dewenter, and T. Tscharntke. 2003.
Fruit set of highland coffee increases with the diversity of
pollinating bees. Proceedings of the Royal Society B 270:955–
961.
Klotz, S., I. Ku
¨hn, and W. Durka. 2002. Bioflor: eine
Datenbank mit biologisch-o
¨kologischen Merkmalen zur
Flora von Deutschland. Bundesamt fu
¨r Natuschutz, Bonn,
Germany.
Koh, L. P. 2004. Species coextinction and the biodiversity crisis.
Science 305:1632–1634.
Kotze, D. J., and R. B. O’Hara. 2003. Species decline—but
why? Explanations of carabid beetle (Coleoptera, Carabidae)
declines in Europe. Oecologia 135:138–148.
Kunin, W. E. 1997. Population size and density effects in
pollination: pollinator foraging an plant reproductive success
in experimental arrays of Brassica kaber. Journal of Ecology
85:225–234.
Kwaiser, K. S., and S. D. Hendrix. 2007. Diversity and
abundance of bees (Hymenoptera: Apiformes) in native and
ruderal grasslands of agriculturally dominated landscapes.
Agriculture, Ecosystems and Environment 124:200–204.
Laliberte, E., et al. 2013. Land-use intensification reduces
functional redundancy and response diversity in plant
communities. Ecology Letters 13:76–86.
Le Fe
´on, V., A. Schermann-Lgionnett, Y. Delettre, S. Aviron,
R. Billeter, R. Bugter, F. Hendrickx, and F. Burel. 2010.
Intensification of agriculture, landscape composition and
wild bee communities: a large scale study from European
countries. Agriculture, Ecosystems and Environment 137:
143–150.
Loreau, M., et al. 2001. Biodiversity and ecosystem functioning:
current knowledge and future challenges. Science 294:804
808.
McKinney, M. L. 1997. Extinction vulnerability and selectivity:
combining ecological and paleontological views. Annual
Review of Ecology and Systematics 28:495–516.
Memmott, J., P. G. Craze, N. M. Waser, and M. V. Price. 2007.
Global warming and the disruption of plant–pollinator
interactions. Ecology Letters 10:710–717.
Montoya, J. M., S. L. Pimm, and R. V. Sole
´. 2006. Ecological
networks and their fragility. Nature 442:259–264.
Ollerton, J., R. Winfree, and S. Tarrant. 2011. How many
flowering plants are pollinated by animals? Oikos 120:321–
326.
Pauw, A. 2007. Collapse of a pollination web in small
conservation areas. Ecology 88:1759–1769.
Pocock, M. J. O., D. M. Evans, and J. Memmott. 2012. The
robustness and restoration of a network of ecological
networks. Science 335:973–977.
Potts, S. G., B. Vulliamy, S. Roberts, C. O’Toole, A. Dafni, G.
Ne’eman, and P. Willmer. 2005. Role of nesting resources in
organising diverse bee communities in a Mediterranean
landscape. Ecological Entomology 30:78–85.
Praz, C. J., A. Mu
¨ller, and S. Dorn. 2008. Specialized bees fail
to develop on non-host pollen: Do plants chemically protect
their pollen? Ecology 89:795–804.
R Development Core Team. 2012. R 2.15.1. R Project for
Statistical Computing, Vienna, Austria. www.r-project.org
Strickler, K. 1979. Specialization and foraging efficiency of
solitary bees Hoplitis anthocopoides. Ecology 60:998–1009.
Tudor, O., R. L. H. Dennis, J. N. Greatorex-Davies, and T. H.
Sparks. 2004. Flower preferences of woodland butterflies in
the UK: nectaring specialists are species of conservation
concern. Biological Conservation 119:397–403.
Tylianakis, J. M., T. Tscharntke, and O. T. Lewis. 2007.
Habitat modification alters the structure of tropical host–
parasitoid food webs. Nature 445:202–205.
Vamosi, J., T. M. Knight, J. A. Steets, S. J. Mazer, M. Burd,
and T. L. Ashmann. 2006. Pollination decays in biodiversity
hotspots. Proceedings of the National Academy of Sciences
USA 103:956–961.
Va
´zquez, D. P., N. Chacoff, and L. Cagnolo. 2009. Evaluating
multiple determinants of the structure of mutualistic net-
works: comment. Ecology 90:2039–2046.
Va
´zquez, D. P., and D. Simberloff. 2002. Ecological speciali-
zation and susceptibility to disturbance: conjectures and
refutations. American Naturalist 159:606– 623.
Weiner, C., M. Werner, K. E. Linsenmair, and N. Blu
¨thgen.
2011. Land-use intensity in grasslands: changes in biodiver-
sity, species composition and specialization in flower-visitor
networks. Basic and Applied Ecology 12:292–299.
Winfree, R., T. Griswold, and C. Kremen. 2007. Effect of
human disturbance on bee communities in a forested
ecosystem. Conservation Biology 21:213–223.
SUPPLEMENTAL MATERIAL
Appendix
Specialization metrics, land use responses, and species lists (Ecological Archives E095-041-A1).
CHRISTIANE NATALIE WEINER ET AL.474 Ecology, Vol. 95, No. 2
... Adults of these flies are abundant in a broad range of habitats (e.g. Pimentel & Epstein, 1960;Szpila, 1999;Heath et al., 2004) and they often constitute an important part of plant-pollinator communities (Jędrzejewska-Szmek & Zych, 2013;Weiner et al., 2014;Howlett et al., 2016;Rader et al. 2020). The majority of Pollenia species overwinter as adults, often entering human dwellings en masse during the autumn (Pimentel & Epstein, 1960;Heath et al., 2004;Vezsenyi et al., 2022). ...
... Another problem for morphology-based delimitation may be cryptic variation, which is plausible because insects often speciate based on sexually selected traits, such as pheromones, acoustic signals (Henry, 1994) or by host jumping (Huyse et al., 2005). A high level of expertise and considerable time is necessary for morphological identification of Pollenia specimens, which presents a practical problem for researchers, for example, carrying out studies related to plant-pollinator interactions or carrion insect assemblages (Weiner et al., 2014;Szpila, 2017). ...
Article
Cluster flies of the genus Pollenia are known as mass invaders of human dwellings, but are important plant pollinators in the temperate climatic zone. Despite being the most species-rich and widespread genus in Polleniidae, no study to date has tested infrageneric relationships using molecular data. Here we use three molecular markers, COI, Ef-1α and CAD to reconstruct the phylogenetic relationships between 18 West Palaearctic species of Pollenia, representing eight predefined morphological species groups, using both maximum likelihood and Bayesian approaches. We show several instances where morphological and molecular results are congruent, but also instances where they are discordant. We develop a COI barcode reference library for 18 species, containing newly generated data (87 sequences) and sequences retrieved from the Barcode of Life Data System (BOLD). We analyse this dataset using both Automatic Barcode Gap Discovery (ABGD) and Bayesian Phylogenetics & Phylogeography (BPP) methods to validate morphological species hypotheses and delimit species. The results of these species delimitation analyses were, in most cases, identical and aligned with predefined morphological species concepts. Based on the results of our analyses, we synonymize P. moravica (stat. rev.) with P. amentaria and assign 191 unidentified sequences from BOLD to named morphospecies.
... However, endemic plant species of Kashmir with less pollinator interactions and strong dependence on them (e.g. dioecious species) may be the most sensitive to pollinator loss and can face co-extinction (Weiner et al., 2014;Portman et al., 2018). Extinction of pollinator hubs and connectors (here Apis spp.) may result in breakdown of modules and networks and thus co-extinction (Geslin et al., 2013). ...
Article
Plant-pollinator studies are increasingly using network analysis to investigate the structure and function of such communities. However, many areas of high diversity largely remained unexplored in this way. Our study describes a plant-pollinator meta-network from an overlooked biodiversity hotspot, the Kashmir Himalaya, where we specifically investigate plant-pollinator network nestedness and modularity, as well as the influence of alien species and the impacts of simulating species extinctions on network structure. Natural history observations were used to document the meta-network between 230 plant and 80 pollinator species forming 1958 (11% of the possible) interactions. Among the plants Malus domestica and among the pollinators Apis mellifera and A. cerana formed the largest number of interactions with significant influence over the whole network. Network cumulative degree distribution depicted a higher number of degree levels in pollinators than plants. A moderately high number of realized interactions were revealed, thereby indicating potential structural and functional stability in the network. Eight strongly defined modules were observed in the network which varied in their composition. For example, the Ephedra module exclusively comprised of native species whereas the Apis module comprised of all the four different types of interacting species (i.e. native and alien plants and pollinators) and also integrated the highest number of alien species. In the network overall, 40% of interactions were by alien species, reflecting how well these were integrated. Extinction simulations suggested that the network would collapse more quickly when the most connected pollinators are removed, rather than the most connected plant species. Our study is the first assessment of a plant-pollinator network from the Himalayan biodiversity hotspot; and will help to inform the ecological and economic implications of plant-pollinator interactions in an era of global biodiversity crisis.
... El cambio del uso de la tierra de ambientes naturales a sistemas productivos suele reducir la diversidad de especies y la complejidad de las interacciones bióticas (Weiner et al. 2014). En particular, los usos intensivos de la tierra pueden afectar a la diversidad de los organismos y los servicios ecosistémicos asociados a las interacciones depredador-presa (Zhao et al. 2015), por ejemplo, generando un aumento en los eventos de brotes de plagas agrícolas por disminución de la diversidad y la abundancia de depredadores (Chaplin-Kramer et al. 2013;Zhao et al. 2013;Prieto-Benítez and Méndez 2011). ...
... We included nesting habit, season of active foraging, length of active season, and pollen specialization (Table 2). These traits are important descriptors of bee ecology and can be predictors of bee community stability (De Palma et al. 2015, Grundel et al. 2010, Hopfenmüller et al. 2014, Michener 2000, Moretti et al. 2009, Weiner et al. 2014. ...
Full-text available
Article
To examine changes in bee communities and bee-flower relations in the Prairie Pothole Region of the Northern Great Plains, we compared bee specimens and their floral associations collected in eastern North Dakota during 2010-2012 to bee specimens and their floral associations collected from the same region during 1910-1920 by pioneering naturalist Orin Alva Stevens. We also examined citizen science photographic records from 2012-2021. Using rarefaction, we found similar estimated bee species richness between the 1910s (135.98 ± 9.82) and the 2010s (125.42 ± 8.14). Bumble bees were less frequently present in collecting events in the 2010s, with one bumble bee species, Bombus terricola, declining from 7% presence in collecting events in the 1910s to 0.4% in the 2010s. Hylaeus annulatus, Andrena miranda, and Hesperapis carinata were each in the top 25% of species most frequently present in collecting events in the 1910s but were absent in the 2010s. Citizen science images documented range expansions for Bombus impatiens and the non-native Anthidium manicatum. Based on the floral association data, we recommend that pollinator plantings include (1) flowers that were formerly common in bee association records but that had decreased presence or were absent from modern collections and (2) flowers visited by possibly declining bee species, as indicated by historic flower associations for bee species that were absent or less frequently present in modern collecting events. The persistence of many bee species, including those of conservation concern, in agriculturally dominated landscapes points to the importance of restoring key floral resources to wide-ranging habitats.
... Increased floral diversity has been found to increase pollinator visitation and large diverse pollen rewards increased the likelihood of visits by hymenopteran and dipteran pollinators (Harder 1990;Makino et al. 2007;Semere and Slater 2007;Vaudo et al. 2015). Diversity in the timing of flowering can also provide resources throughout the season to support more abundant and diverse pollinator communities (Harder 1990;Makino et al. 2007;Weiner et al. 2014;Pyke 2016). Relative to the native and restored areas, the invaded site likely had a much lower potential nutritional reward for pollinators, as reed canary grass only flowers until early July and is wind-pollinated (Merigliano and Lesica 1998;Runkel et al. 2009). ...
Article
Pollinator species have seen recent declines in abundance, generating conservation concern as well as alarm about the ecosystem services they provide. A common approach to alleviate pollinator decline is through habitat management, including restoration of degraded habitats and removal of invasive species, but apparent habitat improvement does not necessarily mean an improvement in pollinator abundance and diversity. We collected pollinators in colored pan traps at three sites at the Lacamas Prairie Natural Area, Washington: remnant wet prairie, restored wet prairie, and an area invaded by reed canary grass (Phalaris arundinacea). We used model selection to assess whether site and trap color explained variation in pollinator abundance, richness, and diversity. Pollinator abundance was similar at the native and restored sites with predicted averages of 9.06 (7.15, 11.48) and 9.51 (7.52, 12.03), respectively while a heavily invaded reed canary grass site had a significantly lower predicted mean of 7.26 (5.69, 9.26). Site was not included in the top model for species richness or diversity. All three measures varied with trap color. Habitat restoration and invasive species control at Lacamas Prairie appear to have benefited local pollinator populations, but evidence for differences in pollinator richness and diversity was weak. Further work, both characterizing the response of pollinator communities to wet prairie restoration and optimizing trap colors for monitoring in this area, is warranted.
... Conventional monitoring is often restricted in terms of comparing multiple communities, requires a high time investment to document the presence or absence of pollinator species, and is reliant on dwindling taxonomic expertise to identify observed pollinators (Sheffield et al., 2009;Tur et al., 2013;Weiner et al., 2014). Moreover, monitoring the overwhelming majority of pollinator species is unrealistic (Didham et al., 2020;Young et al., 2017). ...
Full-text available
Article
Pollinators are declining globally, and this loss can reduce plant reproduction, erode critical ecosystem services and resilience, and drive economic losses. Monitoring pol-linator biodiversity trends is essential for adaptive conservation and management, but conventional surveys are often costly, time-consuming, and requires considerable taxonomic expertise. Environmental DNA (eDNA) metabarcoding surveys are booming due to their rapidity, nondestructiveness, and cost efficiency. Microfluidic technology allows multiple primer sets from different markers to be used in eDNA metabarcoding for more comprehensive inventories, minimizing associated primer bias. We evaluated microfluidic eDNA metabarcoding for pollinator community monitoring in both controlled greenhouse and natural field settings. Using a variety of sampling , preservation, and extraction methods, we assessed pollinator communities with a number of markers using microfluidic metabarcoding. In greenhouse experiments, microfluidic eDNA metabarcoding detected the target bumblebee in two of four focal flower species as well as greenhouse insects in all focal flower species. In the field, numerous common regional arthropods, including some directly observed, were detected. Pollinator detection was maximized using whole flower heads preserved in ATL buffer and extracted with a modified Qiagen® DNeasy protocol for amplification with COI primers. eDNA surveillance could enhance pollinator assessment by detecting protected and endangered species and being more applicable to remote, inaccessible locations, whilst reducing survey time, effort, and expense. Microfluidic eDNA metabarcoding requires optimization to address remaining efficacy concerns, but this approach shows potential in revealing complex networks underpinning critical ecosystem functions and services, enabling more accurate assessments of ecosystem resilience. K E Y W O R D S arthropods, community ecology, ecosystem assessment, eDNA, mutualistic interactions, pollinators 26374943, 0, Downloaded from https://onlinelibrary.wiley.com
... Studies on the effects of landscape changes on plant-pollinator networks have identified that the distance to the forest patch and forest cover can change the structure of visitation networks (Ferreira et al., 2020;Sritongchuay et al., 2019bSritongchuay et al., , 2019a. These effects could be associated with the loss of specialist pollinator species in smallholder orchards with less forest cover and/or to changes in diet breadth of pollinators in response to resource availability (Weiner et al., 2014). The abundance of generalist pollinators tended to increase with forest loss, perhaps ...
Full-text available
Article
There is a global concern of pollinator declines and linked ecosystem service losses. However, although land-use changes are a primary threat to biodiversity, how land-use change affects pollinator communities, pollination networks and fruit-set of food crops is poorly understood. The impact of land-use changes is especially understudied in tropical systems, even though most tropical crops are highly dependent on animal pollination. Using 40 sites to investigate diurnal and nocturnal flower visitors in small-scale agroecosystems across land-use gradients in Thailand and tropical South-western China, we show that habitat structure shapes pollinator communities at local (floral species richness) and landscape level (percentage of tree plantation in a 500 m radius and percentage forest in a 5 km radius), influencing both the species richness of pollinators and their visitation rates. These, in turn, alter plant-pollinator network structure: community-level specialization increases with floral species richness and percentage of forest cover. However, the specialization decreases with percentage of tree plantation, illustrating that natural habitat better supports specialized species. Furthermore, fruit-sets of several crops were affected by land-use. Notably, fruit-set of mango was positively associated with the percentage of forest cover in the surrounding landscape. These findings reveal how land-use influence pollinator communities and highlight how natural habitats may safeguard ecosystem services.
... The most drought-sensitive species, T. vulgaris, was too rare in our system to quantify pollinator visits and therefore to assess the impact of reduced nectar production under drought on pollinator communities. If a similar impact of drought on T. vulgaris was confirmed in a more open habitat where this species is abundant (eg, in a similar shrubland 20 km away; Ropars et al., 2020a), this could negatively affect pollinator populations (Weiner et al., 2014). In a nearby site, T. vulgaris was shown to support 14 flower-visiting species, including two with a potentially high dependence on T. vulgaris (Ropars et al., 2020a). ...
Full-text available
Article
1. Pollinators are declining globally, with climate change implicated as an important driver. Climate change can induce phenological shifts and reduce floral resources for pollinators, but little is known about its effects on floral attractiveness and how this might cascade to affect pollinators, pollination functions and plant fitness. 2. We used an in situ long‐term drought experiment to investigate multiple impacts of reduced precipitation in a natural Mediterranean shrubland, a habitat where climate change is predicted to increase the frequency and intensity of droughts. Focusing on three insect‐pollinated plant species that provide abundant rewards and support a diversity of pollinators (Cistus albidus, Salvia rosmarinus and Thymus vulgaris), we investigated the effects of drought on a suite of floral traits including nectar production and floral scent. We also measured the impact of reduced rainfall on pollinator visits, fruit set and germination in S. rosmarinus and C. albidus. 3. Drought altered floral emissions of all three plant species qualitatively, and reduced nectar production in T. vulgaris only. Apis mellifera and Bombus gr. terrestris visited more flowers in control plots than drought plots, while small wild bees visited more flowers in drought plots than control plots. Pollinator species richness did not differ significantly between treatments. Fruit set and seed set in S. rosmarinus and C. albidus did not differ significantly between control and drought plots, but seeds from drought plots had slower germination for S. rosmarinus and marginally lower germination success in C. albidus. 5. Synthesis. Overall, we found limited but consistent impacts of a moderate experimental drought on floral phenotype, plant reproduction and pollinator visits. Increased aridity under climate change is predicted to be stronger than the level assessed in the present study. Drought impacts will likely be stronger and this could profoundly affect the structure and functioning of plant‐pollinator networks in Mediterranean ecosystems.
Full-text available
Article
Research on plant-pollinator interactions requires a diversity of perspectives and approaches, and documenting changing pollinator-plant interactions due to declining insect diversity and climate change is especially challenging. Natural history collections are increasingly important for such research and can provide ecological information across broad spatial and temporal scales. Here, we describe novel approaches that integrate museum specimens from insect and plant collections with field observations to quantify pollen networks over large spatial and temporal gradients. We present methodological strategies for evaluating insect-pollen network parameters based on pollen collected from museum insect specimens. These methods provide insight into spatial and temporal variation in pollen-insect interactions and complement other approaches to studying pollination, such as pollinator observation networks and flower enclosure experiments. We present example data from butterfly pollen networks over the past century in the Great Basin Desert and Sierra Nevada Mountains, United States. Complementary to these approaches, we describe rapid pollen identification methods that can increase speed and accuracy of taxonomic determinations, using pollen grains collected from herbarium specimens. As an example, we describe a convolutional neural network (CNN) to automate identification of pollen. We extracted images of pollen grains from 21 common species from herbarium specimens at the University of Nevada Reno (RENO). The CNN model achieved exceptional accuracy of identification, with a correct classification rate of 98.8%. These and similar approaches can transform the way we estimate pollination network parameters and greatly change inferences from existing networks, which have exploded over the past few decades. These techniques also allow us to address critical ecological questions related to mutualistic networks, community ecology, and conservation biology. Museum collections remain a bountiful source of data for biodiversity science and understanding global change.
Full-text available
Article
As plant populations decrease in size, reduced seed set may contribute to their ultimate extirpation. In this study, effects of pollen quantity and compatibility relationships (quality) on seed set were investigated in a rare species (Eupatorium resinosum) and a closely related common species (E. perfoliatum). The impact of pollen quantity was studied through pollen supplementation experiments in two populations of each species. Addition of pollen increased seed set only in the smaller population off. resinosum Compatibility relationships (pollen quality) were investigated in a diallel crossing experiment using ten genotypes from the same populations. Plants from the smaller population of E. resinosum were found to be 40% cross-incompatible, which was higher than the larger population off. resinosum and the two populations off. perfoliatum, the latter showing signs of self-compatibility in some individuals. In addition the variance in number of compatible matings per individual was higher in the smaller population off. resinosum. These results are consistent with a computer simulation model that investigated the effect of small population size on S-allele diversity. Sufficient pollination accompanied by a partial breakdown of the incompatibility system may account, in part, for the relative success of E. perfoliatum.
Full-text available
Article
Both the number and the density of flowering plants in a population can be important determinants of pollinator abundance and behavior. We report the joint effects of population size and density on pollinator visitation and pollination success for Lupinus perennis (Fabaceae). Focusing on five pairs of populations, we matched one small population (125-800 flowering plants) with one distinctly larger population (1000-3000 flowering plants). In these pairs, population size did not affect pollinator communities or pollination success. All measures of pollination success increased significantly with density. Only bee behavior (number of flowers probed per inflorescence) exhibited a significant interaction of size and density. Testing whether population sizes smaller than those in the paired populations might affect pollination, we gathered pollen tube samples from 14 unpaired populations (16-215 flowering plants). Combining these data with those from the paired populations revealed a significant decrease in pollination for smaller populations, indicating that effects of population size may be detectable only when populations smaller than a few hundred plants are sampled. We found that effects of density are consistent and much stronger than those of population size. Our results suggest that both size and density of natural populations should be considered in designing restoration and reintroduction programs for this threatened plant.
Article
1 The term 'density-dependence' is often applied rather loosely to a variety of aspects of local abundance. 'Density' is most commonly measured as the size of a local population and/or the (average) spacing between the individuals within it. These parameters are interrelated and correlated in most natural populations. Yet species interactions and population dynamics may be affected differently by these different aspects of abundance. 2 Field experiments were performed to test the effects of two components of local abundance on pollination in the self-incompatible annual plant. Brassica kaber. In one experiment, populations of uniform density but differing size were planted out, whilst in a second study both the density and size of populations were varied. 3 The number of individuals in a population had no effect on pollinator visitation or subsequent seed set in either experiment. 4 Population density, however, had strong effects on both visitation and reproductive success. 5 The position of a plant within a population had an impact on pollinator constancy in the second experiment, but had no effect on visitation rates or reproductive success.
Article
The specialist bee, Hoplitis anthocopoides, foraged for pollen from Echium vulgare, its preferred plant, more efficiently than did four generalist species. Efficiency was measured as the weight of pollen (the larval food) harvested from Echium flowers per unit handling time, divided by the weight of the discrete pollen mass required to rear one offspring. This measure of efficiency corresponds more closely to reproductive output than does the usual measure, net energy gained per unit time. The specialists produced more potential offspring per unit handling time because they manipulated flowers faster and collected more pollen per flower than did generalists. The specialists also flew between flowers more rapidly than did the generalists. The specialists did not defend the flowers against generalists. These results support the assumption in models of resource partitioning and optimal foraging theory, and in hypotheses explaining the evolution of pollen-specializing bee species, that specialists are more efficient at using their preferred resources than are generalists.
Article
The ecological consequences of biodiversity loss have aroused considerable interest and controversy during the past decade. Major advances have been made in describing the relationship between species diversity and ecosystem processes, in identifying functionally important species, and in revealing underlying mechanisms. There is, however, uncertainty as to how results obtained in recent experiments scale up to landscape and regional levels and generalize across ecosystem types and processes. Larger numbers of species are probably needed to reduce temporal variability in ecosystem processes in changing environments. A major future challenge is to determine how biodiversity dynamics, ecosystem processes, and abiotic factors interact.
Article
This study examined bee communities by sweep-net and pan-trap sampling and quantified the number of ramets of floral resources in native tallgrass prairie fragments and nearby ruderal areas (within 2.1km) in Iowa, USA in the summer of 2004. Bee communities in ruderal areas were significantly less diverse than those in native tallgrass prairie remnants, with about half as many species and approximately a third as many bees. Diversity, abundance, and richness of floral resources were also significantly less in ruderal grasslands than in native prairies, indicating that poor floral resource levels may substantially depauperate their bee communities. Common bees dominated the composition of the ruderal grasslands; only one rare species in this study was found at a ruderal site, indicating that high-quality prairie remnants are important reservoirs of bee diversity. Abundance of flowering ramets of a plant species was a significant predictor of the abundance of bees found on that plant. There was also a preference for human-yellow flowers after adjusting for ramet abundance and there were significantly more bees caught in yellow pan traps than blue or white ones. The abundance, but not the richness, of small bee species (length≤7.5mm) was less than expected at ruderal sites when compared to prairies, implying the presence of local nesting opportunities in ruderal grasslands for small bees but insufficient resources to support large populations.
Article
The evolution of self-fertilization in hermaphrodites is opposed by costs that decrease the value of self progeny relative to that of outcross progeny1, 2, 3. However, self-fertilization is common in plants4; 20% are highly selfing and 33% are intermediate between selfing and outcrossing5. Darwin6 proposed an adaptive benefit of self-pollination in providing reproductive assurance when outcrossing is impossible6, 7, 8, 9. Moreover, if outcross pollen receipt is inconsistent within or between years, these conditions likewise favour self-pollination10, and this can result in a mixture of self and outcross seed production (mixed mating). Despite wide acceptance, the reproductive assurance hypothesis has lacked the support of complete empirical evidence to show that variable pollination can create both the ecological and genetic conditions favouring self-pollination. We recently showed in Collinsia verna that during periods of infrequent pollinator visits, autonomous self-pollination boosted seed output per flower11, the key ecological condition. Here we show low inbreeding depression and marker-based estimates of selfing, demonstrating that when the pollination environment in wild populations necessitates reproductive assurance, selfing rates increase. We provide a complete demonstration of reproductive assurance under variable pollination environments and mechanistically link reproductive assurance to intermediate selfing rates through mixed mating.