Non-bee insects are important contributors to global

crop pollination
Romina Radera,1, Ignasi Bartomeusb, Lucas A. Garibaldic,d, Michael P. D. Garratte, Brad G. Howlettf, Rachael Winfreeg,
Saul A. Cunninghamh, Margaret M. Mayfieldi,j, Anthony D. Arthurk, Georg K. S. Anderssonl, Riccardo Bommarcom,
Claire Brittainn, Luísa G. Carvalheiroo,p,q, Natacha P. Chacoffr, Martin H. Entlings, Benjamin Foullya, Breno M. Freitast,
Barbara Gemmill-Herrenu, Jaboury Ghazoulv, Sean R. Griffing, Caroline L. Grossa, Lina Herbertssonl, Felix Herzogw,
Juliana Hipólitox, Sue Jaggara, Frank Jaukery, Alexandra-Maria Kleinz, David Kleijnaa, Smitha Krishnanv,
Camila Q. Lemost, Sandra A. M. Lindströmk,bb,cc, Yael Mandelikdd,ee, Victor M. Monteirot, Warrick Nelsonf,
Lovisa Nilssonl, David E. Pattemoref, Natália de O. Pereirat, Gideon Pisantydd,ee, Simon G. Pottse, Menno Reemerff,
Maj Rundlöfbb, Cory S. Sheffieldgg, Jeroen Scheperhh,ii, Christof Schüepps,jj, Henrik G. Smithl,bb, Dara A. Stanleykk,ll,mm,
Jane C. Stoutll,mm, Hajnalka Szentgyörgyinn,oo, Hisatomo Takipp, Carlos H. Vergaraqq, Blandina F. Vianax,
and Michal Woyciechowskinn
a
School of Environmental and Rural Science, University of New England, Armidale, 2350, NSW Australia; bDepartment of Integrative Ecology, Estación
Biológica de Doñana, Isla de la Cartuja, 41092, Seville, Spain; cGrupo de Investigación en Agroecología, Sede Andina, Universidad Nacional de Río Negro,
Mitre 630, 8400 San Carlos de Bariloche, Río Negro, Argentina; dConsejo Nacional de Investigaciones Científicas y Técnicas, 8400 San Carlos de Bariloche,
Argentina; eCentre for Agri-Environmental Research, School of Agriculture, Policy and Development, Reading University, Reading, RG6 6AR, United
Kingdom; fThe New Zealand Institute for Plant and Food Research Ltd., 8140 Christchurch, New Zealand; gDepartment of Ecology, Evolution and Natural
Resources, Rutgers University, New Brunswick, NJ 08901; hCommonwealth Scientific and Industrial Research Organisation Land and Water Flagship,
Canberra, ACT 2601, Australia; iSchool of Biological Sciences, The University of Queensland, Brisbane, QLD 4072, Australia; jThe Ecology Centre, The
University of Queensland, Brisbane, QLD 4072 Australia; kAustralian Bureau of Agricultural and Resource Economics and Sciences, Department of
Agriculture, Canberra, ACT 2601, Australia; lCentre for Environmental and Climate Research, Lund University, SE-223 62 Lund, Sweden; mDepartment of

ECOLOGY
Ecology, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden; nDepartment of Entomology, University of California, Davis, CA 95616;
o
Departamento de Ecologia, Campus Universitário Darcy Ribeiro, Universidade de Brasília, Brasilia, Federal District, 70910-900, Brazil; pNaturalis Biodiversity
Center, 2333 CR Leiden, The Netherlands; qCentre for Ecology, Evolution and Environmental Changes, Faculdade de Ciencias, Universidade de Lisboa, 1649-
004 Lisbon, Portugal; rInstituto de Ecologia Regional, Facultad de Ciencias Naturales e Instituto Miguel Lillo, Universidad Nacional de Tucumán, 4000 San
Miguel de Tucumán, Tucumán, Argentina; sInstitute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany; tDepartamento
de Zootecnia, Centro de Ciencias Agrarias, Universidade Federal do Ceará, 60.356-000, Fortaleza, Ceara, Brazil; uSustainable Agriculture, Plant Production
and Protection Division, Agriculture and Consumer Protection Department, Food and Agricultural Organization of the United Nations, Rome 00153, Italy;
v
Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zürich, 8092 Zurich, Switzerland; wAgroscope, Institute for
Sustainability Sciences INH, CH-8046 Zurich, Switzerland; xInstituto de Biologia, Universidade Federal da Bahia - Campus de Ondina, 40170-210 Salvador,
Bahia, Brasil; yDepartment of Animal Ecology, Justus Liebig University Giessen, D-35392 Giessen, Germany; zNature Conservation and Landscape Ecology,
Institute of Earth and Environmental Sciences, University of Freiburg, 79106 Freiburg, Germany; aaPlant Ecology and Nature Conservation Group,
Wageningen University, 6708 PB, Wageningen, The Netherlands; bbDepartment of Biology, Lund University, SE-223 62 Lund, Sweden; ccSwedish Rural
Economy and Agricultural Society in Kristianstad, S-291 09 Kristianstad, Sweden; ddDepartment of Entomology, The Hebrew University of Jerusalem,
Rehovot 7610001, Israel; eeSteinhardt Museum of Natural History and National Research Center, Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978,
Israel; ffNaturalis Biodiversity Center, European Invertebrate Survey - The Netherlands, 2300 RA Leiden, The Netherlands; ggRoyal Saskatchewan Museum,
Regina, SK, Canada S4P 2V7; hhResource Ecology Group, Wageningen University, 6708 PB, Wageningen, The Netherlands; iiAnimal Ecology Team, Alterra,
Wageningen University and Research Center, Droevendaalsesteeg 3a, 6708 PB, Wageningen, The Netherlands; jjInstitute of Ecology and Evolution,
Community Ecology, University of Bern, CH-3012 Bern, Switzerland; kkSchool of Biological Sciences, Royal Holloway University of London, Egham, Surrey,
TW20 0EX, United Kingdom; llSchool of Natural Sciences, Trinity College Dublin, Dublin 2, Republic of Ireland; mmTrinity Centre for Biodiversity Research,
Trinity College Dublin, Dublin 2, Republic of Ireland; nnInstitute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, 30-387 Krakow, Poland;
oo
Department of Pomology and Apiculture, University of Agriculture in Krakow, 31-425, Krakow, Poland; ppForestry and Forest Products Research Institute,
Tsukuba, Ibaraki 305-8687, Japan; and qqDepartamento de Ciencias Químico-Biológicas, Universidad de las Américas Puebla, Cholula, Puebla, Mexico

Edited by May R. Berenbaum, University of Illinois at Urbana-Champaign, Urbana, IL, and approved October 20, 2015 (received for review August 28, 2015)

Wild and managed bees are well documented as effective pollinators changes in land use. Non-bee insects provide a valuable service and
of global crops of economic importance. However, the contributions provide potential insurance against bee population declines.
by pollinators other than bees have been little explored despite their
potential to contribute to crop production and stability in the face of unmanaged pollinator | insect pollinator | fly | bee | beetle
environmental change. Non-bee pollinators include flies, beetles,
moths, butterflies, wasps, ants, birds, and bats, among others. Here
we focus on non-bee insects and synthesize 39 field studies from five
continents that directly measured the crop pollination services pro-
P ollinator-dependent crops are increasingly grown to provide
food, fiber, and fuel as well as micronutrients essential to

vided by non-bees, honey bees, and other bees to compare the

relative contributions of these taxa. Non-bees performed 25–50% of Author contributions: R.R. designed and coordinated the study, collated datasets and inter-
the total number of flower visits. Although non-bees were less effec- preted analyses, wrote the first draft of the manuscript, and is the corresponding and senior
author; I.B. assisted with the design of the study, conducted and interpreted analyses (with
tive pollinators than bees per flower visit, they made more visits; thus assistance from L.A.G.), discussed, and revised earlier versions of the manuscript; L.A.G., M.P.D.G.,
these two factors compensated for each other, resulting in pollination B.G.H., R.W., S.A.C., M.M.M., B.G.-H., and C.S.S. contributed data and discussed and revised
services rendered by non-bees that were similar to those provided by earlier versions of the project and manuscript; and A.D.A., G.K.S.A., R.B., C. B., L.G.C., N.P.C.,
M.H.E., B.F., B.M.F., J.G., S.R.G., C.L.G., L.H., F.H., J.H., S.J., F.J., A.-M.K., D.K., S.K., C.Q.L., S.A.M.L.,
bees. In the subset of studies that measured fruit set, fruit set in- Y.M., V.M.M., W.N., L.N., D.E.P., N.d.O.P., G.P., S.G.P., M. Reemer, M. Rundlöf, J.S., C.S., H.G.S.,
creased with non-bee insect visits independently of bee visitation D.A.S., J.C.S., H.S., H.T., C.H.V., B.F.V., and M.W. collected and formatted field data, and pro-
rates, indicating that non-bee insects provide a unique benefit that vided several important corrections to subsequent manuscript drafts.
is not provided by bees. We also show that non-bee insects are not as The authors declare no conflict of interest.
reliant as bees on the presence of remnant natural or seminatural This article is a PNAS Direct Submission.
habitat in the surrounding landscape. These results strongly suggest Freely available online through the PNAS open access option.
that non-bee insect pollinators play a significant role in global crop 1
To whom correspondence should be addressed. Email: rrader@une.edu.au.
production and respond differently than bees to landscape structure, This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
probably making their crop pollination services more robust to 1073/pnas.1517092112/-/DCSupplemental.

www.pnas.org/cgi/doi/10.1073/pnas.1517092112 PNAS Early Edition | 1 of 6

 differential responses to habitat proximity by bees and non-bees,
Significance if such exists, could provide an additional stabilizing effect on
crop-pollination services.
Many of the world’s crops are pollinated by insects, and bees are In summary, non-bees are often neglected as potential pro-
often assumed to be the most important pollinators. To our viders of crop ecosystem services by the scientific community and
knowledge, our study is the first quantitative evaluation of the by growers. In the data collection for the present synthesis, for
relative contribution of non-bee pollinators to global pollinator- example, 33% of the original 58 pollination studies we obtained
dependent crops. Across 39 studies we show that insects other did not record or distinguish non-bee pollinators from bee pol-
than bees are efficient pollinators providing 39% of visits to crop linators and thus had to be excluded.
flowers. A shift in perspective from a bee-only focus is needed for In this study we address the knowledge gap about non-bee
assessments of crop pollinator biodiversity and the economic value crop pollination and ask:
of pollination. These studies should also consider the services
provided by other types of insects, such as flies, wasps, beetles, and i) How does the crop pollination provided by non-bee insects
butterflies—important pollinators that are currently overlooked. compare with that provided by honey bees and other bees?
ii) How does the crop pollination provided by non-bees, honey
human health (1–5). The yield and quality of these crops benefit bees, and other bees translate into fruit/seed set?
to varying degrees from flower visitation by animals. The honey iii) Do non-bee crop pollinators respond similarly to bees with
bee, Apis mellifera L. (Hymenoptera: Apidae), is the most ver- regard to isolation from natural and semi/natural habitats?
satile, ubiquitous, and commonly used managed pollinator (6), To answer these questions, we compiled a dataset comprising
but the global reliance on this single pollinator species is a risky 39 studies of crop pollinators around the world and the polli-
strategy, especially given major threats to the health of managed nation services they provide (Table S1).
honey bee colonies because of poor nutrition, the ectoparasitic
mite Varroa destructor Anderson and Trueman (Mesostigmata: Results
Varroidae), and a number of other pests and diseases (7–10). Pollination Services Provided by Honey Bees, Other Bees, and Non-
However, honey bees are not the only insects that pollinate Bees. Flower-visitor assemblages were diverse, with representa-
crops. Apart from a few managed bee taxa, the great majority of tives from the orders Hymenoptera, Diptera, Lepidoptera, and
other pollinators are free-living or wild, providing an ecosystem
Coleoptera. Non-bee taxa included flies (Diptera: mainly domi-
service to crops. Wild pollinators other than honey bees recently
nated by Syrphidae, Calliphoridae, Tachinidae, Empididae, and
have been recognized for their role in increasing and stabilizing
Muscidae), butterflies and moths (Lepidoptera), and various beetle
crop-pollination services (11, 12). Wild bees are known to im-
families (Coleoptera) and hymenopterans including ants (For-
prove seed set, quality, shelf life, and commercial value of a
micidae) and wasps (Fig. S1). Bees observed in the studies included
variety of crops (13–17). Increasingly, studies indicate that insect
Apidae (e.g., Meliponini, Bombus spp., Xylocopini, and Cerati-
pollinators other than bees, such as flies, beetles, moths, and
nini), Halictidae, Colletidae, Megachilidae, and Andrenidae.
butterflies, are equally if not more important for the production
The total pollination services provided, which we calculated as
of some crops (18–24). Nonetheless, the contribution to crop
the product of visitation frequency and pollen deposition or fruit
pollination by non-bee insects has been largely unnoticed, with
set per visit (n = 9 studies) (56) did not differ significantly among
most global syntheses focusing on bees (25–28) or grouping to-
honey bees, other bees, and non-bees (Fig. 1A). On average,
gether all bee and non-bee wild-insect pollinators (11).
Diverse pollinator assemblages have been shown to increase non-bees accounted for 38% [confidence interval (CI): 29–49%],
pollination services as a result of complementary resource use honey bees for 39% (CI: 29–50%), and other bees for 23% (CI:
arising from variations in morphology and behavior among pol- 15–33%) of the visits to crop flowers (n = 37 studies) (Fig. 1B).
linator taxa (29, 30). For example, pollinator species may visit Visitation rates of other bees and non-bees were very weakly
different parts within a flower or inflorescence or different correlated (Pearson’s product–moment correlation: 0.22), and
flowers within a plant (high versus low flowers), improving the the visitation rates of non-bees and honey bees and of other bees
quality or quantity of pollination services overall (13, 31–33).
Non-bee taxa, in particular, often have broader temporal activity
ranges (34–36) and can provide pollination services at different A B C
times of the day compared with bees and in weather conditions
when bees are unable to forage (37–40). In addition, non-bee
taxa may be more efficient in transferring pollen for some crops honey bee a a

under certain conditions (18, 19, 38) and/or carry pollen further
other bees a b
distances than some bees (41). It has been suggested that this
long-distance pollen transfer could have important genetic conse- a a
non−bee
quences for wild plants (42, 43). However, there is little information
on the overall importance of the diverse group of non-bee wild
pollinators (but see refs. 39 and 44) and their importance to global −1.0 0.0 0.5 1.0 10 20 30 40 50 −2 −1 0 1 2
crop production.
Z−total effectiveness % visits Z−per visit effectiveness
Anthropogenic land use change and intensification are con-
sidered to be among the main drivers of bee declines (45, 46). Fig. 1. The contribution by honey bees, other bees, and non-bees to crop
One of the mechanisms underlying observed declines is thought pollination. Data from individual crop studies were standardized by z-scores
to be the loss of habitat that supports host plants (47) and nesting before analysis. (A) Pollination considered as a function of visits*single-visit
sites (48). However, different pollinator taxa respond differently effectiveness among guilds for the nine studies with effectiveness and visi-
tation data. Note that per capita effectiveness in each guild is measured only
to disturbances (49, 50). The proximity and area of natural
in a subset of dominant species in each study. (B) The contributions of dif-
habitat are often associated with higher crop flower visitation ferent insect groups to visitation (i.e., percentage of visits). (C) The relative
and bee diversity (25, 46, 51). Yet, although several studies have effectiveness of honey bees, other bees, and non-bees as measured by pollen
investigated the habitat requirements of non-bee taxa (52–55), deposition or fruit set per visit, combined across the 11 crop studies for
little is known about how habitat availability affects crop-polli- which data were available. Letters depict post hoc test differences (at P <
nation services from non-bee taxa (but see ref. 44). Thus, 0.05) among pollinator groups.

2 of 6 | www.pnas.org/cgi/doi/10.1073/pnas.1517092112 Rader et al.

 100 other
ants
80 Hemiptera
Coleoptera
Lepidoptera
% visits

60 Hymenoptera
other Diptera
Syrphidae

40 other bee
honey bee

20
0
Lowland coffee
Grapefruit
Watermelon A
Oilseed rape A
Watermelon B
Field bean
Highland coffee
Sunflower A
Strawberry
Kiwi
Apple A
Sunflower B
Oilseed rape B
Buckwheat A
Almond
Pear
Oilseed rape C
Oilseed rape D
Oilseed rape E
Onion (seed)
Oilseed rape F
Oilseed rape G
Turnip rape J
Apple B
Oilseed rape K
Buckwheat B
Turnip rape L
Mango A
Oilseed rape M
Carrot (seed)

Oilseed rape N
Cherry
Mango B
Mango C
Custard apple A
Custard apple B
Soursop
Fig. 2. The contribution of different
insect groups to flower visitation across
the 37 crop studies for which visitation
data were available. Crops are ordered,
left to right, from mostly bee-dominated
to mostly non-bee–dominated.

and honey bees were not correlated (0.02 and 0.04, respectively). 2.5% CI = −0.270, 97.5% CI = 0.182), whereas honey bee visits show
In contrast, the per-visit pollen deposition or fruit set (n = 11 no response to proximity to natural/seminatural vegetation (β =
studies) was significantly lower for non-bees than for either type 0.070, 2.5% CI = −0.161, 97.5% CI = 0.301).
of bee (Fig. 1C and Fig. S2). Thus, non-bees’ higher visitation
frequency and lower per visit effectiveness were compensatory, Discussion
resulting in levels of pollination-service delivery similar to that The clear importance of non-bees as global crop pollinators, as
provided by bees (Fig. 1A). shown in this study, illustrates how important the omission of

ECOLOGY
non-bees from crop pollination studies is to our understanding
Spatial Variation in Pollinator Community Composition. Observa- of crop-pollination services by wild insects. This crop pollina-
tions of insect visitation rates revealed that assemblage compo- tion role is in addition to the well-established contributions
sition varied across crop type and region (Fig. 2). Across the 37 that non-bees make to the reproduction of wild, native plant
crop studies, 31 recorded visits by all three groups of taxa, i.e.,
species (44, 57). Although on average the amount of pollen
honey bees, other bees (all species other than Apis mellifera), and
deposited per visit to crop flowers is lower for non-bees than
non-bees (Fig. 2). Two custard apple crops in Australia and
Brazil (Annona sp.) were visited exclusively by non-bee taxa. for bees, the high visitation frequency of non-bees to crop
Spatial variation in composition of the pollinator community flowers compensates for the deficit in per-visit effectiveness
resulted in some crops being visited by a more diverse group of and results in high pollination services overall (Fig. 1). Thus,
insects than others, even within the same crop type. For example,
pollinators of oilseed rape (Brassica napus) were surveyed in
Sweden, Germany, the United Kingdom, the Netherlands, Ire-
land, and Australia, and the contribution to visitation by non-
A B
bees differed markedly (5–80%) among these surveys. Even
within the three studies in Sweden (oilseed rape A, G, and M),
visitation by non-bees ranged from 5–60%, demonstrating that honey bee
location can have a strong influence, as can crop type, in de-
termining assemblage composition (Fig. 2).
other bees
Fruit/Seed Set. Higher visitation rates by non-bees and other bees
each enhanced crop fruit and seed set more so than similar in-
creases in visitation by honey bees (n = 19 studies) (Fig. 3A). In non−bee
fact, honey bee visitation was not correlated with fruit set, with
the average slope of this relationship centered on zero (β = −0.019,
2.5% CI = −0.164, 97.5% CI = 0.126), whereas non-bees show a
positive slope (β = 0.12) minimally overlapping with zero (2.5% −0.2 0.0 0.2 0.4 −0.6 −0.2 0.2 0.6
CI = −0.016, 97.5% CI = 0.265). The strongest relationship was
between other bee visitation and fruit set (β = 0.187, 2.5% CI = slope (fruit set) slope (isolation)
0.044, 97.5% CI = 0.330). Importantly, fruit set increased with Fig. 3. Regression coefficients (i.e., slopes ßi ± 95% CI) representing honey
non-bee visits independently of bee visitation rates, indicating bee, other bees, and non-bee contributions to overall fruit set and distance
that non-bee pollinators supplement rather than substitute for from natural/seminatural habitat. (A) Overall fruit set measured by seed set
bee visitation. Therefore both groups are required for optimal across 19 crop studies, estimated from the relationship between visitation
pollination services. and fruit set variation. Visitation by other bees increased fruit set (i.e., the
average slope is positive, and CIs for regression coefficients did not include
Response to Changes in Land Use. To test whether non-bees and zero). The average regression coefficients across crops for non-bees in-
bees respond differently to isolation from natural or seminatural creased fruit set (i.e., positive mean), but CIs minimally overlapped zero.
vegetation, we investigated the relationship between the proximity (B) Distance from natural/seminatural habitat was measured across 23
studies. Visitation by other bees was negatively related to distance from
to these features and the visitation rate of honey bees, other bees,
natural/seminatural habitat (i.e., the average slope is negative, CIs for re-
and non-bee taxa across 23 studies. When data across all crop gression coefficients did not include zero). Visitation by honey bees and non-
studies are considered, other bee visits declined sharply with in- bees was not related to distance from natural/seminatural habitat (i.e., the
creasing isolation from natural/seminatural vegetation (β = −0.263, average slope is negative, but confidence intervals overlapped zero for both
2.5% CI = −0.484, 97.5% CI = −0.042) (Fig. 3B). In contrast, taxa). Data from individual crop studies were standardized by z-scores be-
non-bee declines are moderate, and the CIs include zero (β = −0.049, fore analysis to permit direct comparison of slopes.

Rader et al. PNAS Early Edition | 3 of 6

our results are consistent with other studies that have found increasingly being recognized for their role in improving and
that visitation frequency drives the overall function provided stabilizing crop-pollination services (75). Here, we show that wild
by a species, because the variance across species in their flower pollinators other than bees also make substantial contributions
visitation is much larger than the variance in per-visit function to global crop-pollination services. This study demonstrates the
(28, 58). One outcome is that taxa with less efficient pollen importance of including non-bee pollinators in future crop-polli-
deposition may be the most important pollinators in certain nation surveys, pollination estimates, and pollinator-management
years or seasons when they are at high abundance relative to practices to ensure that we ascertain the relative contributions from
other taxa (28, 59, 60). all crop-pollinating taxa, over and above the well-known bee taxa.
Increased visitation by other bees and by non-bees each
enhanced crop fruit and seed set more than increased visitation Materials and Methods
by honey bees (Fig. 3A). Measuring this downstream outcome We analyzed data from 480 fields for 17 crops examined in 39 studies on five
variable is important, because pollen deposition does not continents. Fields ranged from extensive monocultures to small, diversified
necessarily lead to fruit set (61) [e.g., if pollinator visits are at systems (Tables S1 and S2). All crop studies that were included benefit in
saturating levels and result in flower damage or the transfer of some way from insect pollination. The protocols and identity of studies used
poor quality/incompatible pollen (62, 63)]. For example, in our to investigate the visitation rate, effectiveness, contribution to yield, and
response to natural or seminatural vegetation in each study are provided in
study, honey bees were good at depositing pollen in many
Tables S1 and S2. Across all the studies, 37 provided data on visitation fre-
crops, but increased honey bee visitation did not increase fruit
quency; 11 studies provided data on pollen transfer or fruit set per-visit
set, a result that other researchers (11, 64) also have found. In effectiveness; 19 studies provided data on seed or fruit set; and 23 provided
contrast, increased visits from other bees, as from non-bees, data on distance to natural/seminatural vegetation. Thirteen of the 39 crop
were associated with increased fruit set. As argued by Garibaldi studies have not been included in any previous synthesis on wild pollinator
et al. (11), these patterns suggest that the effect of other bees contributions to crop pollination.
and non-bees is additive to the effect of honey bees in the
datasets examined. Flower Visitation Frequency. To investigate the frequency with which non-
A final benefit of non-bees documented here is that they re- bees visit crop flowers in comparison with bees across our studies, we ob-
spond less negatively than bees to changes in land use (Fig. 3B). served flower visitors within standardized quadrats and transects and
Thus, where non-bees and bees pollinate the same crop, the measured flower visitation per unit of time for each insect species/group (37
presence of non-bees could help stabilize crop-pollination ser- studies). Pollinator observations were carried out during peak flowering. In
several studies, visitation was standardized with respect to a unit area or
vices against changes in land use through a mechanism known as
branch (because some crops have hundreds of small flowers per plant, visits
“response diversity” (49). Hence differences in responses among per flower could not be accurately assessed). We analyzed visitation by three
bee and non-bee taxa potentially could provide pollination “in- different groups: honey bees, other bees, and non-bees (i.e., all other insects).
surance” in the event of bee declines (33). Although other bees In this synthesis across all studies, we considered Apis mellifera as the only
responded positively to natural habitat, non-bees and honey species within the honey bee group for consistency across all datasets. Other
bees did not show a clear pattern, perhaps because most other bees Apis bees (e.g., Apis cerana indica) were pooled into the other-bee category.
are central place foragers, some of which require untilled ground We analyzed all feral and managed honey bees as a single group because
and sparsely vegetated ground for nesting. Other bees also require they cannot be distinguished during field observations. Feral honey bees
reliable, long-term pollen and nectar resources, and these habitat were uncommon in most studies except for those in South Africa and
features are associated with seminatural or natural vegetation (46). Argentina. The exact methods and numbers of sampling points surveyed in
each study are published elsewhere or are provided in the supporting in-
In contrast, many non-bee taxa have diverse nesting habits; e.g.,
formation (Table S1).
many flies lack central nest locations, and others are dependent on
floral resources only during adult life stages (65). For this diverse Effectiveness per Flower Visit. To investigate differences in per-visit effec-
group of insects the agricultural matrix may be more permeable tiveness among bee and non-bee taxa (11 studies) (Table S2), pollen de-
than it is for many bees (66). position on stigmatic surfaces (76) or fruit set after a single visit was
The diversity of life history strategies exhibited by non-bees estimated in fine weather conditions from pollination-effectiveness experi-
necessitates an approach to habitat management different from ments in which virgin inflorescences were bagged with a fine mesh to ex-
that used for bees to ensure that a wide range of foraging and clude pollinators. When bagged flowers opened, the bag was removed, and
nesting resources are available. For example, within the hov- the flowers were observed until an insect visited the flower and contacted
erfly family (Diptera: Syrphidae) the larvae of some species the stigma. The stigma then was removed by carefully severing it from the
feed on pollen (67), or aphids (65), or plant matter (68), or style using finely pointed forceps, and the pollen grains or pollen tubes were
counted after one visit by each insect. A variation of this method was used
dung, among other resources (69), but the adults usually are
for several crops (i.e., radish, kiwi, avocado, carrot, and watermelon), which
generalist flower visitors. Furthermore, at least some hoverfly involved removing the virgin flower and positioning it to allow visitation by
species appear to be less affected by changes in land use than particular taxa (Tables S1 and S2). Single-visit pollen-deposition values
bees, because many hoverfly species are able to use resources generally were available only for the dominant taxa; hence this analysis does
from highly modified habitats, including agricultural fields (44, not necessarily represent the effectiveness of entire communities.
46, 66). The variability among life histories may explain why
some non-bee pollinator populations are known to benefit from Calculating Total Pollination per Species. Total pollination is often considered
the same pollinator-enhancement practices as bees but others to be a function of both visitation frequency and per-visit effectiveness (56).
do not (54, 70, 71). We estimated total pollination for the nine studies in which these data were
There are several reasons why non-bees generally have been available. We used species-level visitation records and multiplied total visi-
overlooked in crop pollination studies until now. The diversity of tation of each group (i.e., honey bee, other bees, and non-bees) by the mean
per-visit pollen deposition of each group (Fig. 1).
families and the taxonomy of non-bee taxa are often poorly re-
solved (72, 73). Some non-bee taxa (such as flies and small wasps)
Fruit/Seed Set. To investigate differences in fruit set or seed set in relation to
move quickly and are difficult to follow in visual observations (e.g.,
visitation by bee and non-bee taxa (19 studies) (Table S2), we recorded the
transects). Further, many researchers have made the erroneous proportion of flowers that set fruit or the total number of fruits or seeds as a
assumption that non-bee taxa are unimportant to pollination, as measure of pollination success.
demonstrated by the 33% of studies reviewed that did not collect
data on non-bee taxa as an a priori decision. Isolation from Natural/Seminatural Habitat. Finally, to investigate the response
With the growing economic importance of crops that require of bees and non-bees to isolation from natural/seminatural vegetation, we
animal-mediated pollination (74), wild insect pollinators are calculated the linear distance (in kilometers) from each field site to the nearest

4 of 6 | www.pnas.org/cgi/doi/10.1073/pnas.1517092112 Rader et al.

patch of natural or seminatural vegetation (23 studies) (Table S2). For two with increased fruit set, the first model consisted of fruit set regressed
crops, almond and oilseed rape E, we transformed the percentage of semi- against total visitation of honey bees, other bees, and non-bees, with ran-
natural vegetation within a 1-km area to linear distances following ref. 12. dom intercepts for crop study. The second set of models included both
random intercepts and random slopes. A third set of models was run including
Study Selection. We initially contacted 58 data holders with the following pairwise interactions among the three groups and only random intercepts. The
criteria for inclusion of datasets in the synthesis: field studies must have set three models were compared using the Akaike information criterion (AIC) (84).
out to record all groups of pollinators (i.e., both bee and non-bee groups). The first model had the greatest support (AIC = 555) followed by both the
Studies were excluded that did not set out to record non-bees (n = 14) or that interaction model (ΔAIC = 5) and the random slopes model (ΔAIC = 4); hence
did not set out to record honey bees (n = 1). If a researcher stated that a
only the random intercept models are presented. Finally, to answer the third
systematic survey was performed with the aim of sampling all pollinators
question, visitation rate by each group was regressed against isolation from
(even though an entire group of pollinators was absent), we included that
natural habitats in a separate model with random intercepts as described
study. Finally, studies that included either bees or non-bees on an ad hoc
basis (rather than in a systematic survey) were excluded (n = 4). Although above. We present estimated slopes and CIs for all analyses (Table S4). To meet
the present study is limited to crop studies in which data were available for the assumptions of homoscedasticity, we used a constant variance function
non-bee taxa, we do include several crops for which bees are assumed to be when necessary. Variance inflation factors of the predictors were always below
the primary visitors, such as almond and watermelon (77, 78). Furthermore, 1.5, indicating no multicollinearity (85).
the ratio of bee- to non-bee–visited crops in the FAOSTAT crop database (6)
is comparable to the ratio investigated in this synthesis (Table S3). None- ACKNOWLEDGMENTS. Data collection was funded by a University of New
theless, we acknowledge that the study represents a limited number of England seed grant (to R.R.). I.B. was supported by European Union Proj-
crops, and a greater range of datasets is required to obtain a fuller picture of ect BeeFun PCIG14-GA-2013-631653; L.A.G. was supported by Universidad
the relative importance of these different groups of pollinators. Nacional de Río Negro Grant PI 40-B-399 and Consejo Nacional de Investiga-
ciones Científicas y Técnicas Resolución 3260/14, Expediente 3207/14; A.-M.K.
and C.B. were supported by the German Science Foundation; D.K., M. Reemer,
Data Analysis. Data on visitation rates, pollination effectiveness, fruit or seed and J.S. were supported by the Dutch Ministry of Economic Affairs Grants BO-
set, and isolation from natural/seminatural vegetation were standardized for 11-011.01-011 and KB-14-003-006; L.G.C. D.K., J.S., R.B., H.S., M.W., M. Rundlöf,
cross-study analysis with the calculation of z-scores within each study and S.G.P. were supported by the European Community’s Seventh Framework
(Datasets S1–S4). Z-scores do not modify the form (e.g., linear or nonlinear) Programme FP7/2007–2013 under Grant Agreement 244090, Status and Trends
of the relationship between response and predictor variables and allow di- of European Pollinators; H.S. and M.W. were supported by European Com-

ECOLOGY
rect comparison of the values collected in different studies (79). munity’s Sixth Framework Programme under Grant Agreement GOCE-CT-
2003-506675, Assessing Large Scale Risks for Biodiversity with Tested Methods
We analyzed all data using general linear mixed-effects models using R
Project; S.A.M.L. was supported the Swedish Farmers’ Foundation for Agricul-
software version 3.0.2, nlme package, lme function, with Gaussian error tural Research and the Swedish Board of Agriculture; M.P.D.G. and S.G.P. were
distribution (80). By including crop study as a random variable, our models supported by a grant from Biotechnology and Biological Sciences Research
estimated different intercepts (αj) for each study (j), accounting for the hi- Council, Defra, the Natural Environment Research Council, the Scottish Govern-
erarchical structure of the data, i.e., different fields are nested within each ment, and the Wellcome Trust under the UK Insect Pollinators Initiative; H.G.S.
study (79, 81). The overall intercept (μα) reflects a weighted average over and R.B. were supported by the Swedish Research Council for Environment,
crop studies (αj), in which the relative influence of each crop study increases Agricultural Sciences and Spatial Planning; C.S. was supported by the Swiss
with the precision of its local model fit and its sample size (79, 82). National Science Foundation under Grant 3100A0-127632 (FRAGMENT) to F.H.
and M.H.E.; J.C.S. and D.A.S. were supported by Irish Environmental Protection
To answer the first question regarding differences in crop-pollination
Agency Grant EPA 2007-B-CD-1-S1 under the Sectoral Impacts on Biodiversity
services provided to crop flowers by non-bee and bee taxa, we ran a different and Ecosystems Services (SIMBIOSYS) project; B.M.F. and L.G.C. were supported
model for each group (honey bees, wild bees, and non-bees) with no pre- by National Council for Scientific and Technological Development-Brasília Re-
dictor. This model enabled calculation of the overall intercept (i.e., mean search Grants 05126/2013-0 and 300005/2015-6, respectively; Y.M. and G.P. were
percent visitation) and CIs for each of the three groups, taking into account supported by The Israel Science Foundation; S.K. was supported by The North-
the hierarchical structure of the data. Per capita effectiveness values were South Centre, Swiss Federal Institute of Technology, Zurich; B.F.V. and J.H. were
regressed against pollinator group (categorical: honey bee, other bee, non- supported by the Ministry of the Environment and the Brazilian Research Coun-
bee). Post hoc Tukey tests were used to disentangle the differences in ef- cil; and the study on Highland coffee was supported by Grant SEMARNAT-
CONACyT 2002-C01-0194 from Mexico’s Environmental Ministry (to C.H.V.).
fectiveness among the three groups using the multcomp package (83) with a
H.T. was supported by the Global Environment Research Fund (E-0801
Hochberg correction for multiple comparisons. To answer the second ques- and S-9) of the Ministry of the Environment, Japan. Funding for kiwi in New
tion, we built three sets of models to examine the relationship between fruit Zealand provided by the Thomas J. Watson Foundation (to M.M.M.). B.G.H. and
set and the visitation rates of the different insect groups. To determine D.E.P. were supported by Ministry for Business Innovation and Employment
whether increased visitation rate by each of the three groups was associated (C11X1309).

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