LETTER
A global quantitative synthesis of local and landscape effects
on wild bee pollinators in agroecosystems
Christina M. K ennedy,
1*†
Eric Lonsdorf,
1
Maile C. Neel,
2
Neal M. Williams ,
3
Taylor H.
Ricketts ,
4
Rachael Winfree ,
5
Riccardo
Bommarco,
6
Claire Brittain,
3,7
Alana L.
Burley ,
8
Daniel Cariveau,
5
Lu
ısa G.
Carvalheiro,
9,10,11
Natacha P.
Chacoff,
12
Saul A. Cunningham,
13
Bryan N. Danforth,
14
Jan-Hendrik
Dudenh
€
offer,
15
Elizabeth Elle,
16
Hannah R. Gaines,
17
Lucas A.
Garibaldi,
18
Claudio Gratton,
17
Andrea Holzschuh,
15,19
Rufus
Isaacs ,
20
Steven K. Javorek,
21
Shalene Jha,
22
Alexandra M. Klein,
7
Kristin Krewenka,
15
Yael Mandelik,
23
Margaret M. Mayfield,
8
Lora
Morandin,
18
Lisa A. Neame ,
16
Mark
Otieno,
24
Mia Park,
14
Simon G.
Potts,
24
Maj Rundl
€
of,
6,25
Agustin
Saez,
26
Ingolf Steffan-Dewenter,
19
Hisatomo T aki,
27
Blandina Felipe
Viana,
28
Catrin Westphal,
15
Julianna
K. Wilson,
20
Sarah S. Greenleaf
29
and Claire Kremen
29
Abstract
Bees provide essential pollination services that are potentially affected both by local farm management and
the surrounding landscape. To better understand these different factors, we modelled the relative effects of
landscape composition (nesting and floral resources within foraging distances), landscape configuration
(patch shape, interpatch connectivity and habitat aggregation) and farm management (organic vs. conven-
tional and local-scale field diversity), and their interactions, on wild bee abundance and richness for 39 crop
systems globally. Bee abundance and richness were higher in diversified and organic fields and in land-
scapes comprising more high-quality habitats; bee richness on conventional fields with low diversity bene-
fited most from high-quality surrounding land cover. Landscape configuration effects were weak. Bee
responses varied slightly by biome. Our synthesis reveals that pollinator persistence will depend on both
the maintenance of high-quality habitats around farms and on local management practices that may offset
impacts of intensive monoculture agriculture.
Keywords
Agri-environment schemes, diversified farming system, ecologically scaled landscape index, ecosystem ser-
vices, farm management, habitat fragmentation, landscape structure, organic farming, pollinators.
Ecology Letters (2013) 16: 584–599
1
Urban Wildlife Institute, Lincoln Park Zoo, Chicago, IL, 60614, USA
2
Department Plant Science and Landscape Architecture, University of
Maryland, College Park, Maryland, 20742, USA
3
Department of Entomology, University of California, One Shields Ave., Davis,
CA, 95616, USA
4
Gund Institute for Ecological Economics, University of Vermont, Burlington,
VT, 05401, USA
5
Department of Entomology, Rutgers University, New Brunswick, NJ, 08901,
USA
6
Department of Ecology, Swedish University of Agricultural Sciences,
SE-75007, Uppsala, Sweden
7
Section Ecosystem Functions, Institute of Ecology, Leuphana University of
L
€
uneburg, Scharnhorststraße 1, 21335, L
€
uneburg, Germany
8
School of Biological Sciences, The University of Queensland, Goddard
Building, St Lucia Campus, Brisbane, QLD, 4072, Australia
9
Institute of Integrative and Comparative Biology, University of Leeds, Leeds,
LS2 9JT, UK
10
NCB-Naturalis, postbus 9517, 2300 RA, Leiden, The Netherlands
11
Department of Zoology and Entomology, University of Pretoria, Pretoria
0002, South Africa
12
Instituto de Ecolog
ıa Regional (IER), Facultad de Ciencias Naturales e IML,
UNT. CC 34, 4107, Tucum
an, Argentina
13
CSIRO Ecosystem Sciences, GPO Box 1700, Canberra, ACT 2601, Australia
14
Department of Entomology, Cornell University, Ithaca, NY, 14853, USA
15
Department of Crop Sciences, Agroecology, Geo rg August University
G
€
ottingen, Grisebachstr, 6 D-37077, G
€
ottingen, Germany
16
Department of Biological Sciences, Simon Fraser University, Burnaby, BC,
V5A 1S6, Canada
17
Department of Entomology, University of Wisconsin, 1630 Linden Drive,
Madison, WI, 53706, USA
18
Sede Andina, Universidad Nacional de R
ıo Negro (UNRN) and Consejo
Nacional de Investigaciones Cient
ıficas y T
ecnicas (CONICET), Mitre 630, CP
8400, San Carlos de Bariloche, R
ıo Negro, Argentina
19
Department of Animal Ecology and Tropical Biology, Biocenter, University
of W
€
urzburg, Am Hubland, 97074, W
€
urzburg, Germany
20
Department of Entomology, Michigan State University, East Lansing, MI,
48824, USA
21
Agriculture and Agri-Food Canada, Atlantic Food and Horticultural Research
Centre, 32 Main Street, Kentville, NS, B4N 1J5, Canada
22
Integrative Biology, 401 Biological Laboratories, University of Texas, Austin,
TX, 78712, USA
23
Department of Entomology, The Hebrew University of Jerusalem, P.O. Box
12, Rehovot, 76100, Israel
24
School of Agriculture, Policy and Development, University of Reading,
Reading, RG6 6AR, UK
25
Department of Biology, Lund University, SE-223 62, Lund, Sweden
26
Laboratorio Ecotono-CRUB, Universidad Nacional del Comahue - INIBIOMA,
(8400) San Carlos de Bariloche, R
ıo Negro, Argentina
27
Department of Forest Entomology, Forestry and Forest Products Research
Institute, 1 Matsunosato, Tsukuba, Ibaraki, 305-8687, Japan
28
Biology Institute, Federal University of Bahia – UFBA, Rua Bar
~
ao de Geremo-
abo, s/n Campus Universit
ario de Ondina, Salvador, BA, 40170-210, Brazil
29
Department of Environmental Science, Policy and Management, University
of California, Berkeley, CA, 94720-3114, USA
†
Current affiliation:Development by Design Program, The Nature
Conservancy, Fort Collins, CO, 80524, USA
*Correspondence: E-mail: ckennedy@tnc.org
© 2013 Blackwell Publishing Ltd/CNRS
Ecology Letters, (2013) 16: 584–599 doi: 10.1111/ele.12082
INTRODUCTION
Wild bees are a critical component of ecosystems and provide
essential pollination services to wild plants (Kearns et al. 1998) and
to crops (Klein et al. 2007) in agricultural landscapes. In some situa-
tions, wild bees alone can fully pollinate crops (Kremen et al. 2002;
Winfree et al. 2007b), and bee richness can enhance the magnitude
and temporal stability of pollination (Kremen et al. 2002; Klein et al.
2009; Garibaldi et al. 2011). However, growers often rely on the
managed honey bee (Apis mellifera) to provide crop pollination. Apis
declines in regions of the United States and Europe (Potts et al.
2010b), concomitant with increases in pollination-dependent crop
cultivation globally, have increased the potential for pollination
shortfalls for farmers (Aizen et al. 2008). These factors in turn
increase the importance of wild pollinators (Potts et al. 2010b). It is
therefore vital to determine the environmental conditions, both at
local and landscape scales, that support diverse and abundant wild
bee assemblages in agroecosystems.
Two drivers are proposed to influence wild bee abundance and
richness on farms: local management practices on the farm and the
quality and structure of the surrounding landscape (Kremen et al.
2007). There is growing evidence for the importance of local field
management on wild pollinators, both separately and in interaction
with landscape effects, as revealed in regional studies (Williams &
Kremen 2007; Rundl€of et al. 2008; Batary et al. 2011; Concepcion
et al. 2012). Different management practices, such as organic farm-
ing or increasing within-field habitat heterogeneity, can improve bee
abundance, richness and productivity even in landscapes with little
natural habitat (Williams & Kremen 2007; Holzschuh et al. 2008;
Rundl€of et al. 2008; Batary et al. 2011), as long as sufficient habitat
exists to maintain source populations (Tscharntke et al. 2005, 2012).
Whether these local-scale and interactive effects are consistent
across global agriculture remains unknown.
Research on landscape-level effects on pollinators has focused
predominantly on the contribution of natural and semi-natural areas
surrounding farms, which may provide essential habitats and key
floral resources and nesting sites that contribute to the long-term
persistence of wild bees (Westrich 1996; Williams & Kremen 2007).
Syntheses of data across multiple taxa, crop species and biomes
reveal that bee visitation, richness and stability increase with
decreasing distance from these habitats (Ricketts et al. 2008;
Garibaldi et al. 2011). These studies offer insights into the impor-
tance of natural areas in sustaining pollination services in human-
modified landscapes, but their use of binary landscape categories
(e.g. natural and semi-natural habitat vs. cropland) fails to account
for the complexity of different habitats known to provide partial
resources for bees (Westrich 1996; Winfree et al. 2007a). These
recent syntheses also do not consider species’ responses to local-
scale management practices or differential responses to habitat attri-
butes.
To develop a more robust understanding of how different land-
cover types influence wild (bee) pollinators in agricultural land-
scapes, a spatially explicit model has been developed to predict rela-
tive bee abundance based on the composition of habitats and their
floral and nesting resources (Lonsdorf et al. 2009). The Lonsdorf
et al. (2009) model produces an ecologically scaled landscape index
(sensu Vos et al. 2001) that captures the estimated quality and
amounts (and potential seasonal shifts) of habitats in a landscape,
and is scaled based on species mobility. This model, however, does
not account for variation caused by different farm management
practices; and it does not account explicitly for landscape configura-
tion (i.e. the spatial arrangement of habitat patches in a landscape),
which can impact floral, nesting and overwintering resources for
bees (Kremen et al. 2007) and has been hypothesised to be an
important, yet unaccounted for determinant of bee communities
(Lonsdorf et al. 2009).
Here, we performed an empirical synthesis to disentangle the
independent and interactive effects of local management and land-
scape structure on wild bees, which is essential to inform ecosystem
service-based land use recommendations in agroecosystems
(Tscharntke et al. 2005, 2012). We apply the Lonsdorf et al. (2009)
model to 39 studies on 23 crops in 14 countries on 6 continents to
capture landscape composition effects on bee richness and abun-
dance, accounting for the floral and nesting value of all habitat
types in a landscape. We expand on previous analyses by determin-
ing the influence of landscape configuration (patch shape, interpatch
connectivity and habitat aggregation) and local farm management
(organic vs. conventional farming and local-scale field diversity).
Using mixed model analysis in a model selection framework, we
then test the relative importance of landscape composition (i.e.
model output), landscape configuration, local farm management and
their potential interactions, as predictors of observed wild bee abun-
dance and richness in crop fields.
METHODS
Studies and measures of pollinators
We analysed pollinator and landscape data from 605 field sites from
39 studies in different biomes (tropical and subtropical, n = 10;
Mediterranean, n = 8; and other temperate, n = 21) and on 23
crops with varying degrees of dependency on pollinators (Table 1,
see Appendix S1 for references of published studies and Appendix
S2 for methods of unpublished studies in Supporting Information).
Our analyses focused on bees because they are considered the most
important crop pollinators (Klein et al. 2007) and their biology is
relatively well known. We analysed only wild species, because the
abundance of managed species depends more on human choice of
placement than on landscape or local field site characteristics. We
targeted studies that sampled bees at multiple independent fields
within an agricultural landscape (across a gradient in agricultural
intensity) based on author knowledge and previous synthetic work
(Ricketts et al. 2008; Garibaldi et al. 2011). Author(s) of each study
provided site-specific data on (1) bee abundance and/or visitation
and bee richness, (2) spatial locations of fields, (3) characterisation
of local management (organic vs. conventional and field diversity),
(4) GIS data on surrounding multi-class land cover and (5) esti-
mates of nesting and floral resource quality for different bee guilds
for each land-cover class. Within studies, all sites were separated by
distances of 350 m–160 km (mean SD: 25 22 km), with only
0.02% site pairs located < 1 km apart (Appendix S3).
Bee abundance and richness
All 39 studies measured bee abundance on (n = 22) or number of
visits to (n = 17) crop flowers, and all but one study measured spe-
cies richness (Table 1). Abundance was quantified as the number of
individual bees collected from aerial netting, pan trapping or both;
bee visitation was measured as the total number of times a bee
© 2013 Blackwell Publishing Ltd/CNRS
Letter Local and landscape effects on pollinators 585
Table 1 Studies included in the modelling of local and landscape effects on global wild bee assemblages
Study Citation
§
Crop species
Crop pollinator
dependence* Bee flower visitors modelled
Honey bee:
managed, feral
$
# Years
sampled # Sites
Site distance
range (mean) (m) Location
Tropical and subtropical biomes
†
Coffee_A Jha & Vandermeer 2010 Coffea
arabica
Medium
(10–40%)
44 taxa: Augochlora spp.,
Augochlorella sp., Augochloropsis spp.,
Caenaugochlora sp., Ceratina spp.,
Dialictus spp., Euglossa sp.,
Halictus spp., Melitoma spp.,
Melissodes sp., Plebia sp.,
Trigona sp., Trigonisca sp.,
Xylocopa sp.
Yes, yes 1 7 >925–4030
(2470)
Chiapas,
Mexico
Coffee_B Ricketts 2004;
Ricketts et al. 2004
C. arabica Medium
(10–40%)
11 taxa: Apis sp., Melipona sp.,
Nannotrigona sp., Partamona sp.,
Plebeia sp., Plebia sp.,
Trigona spp., Trigonisca sp.
No, yes 1 8 >490–3100
(1400)
San Isidro
del General,
Costa Rica
Grapefruit Chacoff & Aizen 2006;
Chacoff et al. 2008
Citrus
paradisi
Little
(< 10%)
14 taxa: Apis mellifera,
Augochlorospis spp.,
Bombus sp., Dialictus sp.,
Megachilidae sp., Plebeia spp.,
Psaenythia sp., Tetragonisca sp.,
Trigona spp.
No, yes 3 12 >430–74 000
(33 200)
Yungas,
Argentina
Longan Blanche et al. 2006 Dimocarpus
longan
Medium
(10–40%)
3 taxa: A. mellifera, Homalictus
dampieri, Trigona carbonaria
No, yes 1 6 >2500–80 000
(43 000)
Queensland,
Australia
Macadamia_A Blanche et al. 2006 Macadamia
integrifolia
Essential
(>90%)
1 taxon: A. mellifera No, yes 1 5 >10 000–40 000
(24 000)
Queensland,
Australia
Macadamia_B Mayfield (unpublished
data)
Macadamia
integrifolia
Essential
(>90%)
1 taxon: Trigona carbonaria Yes, yes 1 10 >430–24 000
(13 300)
New South
Wales,
Australia
Mango Carvalheiro et al. 2010 Mangifera indica High
(40–90%)
3 taxa: Ceratina spp.,
Xylocopa sp.
Yes, yes 1 12 >1700–13 600
(6500)
Limpopo,
South Africa
Passion flower Viana & Silva
(unpublished data)
Passiflora edulis
Sims f. flavicarpa
Essential
(>90%)
4 taxa: A. mellifera, Trigona spinipes,
Xylocopa (Megaxylocopa)
frontalis, Xylocopa
(Neoxylocopa) grisescens
No, yes 1 16 >1000–9600
(4400)
Bahia, Brazil
Pigeon pea Otieno et al.
(unpublished data)
Cajanus cajan Little
(< 10%)
48 taxa: Amegilla spp., Anthidium sp.,
Anthophora sp., Braunsapis sp.,
Ceratina sp., Coelioxys sp.,
Dactylurina sp.,
Euaspis sp., Halictus sp., Heriades sp.,
Hypotrigona sp., Lasioglossum sp.,
Lipotriches sp., Lithurge sp.,
Macrogalea sp., Megachile spp., Meliponula sp.,
Melissodes sp., Nomia sp.,
Pachyanthidium sp., Pachymelus sp.,
Plebeina sp., Pseudapis sp.,
Pseudoanthidium sp., Pseudophilanthus sp.,
Systropha sp., Tetralonia sp.,
Tetraloniella sp., Thyreus sp.,
Xylocopa spp.
Yes, no 1 12 >2100–35 000
(16 300)
Kibwezi
District, Kenya
(continued)
© 2013 Blackwell Publishing Ltd/CNRS
586 C. M. Kennedy et al. Letter
Table 1. (continued)
Study Citation
§
Crop species
Crop pollinator
dependence* Bee flower visitors modelled
Honey bee:
managed, feral
$
# Years
sampled # Sites
Site distance
range (mean) (m) Location
Sunflower_A Carvalheiro et al. 2011 Helianthus
annuus
Medium
(10–40%)
4 taxa: Lasioglossum sp., Megachile sp.,
Tetraloniella sp., Xylocopa sp.
Yes, yes 1 30 >350–24 000
(8400 m)
Limpopo,
South Africa
Mediterranean biome
Almond_A Klein et al. 2012; Klein,
Brittain, & Kremen
(unpublished data)
Prunus dulcis High
(40–90%)
38 taxa: Agapostemon sp., Andrena spp.,
Bombus sp., Ceratina spp.,
Eucera spp., Habropoda sp.,
Halictus spp.; Hoplitis sp.,
Lasioglossum spp., Micralictoides sp.,
Osmia spp., Panurginus sp.,
Protosmia sp., Stelis sp.
Yes, no 1 23 >1460–46 000
(17 600)
California, USA
Almond_B Kremen (unpublished
data)
P. dulcis High
(40–90%)
8 taxa: Andrena sp., Bombus sp.,
Dialictus sp., Halictus spp.,
Lasioglossum sp.
Yes, no 1 15 >1150–54 100
(25 400)
California, USA
Almond_C Mandelik (unpublished
data) (a)
P. dulcis High
(40–90%)
27 taxa: Andrena spp., Ceratina spp.,
Eucera spp., Halictus sp.,
Lasioglossum spp., Nomada spp.
Yes, no 1 6 >1100–23 000
(13 100)
Judean
Foothills,
Israel
Sunflower_B Greenleaf & Kremen
2006 (b)
H. annuus Medium
(10–40%)
13 taxa: Agapostemon sp.,
Anthophoridae spp., Bombus spp.,
Halictus spp., Lasioglossum sp.,
Megachile spp., Svastra sp.,
Xylocopa sp.
Yes, no 3
¶
15 1400–55 000
(20 600)
California, USA
Sunflower_C Mandelik (unpublished
data) (b)
H. annuus Medium
(10–40%)
60 taxa: Andrena spp., Ceratina spp.,
Ceylalictus sp., Colletes sp.,
Eucera spp., Halictus spp.,
Hylaeus spp., Lasioglossum spp.,
Nomada spp., Nomioides sp.,
Osmia sp., Panurgus sp., Systropha sp.
Yes, no 1 13 1200–26 600
(11 050)
Judean
Foothills,
Israel
Tomato_A Greenleaf & Kremen
2006 (a)
Solanum
lycopersicum
Little
(< 10%)
4 taxa: Anthophora urbana, Bombus
vosnesenskii, Lasioglossum incompletus,
Small striped bee
Yes, no 1 10 2900–58 000
(27 100)
California, USA
Watermelon_A Kremen et al. 2002, 2004 Citrullus
lanatus
Essential
(>90%)
17 taxa: Agapostemon sp., Anthophora sp.,
Bombus spp., Calliopsis sp., Halictus spp.,
Hylaeus sp., Lasioglossum spp.,
Melissodes spp., Osmia sp., Peponapis sp.,
Sphecodes sp., Triepeolus sp.
Yes, no 2
¶
34 >410–69 500
(25 240)
California, USA
Watermelon_B Mandelik (unpublished
data) (c)
C. lanatus Essential
(>90%)
47 taxa: Ceratina spp., Ceylalictus sp.,
Eucera spp., Halictus spp., Hylaeus spp.,
Lasioglossum spp., Lithurgus sp.,
Megachile spp., Nomada spp.,
Nomiapis spp., Ochreriades sp.,
Xylocopa sp.
Yes, no 1 19 >935–30 100
(14 000)
Judean
Foothills,
Israel
(continued)
© 2013 Blackwell Publishing Ltd/CNRS
Letter Local and landscape effects on pollinators 587
Table 1. (continued)
Study Citation
§
Crop species
Crop pollinator
dependence* Bee flower visitors modelled
Honey bee:
managed, feral
$
# Years
sampled # Sites
Site distance
range (mean) (m) Location
Other temperate biomes
‡
Apple Park & Danforth
(unpublished data)
Malus domestica Essential
(>90%)
58 taxa: Andrena spp., Augochlora sp.,
Augochlorella sp., Augochloropsis sp.,
Bombus spp., Ceratina sp., Colletes sp.,
Halictus spp., Lasioglossum spp.,
Nomada spp., Osmia spp., Sphecodes sp.,
Xylocopa sp.
Yes, yes 2
¶
14 >2500–110 000
(52 200)
New York,
USA
Blueberry_A Isaacs & Kirk 2010 Vaccinium
corymbosum,
cv. Jersey
High
(40–90%)
4 taxa: Andrena spp., Bombus spp.,
Halictidae spp., Xylocopa sp.
Yes, no 1 12 >1200–10 200
(36 000)
Michigan, USA
Blueberry_B Javorek (unpublished
data)
Vaccinium
angustifolium
Essential
(>90%)
18 taxa: Andrena spp., Augochlorella sp.,
Bombus spp., Colletes sp., Halictus spp.,
Lasioglossum spp., Osmia spp.
Yes, no 3 16 >2000–155 700
(66 000)
Prince
Edward
Island, Canada
Blueberry_C Tuell et al. 2009 Vaccinium
corymbosum
High
(40–90%)
101 taxa: Agapostemon spp., Andrena spp.,
Augochlora sp., Augochlorella sp.,
Augochloropsis sp., Bombus spp.,
Ceratina spp., Colletes spp.,
Halictus spp., Hoplitis spp.,
Hylaeus spp., Lasioglossum spp.,
Megachile spp.,
Nomada spp.,
Osmia spp., Sphecodes spp.,
Xylocopa sp.
Yes, no 3 15 >2800–80 400
(31 600)
Michigan, USA
Buckwheat Taki et al. 2010 Fagopyrum
esculentum
High
(40–90%)
17 taxa: Apis cerana, Chalicodoma sp.,
Coelioxys sp., Colletes spp., Epeolus sp.,
Halictus sp., Hylaeus spp.,
Lasioglossum spp., Lipotriches sp.,
Megachile spp., Sphecodes sp.,
Xylocopa sp.
Yes, no 2 17 450–9500
(3500)
Ibaraki, Japan
Canola_A** Arthur et al. 2010 Brassica napus
and juncea
Medium
(10–40%)
2 taxa: A. mellifera, native bees No, yes 1 19 >375–27 497
(11 100)
Boorowa New
South Wales,
Australia
Canola_B Prache, MacFadyen,
& Cunningham
(unpublished data)
B. napus
and juncea
Medium
(10–40%)
12 taxa: Amegilla sp., Lasioglossum spp.,
Leioproctus spp., Lipotriches sp.
Yes, yes 1 10 >530–6400
(4100)
Bethungra
New South
Wales,
Australia
Canola_C Bommarco, Marini &
Vaissi
ere 2012
Brassica napus Medium
(10–40%)
8 taxa: Bombus spp. Yes, no 1 10 >3850–71 000
(26 700)
Uppland,
Sweden
Canola_D Morandin & Winston
2005
Brassica rapa
and napus
High
(40–90%)
86 taxa: Andrena spp., Anthidium sp.,
Anthophora spp., Bombus spp.,
Coelioxys spp., Colletes spp.,
Diadasia sp.,
Eucera sp., Halictus spp., Heriades sp.,
Hoplitis spp., Hylaeus spp., Lasioglossum
spp., Megachile spp., Melissodes sp.,
Nomada spp., Osmia spp., Panurginus sp.,
Protandrena spp., Sphecodes spp., Stelis sp.
No, no 2* 54 >480–67 700
(24 600)
Alberta,
Canada
(continued)
© 2013 Blackwell Publishing Ltd/CNRS
588 C. M. Kennedy et al. Letter
