pollination declines- slu talk
DESCRIPTION
TRANSCRIPT
Historical changes in bee community composition and phenology. Is there a pollination crisis?
Ignasi [email protected]
@ibartomeus
4% of land was agriculture in ~1800
>Z0%of land is
agriculture, now
7 billion people
1 billion people
1880
19501980
2010we are +0.6ºc above the
1950-1980 mean
temperature levels
1800
4% of land was agriculture in ~1800
>Z0%of land is
agriculture, now
7 billion people
1 billion people
1880
19501980
2010we are +0.6ºc above the
1950-1980 mean
temperature levels
1800
4% of land was agriculture in ~1800
>Z0%of land is
agriculture, now
7 billion people
1 billion people
1880
19501980
2010we are +0.6ºc above the
1950-1980 mean
temperature levels
1800
but… how are all these changes affecting plants and animals?
TrendsCauses:
Land Use ChangeClimate Change
Consequences
2010
Rachael Winfree
you can buy a
DeLorean
We could buy a Delorean!
American Natural History Museum
John Ascher
Database:*Date*Collector*Coordinates
Assemble long-term data:
This is not the romantic
trip he promised
This is not the romantic trip he
promised
*American Museum of Natural History *University of Connecticut *Cornell University*Rutgers University*Connecticut Agricultural Station *University of New Hampshire *University of Massachusetts*Vermont State Bee Database*New York State Museum*Bohart Museum of Entomology.
Trends
Bartomeus et al 2013 PNAS
What do we know about the “pollinator crisis”?
What do we know about the “pollinator crisis”?* Honeybees (managed) * Bumblebees
Cameron et al. 2011 Grixti et al. 2009,Colla et al. 2008,
What do we know about the “pollinator crisis”?* Honeybees (managed) * Bumblebees
Cameron et al. 2011 Grixti et al. 2009,Colla et al. 2008,
museum collections throughout the United States (Fig. S1B andTable S2). Comparisons of the historical and current datarevealed extensive range reductions (Fig. 1 A, D, G, and H) andsignificant decreases in RA in all four species suspected of pop-ulation decline (all P < 0.001) (Fig. 2); each was absent fromsignificantly more sites predicted to have high occurrence prob-abilities than were stable species (Fisher’s exact tests; all P <0.001) (Table S4). Declines in RA appear only within the last 20–30 y, with RA values from current surveys lower than in any de-
cade of the last century (Fig. S1C). The four allegedly stablespecies showed no clear patterns of range reduction (Fig. 1 B, C,E, and F and Tables S2, S4, and S5) or consistent declines in RA.Historically, B. occidentalis and B. pensylvanicus had among the
broadest geographic ranges of any bumble bee species in NorthAmerica (Fig. 1 and Table S5). However, the current surveysdetected B. occidentalis only throughout the intermountain westand Rocky Mountains; it was largely absent from the westernportion of its range (Figs. 1A and 2) (detected range-area re-
Fig. 1. Summary of Bombus individuals surveyed from 382 collection locations for eight target species, including historical rangemaps (grayscale shading) withcurrent sightings (pie charts) and associated photographs of hypothesized declining western B. occidentalis (A) and eastern B. pensylvanicus (D), B. affinis(G), and B. terricola (H); stable species are represented by the western B. bifarius (B) and B. vosnesenskii (C), and the eastern B. bimaculatus (E), and B. impatiens(F). Sizes of the pie charts indicate total number of individuals surveyed at each location; size of the orange segment indicates the fraction of the respectivetarget species collected at that site (some locations are pooled across sites for visual clarity; for detailed data, refer to Table S1). Underlying grayscale shadingrepresents the modeled distribution of each target species from unique presence localities obtained from natural history collections (SI Methods, StatisticalNicheModels). PhotographA (B. occidentalis) taken by D. Ditchburn, B (B. bifarius) by L. Solter, C (B. vosnesenskii) byM. Layne,D (B. pensylvanicus) by T.Wilson,E (B. bimaculatus) by J. Whitfield, F (B. impatiens) by J. Lucier, G (B. affinis) by J. James-Heinz, and H (B. terricola) by J. Whitfield.
2 of 6 | www.pnas.org/cgi/doi/10.1073/pnas.1014743108 Cameron et al.
What do we know about the “pollinator crisis”?* Honeybees (managed) * Bumblebees
Cameron et al. 2011 Grixti et al. 2009,Colla et al. 2008,
museum collections throughout the United States (Fig. S1B andTable S2). Comparisons of the historical and current datarevealed extensive range reductions (Fig. 1 A, D, G, and H) andsignificant decreases in RA in all four species suspected of pop-ulation decline (all P < 0.001) (Fig. 2); each was absent fromsignificantly more sites predicted to have high occurrence prob-abilities than were stable species (Fisher’s exact tests; all P <0.001) (Table S4). Declines in RA appear only within the last 20–30 y, with RA values from current surveys lower than in any de-
cade of the last century (Fig. S1C). The four allegedly stablespecies showed no clear patterns of range reduction (Fig. 1 B, C,E, and F and Tables S2, S4, and S5) or consistent declines in RA.Historically, B. occidentalis and B. pensylvanicus had among the
broadest geographic ranges of any bumble bee species in NorthAmerica (Fig. 1 and Table S5). However, the current surveysdetected B. occidentalis only throughout the intermountain westand Rocky Mountains; it was largely absent from the westernportion of its range (Figs. 1A and 2) (detected range-area re-
Fig. 1. Summary of Bombus individuals surveyed from 382 collection locations for eight target species, including historical rangemaps (grayscale shading) withcurrent sightings (pie charts) and associated photographs of hypothesized declining western B. occidentalis (A) and eastern B. pensylvanicus (D), B. affinis(G), and B. terricola (H); stable species are represented by the western B. bifarius (B) and B. vosnesenskii (C), and the eastern B. bimaculatus (E), and B. impatiens(F). Sizes of the pie charts indicate total number of individuals surveyed at each location; size of the orange segment indicates the fraction of the respectivetarget species collected at that site (some locations are pooled across sites for visual clarity; for detailed data, refer to Table S1). Underlying grayscale shadingrepresents the modeled distribution of each target species from unique presence localities obtained from natural history collections (SI Methods, StatisticalNicheModels). PhotographA (B. occidentalis) taken by D. Ditchburn, B (B. bifarius) by L. Solter, C (B. vosnesenskii) byM. Layne,D (B. pensylvanicus) by T.Wilson,E (B. bimaculatus) by J. Whitfield, F (B. impatiens) by J. Lucier, G (B. affinis) by J. James-Heinz, and H (B. terricola) by J. Whitfield.
2 of 6 | www.pnas.org/cgi/doi/10.1073/pnas.1014743108 Cameron et al.
museum collections throughout the United States (Fig. S1B andTable S2). Comparisons of the historical and current datarevealed extensive range reductions (Fig. 1 A, D, G, and H) andsignificant decreases in RA in all four species suspected of pop-ulation decline (all P < 0.001) (Fig. 2); each was absent fromsignificantly more sites predicted to have high occurrence prob-abilities than were stable species (Fisher’s exact tests; all P <0.001) (Table S4). Declines in RA appear only within the last 20–30 y, with RA values from current surveys lower than in any de-
cade of the last century (Fig. S1C). The four allegedly stablespecies showed no clear patterns of range reduction (Fig. 1 B, C,E, and F and Tables S2, S4, and S5) or consistent declines in RA.Historically, B. occidentalis and B. pensylvanicus had among the
broadest geographic ranges of any bumble bee species in NorthAmerica (Fig. 1 and Table S5). However, the current surveysdetected B. occidentalis only throughout the intermountain westand Rocky Mountains; it was largely absent from the westernportion of its range (Figs. 1A and 2) (detected range-area re-
Fig. 1. Summary of Bombus individuals surveyed from 382 collection locations for eight target species, including historical rangemaps (grayscale shading) withcurrent sightings (pie charts) and associated photographs of hypothesized declining western B. occidentalis (A) and eastern B. pensylvanicus (D), B. affinis(G), and B. terricola (H); stable species are represented by the western B. bifarius (B) and B. vosnesenskii (C), and the eastern B. bimaculatus (E), and B. impatiens(F). Sizes of the pie charts indicate total number of individuals surveyed at each location; size of the orange segment indicates the fraction of the respectivetarget species collected at that site (some locations are pooled across sites for visual clarity; for detailed data, refer to Table S1). Underlying grayscale shadingrepresents the modeled distribution of each target species from unique presence localities obtained from natural history collections (SI Methods, StatisticalNicheModels). PhotographA (B. occidentalis) taken by D. Ditchburn, B (B. bifarius) by L. Solter, C (B. vosnesenskii) byM. Layne,D (B. pensylvanicus) by T.Wilson,E (B. bimaculatus) by J. Whitfield, F (B. impatiens) by J. Lucier, G (B. affinis) by J. James-Heinz, and H (B. terricola) by J. Whitfield.
2 of 6 | www.pnas.org/cgi/doi/10.1073/pnas.1014743108 Cameron et al.
(Pathogens)
What we know about all other >400 bee genera?
Biesmeijer et al. 2006
“for most pollinator species, the paucity of long-term data and the incomplete knowledge of even basic taxonomy and ecology make definitive assessment of status exceedingly difficult”
NAS 2008
Assemble long-term data:
* 47 bee genera comprising 438 species.
* >30,000 independently collected bee specimens
Assemble long-term data:
* >1500 collectors * >11000 collection events
* 47 bee genera comprising 438 species.
Assemble long-term data:
* >1500 collectors * >11000 collection events
* >30,000 independently collected bee specimens
Restrict Geographical area & check no temporal bias.
Use independently collected specimens
1) Richness
Rarefaction: “expected richness if sample size was equal”
180
200
220
240
Num
ber o
f bee
spe
cies
(exc
ludi
ng B
ombu
s)
1872-1913
1913-1931
1931-1960
1960-1965
1965-1972
1972-1981
1981-2002
2002-2006
2006-2008
2008-2011
12
14
16
18
Num
ber o
f Bom
bus
spec
ies
1877-1899
1899-1906
1906-1919
1919-1937
1937-1963
1963-1975
1975-1986
1986-2005
2005-2008
2008-2011
0
2
4
6
8
10
12
Num
ber o
f exo
tic s
peci
es
1872-1914
1914-1932
1932-1960
1960-1965
1965-1972
1972-1981
1981-2002
2002-2006
2006-2008
2008-2011
Bee p
hoto
Bee p
hoto
Bee p
hoto
Num
ber o
f non
-Bom
bus
spec
ies
Num
ber o
f Bom
bus
spec
ies
Coelioxys sayi
Bombus citrinus
(A)
(B)
(C)
Anthidium manicatum
!
{
180
200
220
240
Num
ber o
f bee
spe
cies
(exc
ludi
ng B
ombu
s)
1872-1913
1913-1931
1931-1960
1960-1965
1965-1972
1972-1981
1981-2002
2002-2006
2006-2008
2008-2011
12
14
16
18
Num
ber o
f Bom
bus
spec
ies
1877-1899
1899-1906
1906-1919
1919-1937
1937-1963
1963-1975
1975-1986
1986-2005
2005-2008
2008-2011
0
2
4
6
8
10
12
Num
ber o
f exo
tic s
peci
es
1872-1914
1914-1932
1932-1960
1960-1965
1965-1972
1972-1981
1981-2002
2002-2006
2006-2008
2008-2011
Bee p
hoto
Bee p
hoto
Bee p
hoto
Num
ber o
f non
-Bom
bus
spec
ies
Num
ber o
f Bom
bus
spec
ies
Coelioxys sayi
Bombus citrinus
(A)
(B)
(C)
Anthidium manicatum
!
140 people/km^21900’s
Rarefaction: “expected richness if sample size was equal”
180
200
220
240
Num
ber o
f bee
spe
cies
(exc
ludi
ng B
ombu
s)
1872-1913
1913-1931
1931-1960
1960-1965
1965-1972
1972-1981
1981-2002
2002-2006
2006-2008
2008-2011
12
14
16
18
Num
ber o
f Bom
bus
spec
ies
1877-1899
1899-1906
1906-1919
1919-1937
1937-1963
1963-1975
1975-1986
1986-2005
2005-2008
2008-2011
0
2
4
6
8
10
12
Num
ber o
f exo
tic s
peci
es
1872-1914
1914-1932
1932-1960
1960-1965
1965-1972
1972-1981
1981-2002
2002-2006
2006-2008
2008-2011
Bee p
hoto
Bee p
hoto
Bee p
hoto
Num
ber o
f non
-Bom
bus
spec
ies
Num
ber o
f Bom
bus
spec
ies
Coelioxys sayi
Bombus citrinus
(A)
(B)
(C)
Anthidium manicatum
!
p = 0.07
Rarefaction: “expected richness if sample size was equal”140 people/km^2 325 people/km^2
1900’s 2000’s1950’s
180
200
220
240
Num
ber o
f bee
spe
cies
(exc
ludi
ng B
ombu
s)
1872-1913
1913-1931
1931-1960
1960-1965
1965-1972
1972-1981
1981-2002
2002-2006
2006-2008
2008-2011
12
14
16
18
Num
ber o
f Bom
bus
spec
ies
1877-1899
1899-1906
1906-1919
1919-1937
1937-1963
1963-1975
1975-1986
1986-2005
2005-2008
2008-2011
0
2
4
6
8
10
12
Num
ber o
f exo
tic s
peci
es
1872-1914
1914-1932
1932-1960
1960-1965
1965-1972
1972-1981
1981-2002
2002-2006
2006-2008
2008-2011
Bee p
hoto
Bee p
hoto
Bee p
hoto
Num
ber o
f non
-Bom
bus
spec
ies
Num
ber o
f Bom
bus
spec
ies
Coelioxys sayi
Bombus citrinus
(A)
(B)
(C)
Anthidium manicatum
!
p = 0.01
180
200
220
240
Num
ber o
f bee
spe
cies
(exc
ludi
ng B
ombu
s)
1872-1913
1913-1931
1931-1960
1960-1965
1965-1972
1972-1981
1981-2002
2002-2006
2006-2008
2008-2011
12
14
16
18
Num
ber o
f Bom
bus
spec
ies
1877-1899
1899-1906
1906-1919
1919-1937
1937-1963
1963-1975
1975-1986
1986-2005
2005-2008
2008-2011
0
2
4
6
8
10
12
Num
ber o
f exo
tic s
peci
es
1872-1914
1914-1932
1932-1960
1960-1965
1965-1972
1972-1981
1981-2002
2002-2006
2006-2008
2008-2011
Bee p
hoto
Bee p
hoto
Bee p
hoto
Num
ber o
f non
-Bom
bus
spec
ies
Num
ber o
f Bom
bus
spec
ies
Coelioxys sayi
Bombus citrinus
(A)
(B)
(C)
Anthidium manicatum
!p = 0.01
2) Species level
Effort
Logistic regression estimate
1880 1900 1920 1940 1960 1980 2000
0.00
0.05
0.10
0.15
Halictus ligatus
Year
Prop
ortio
n in
col
lect
ion
● ●●
●
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1880 1900 1920 1940 1960 1980 2000
0.00
0.05
0.10
0.15
Andrena carlini
Year
Prop
ortio
n in
col
lect
ion
● ●●● ●
●
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Logistic regression estimate
Effort
Coelioxys
Megachile
Bombus
Melissodes
Osmia
Colletes
Andrena
Hylaeus
Halictus
Lasioglossum
Agapostemon
Sphecodes
Nomada
Ceratina
-0.04
-0.02
0.00
0.02
0.04R
ate
of c
hang
e (e
stim
ate)
!
Coe
lioxy
s
Meg
achi
le
Bom
bus
Mel
issod
es
Osm
ia
Col
lete
s
Andr
ena
Hyla
eus
Hal
ictu
s
Las
iogl
ossu
m
Aga
post
emon
Sph
ecod
es
Nom
ada
Cera
tina
!
187 species 29% had signi5icant decreases 27% had signi5icant increases
1880 1900 1920 1940 1960 1980 2000
0.00
0.05
0.10
0.15
Macropis patellata
Year
Prop
ortio
n in
col
lect
ion
● ●●● ●●●●●●●●●●●●●●
●
●●●●●●
●
●●
●
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●
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●
●●●●●●●●
●
●●●●●●●●●●●●●●●●●●●●
Not recently in
the database
Macropis sp.
1880 1900 1920 1940 1960 1980 2000
0.0
0.2
0.4
0.6
0.8
1.0
Bombus affinis
Year
Presence/Absence
●
●
●●
●●●
●●●●●●
●
●
●
●
●●●●●
●
●●●●●●●●●●●●●●●●
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●
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●
●●●●●●
●
●●●●
●
●
●●●●●●●●●●
Bombus affinis
Bombus ashtoni
Bombus pensylvanicus
+ Macropis patellata
3) Traits
Coelioxys
Megachile
Bombus
Melissodes
Osmia
Colletes
Andrena
Hylaeus
Halictus
Lasioglossum
Agapostemon
Sphecodes
Nomada
Ceratina
-0.04
-0.02
0.00
0.02
0.04R
ate
of c
hang
e (e
stim
ate)
!
Coe
lioxy
s
Meg
achi
le
Bom
bus
Mel
issod
es
Osm
ia
Col
lete
s
Andr
ena
Hyla
eus
Hal
ictu
s
Las
iogl
ossu
m
Aga
post
emon
Sph
ecod
es
Nom
ada
Cera
tina
!
Can Bee Traits explain the Trends?
λ of the relative change estimate = 0.24
Oligolectic Polylectic
-0.04
-0.02
0.00
0.02
0.04R
ate
of c
hang
e (e
stim
ate)
1 2 3 4 5 6
-0.04
-0.02
0.00
0.02
0.04
Body size (mm)
Rat
e of
cha
nge
(est
imat
e)
40 60 80 100 120 140
-0.04
-0.02
0.00
0.02
0.04
Phenological breadth (days)
Rat
e of
cha
nge
(est
imat
e)
42 44 46 48 50
-0.04
-0.02
0.00
0.02
0.04
Northernmost latitude recorded
Rat
e of
cha
nge
(est
imat
e)
!
Oligolectic Polylectic
-0.04
-0.02
0.00
0.02
0.04R
ate
of c
hang
e (e
stim
ate)
1 2 3 4 5 6
-0.04
-0.02
0.00
0.02
0.04
Body size (mm)
Rat
e of
cha
nge
(est
imat
e)
40 60 80 100 120 140
-0.04
-0.02
0.00
0.02
0.04
Phenological breadth (days)
Rat
e of
cha
nge
(est
imat
e)
42 44 46 48 50
-0.04
-0.02
0.00
0.02
0.04
Northernmost latitude recorded
Rat
e of
cha
nge
(est
imat
e)
!
Oligolectic Polylectic
-0.04
-0.02
0.00
0.02
0.04R
ate
of c
hang
e (e
stim
ate)
1 2 3 4 5 6
-0.04
-0.02
0.00
0.02
0.04
Body size (mm)
Rat
e of
cha
nge
(est
imat
e)
40 60 80 100 120 140
-0.04
-0.02
0.00
0.02
0.04
Phenological breadth (days)
Rat
e of
cha
nge
(est
imat
e)
42 44 46 48 50
-0.04
-0.02
0.00
0.02
0.04
Northernmost latitude recorded
Rat
e of
cha
nge
(est
imat
e)
!
Oligolectic Polylectic
-0.04
-0.02
0.00
0.02
0.04R
ate
of c
hang
e (e
stim
ate)
1 2 3 4 5 6
-0.04
-0.02
0.00
0.02
0.04
Body size (mm)
Rat
e of
cha
nge
(est
imat
e)
40 60 80 100 120 140
-0.04
-0.02
0.00
0.02
0.04
Phenological breadth (days)
Rat
e of
cha
nge
(est
imat
e)
42 44 46 48 50
-0.04
-0.02
0.00
0.02
0.04
Northernmost latitude recorded
Rat
e of
cha
nge
(est
imat
e)
!
Oligolectic Polylectic
-0.04
-0.02
0.00
0.02
0.04R
ate
of c
hang
e (e
stim
ate)
1 2 3 4 5 6
-0.04
-0.02
0.00
0.02
0.04
Body size (mm)
Rat
e of
cha
nge
(est
imat
e)
40 60 80 100 120 140
-0.04
-0.02
0.00
0.02
0.04
Phenological breadth (days)
Rat
e of
cha
nge
(est
imat
e)
42 44 46 48 50
-0.04
-0.02
0.00
0.02
0.04
Northernmost latitude recorded
Rat
e of
cha
nge
(est
imat
e)
!
Causes:Land use Change
Winfree, Bartomeus, Cariveau 2011 AREES
265 published studies, contributing a total of 674 measures of pollinator response to anthropogenic land use
40%47%
13%
22%29%
49%
32%27%
41%
39%39%
21%
39%30%
30%
Bees Butterflies Syrphid flies
Birds Bats
ES42CH01-Winfree ARI 26 September 2011 12:49
?
? ?
?
?
?
? ?
?
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300 to 3,000 m radius
a
b
Figure 3Schematic showing the two study designs contrasted in this review. (a) Design focused on surroundinglandscape cover. Sampling is generally done within a fixed habitat type. In the most common design, sitesvary in the proportion of surrounding land cover composed of specific habitat types such as forest (dark green)or agriculture ( yellow). The radius at which landscape cover is assessed varies across studies but is typicallybetween 300 and 3,000 m. Other designs, which we include in this category, vary either the linear distance tothe nearest habitat patch or the area of the habitat patch. (b) Design focused on local land-use type. Thesestudies compare pollinator communities among different habitat types. The surrounding landscape coverand the spatial extent of the habitat type where pollinators are sampled are generally not reported.
Figure 4)]. Bees and butterflies both show strong negative responses to land-use change in extremesystems, but more mixed responses in moderate systems (Supplemental Tables 2 and 3). Extremeland use causes a strong decrease in abundance and/or richness (e.g., Aizen & Feinsinger 1994,Koh & Sodhi 2004, Kremen et al. 2002, Ockinger & Smith 2006), whereas studies in moderatelyanthropogenic landscapes find more varied responses (e.g., Bartomeus et al. 2010, Bergman et al.2008).
Study designs that make comparisons across habitat types, rather than across landscape gra-dients, find even fewer negative effects, and responses are predominantly positive for most taxa(Supplemental Table 4). For bees, the ratio of negative-to-positive responses decreases from8.2 for extreme landscape studies to 2.0 for moderate landscape studies, to 0.5 for across-habitatcomparisons. For butterflies, the ratios decrease from 6.0 to 3.0 to 1.1, respectively (Supple-mental Tables 2–4). The responses of syrphid flies and vertebrates are difficult to interpretdue to the limited number of landscape-scale studies that have been conducted (SupplementalTables 2 and 3).
The reason why pollinator abundance and/or richness often decrease with increasing humanland use in the surrounding landscape, but increase with conversion of natural to anthropogenic
8 Winfree · Bartomeus · Cariveau
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ES42CH01-Winfree ARI 26 September 2011 12:49
a Extreme habitat loss
Abundance (31)
Richness (17)
b Moderate habitat loss
–1.4 –1.2 –1.0 –0.8 –0.6 –0.4Hedge’s d
–0.2 0.0 0.2 0.4
Abundance (20)
Richness (13)
–1.2 –1.0 –0.8 –0.6 –0.4Hedge’s d
–0.2 0.0 0.2 0.4
Figure 4A meta-analysis of bee responses to land use. Weighted-mean effect sizes for changes in bee abundance andspecies richness in study systems where land use was (a) extreme (!5% natural habitat cover remaining in thesurrounding landscape, "1 km to the nearest natural habitat, or !1-ha habitat fragment) and (b) moderate(all other studies not classified as extreme). The effect size, Hedge’s d, can be interpreted as the inverse-variance-weighted difference in abundance or richness of bees between natural and disturbed conditions,measured in units of standard deviations (Gurevitch & Hedges 2001). Positive values of d imply positiveeffects of anthropogenic disturbance on bees, whereas negative d values imply negative effects. Error bars are95% confidence intervals. Sample sizes are given in parentheses. Modified from Winfree et al. (2009).
habitat types, is difficult to discern using only the information reported in the published literature.In particular, studies comparing across local land-use types rarely report the composition of thesurrounding landscape, thus leaving this variable uncontrolled. However, it seems probable thatthe comparisons across local land-use types are, on average, studying land-use change at a smallerspatial scale than are the comparisons across gradients in surrounding land cover. If this is thecase, then pollinators appear to respond increasingly negatively as both the spatial scale and extentof land-use conversion increase. It is difficult to generalize on this point because the few studiesthat have been designed to explicitly compare the relative effects of local habitat type conversionwith land-use change in the surrounding landscape have found mixed effects (Gabriel et al. 2010,Haenke et al. 2009, Holzschuh et al. 2010, Koh & Sodhi 2004, Williams & Kremen 2007).Furthermore, most of these studies contrasted organic versus conventional agriculture locallyrather than comparing natural to anthropogenic habitat types. Lastly, a related design has beenused in the context of pollinator restorations to investigate the effectiveness of small-scale habitatrestorations in different landscape contexts. These studies find an interaction between the localand the landscape scales, such that the transition from locally unrestored to restored habitat resultsin greater biodiversity benefits in intensively human-used landscapes (reviewed in Winfree 2010),as originally hypothesized by Tscharntke et al. (2005).
www.annualreviews.org • Pollinators in Anthropogenic Habitats 9
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ES42CH01-Winfree ARI 26 September 2011 12:49
?
? ?
?
?
?
? ?
?
?
300 to 3,000 m radius
a
b
Figure 3Schematic showing the two study designs contrasted in this review. (a) Design focused on surroundinglandscape cover. Sampling is generally done within a fixed habitat type. In the most common design, sitesvary in the proportion of surrounding land cover composed of specific habitat types such as forest (dark green)or agriculture ( yellow). The radius at which landscape cover is assessed varies across studies but is typicallybetween 300 and 3,000 m. Other designs, which we include in this category, vary either the linear distance tothe nearest habitat patch or the area of the habitat patch. (b) Design focused on local land-use type. Thesestudies compare pollinator communities among different habitat types. The surrounding landscape coverand the spatial extent of the habitat type where pollinators are sampled are generally not reported.
Figure 4)]. Bees and butterflies both show strong negative responses to land-use change in extremesystems, but more mixed responses in moderate systems (Supplemental Tables 2 and 3). Extremeland use causes a strong decrease in abundance and/or richness (e.g., Aizen & Feinsinger 1994,Koh & Sodhi 2004, Kremen et al. 2002, Ockinger & Smith 2006), whereas studies in moderatelyanthropogenic landscapes find more varied responses (e.g., Bartomeus et al. 2010, Bergman et al.2008).
Study designs that make comparisons across habitat types, rather than across landscape gra-dients, find even fewer negative effects, and responses are predominantly positive for most taxa(Supplemental Table 4). For bees, the ratio of negative-to-positive responses decreases from8.2 for extreme landscape studies to 2.0 for moderate landscape studies, to 0.5 for across-habitatcomparisons. For butterflies, the ratios decrease from 6.0 to 3.0 to 1.1, respectively (Supple-mental Tables 2–4). The responses of syrphid flies and vertebrates are difficult to interpretdue to the limited number of landscape-scale studies that have been conducted (SupplementalTables 2 and 3).
The reason why pollinator abundance and/or richness often decrease with increasing humanland use in the surrounding landscape, but increase with conversion of natural to anthropogenic
8 Winfree · Bartomeus · Cariveau
Ann
u. R
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For
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ES42CH01-Winfree ARI 26 September 2011 12:49
?
? ?
?
?
?
? ?
?
?
300 to 3,000 m radius
a
b
Figure 3Schematic showing the two study designs contrasted in this review. (a) Design focused on surroundinglandscape cover. Sampling is generally done within a fixed habitat type. In the most common design, sitesvary in the proportion of surrounding land cover composed of specific habitat types such as forest (dark green)or agriculture ( yellow). The radius at which landscape cover is assessed varies across studies but is typicallybetween 300 and 3,000 m. Other designs, which we include in this category, vary either the linear distance tothe nearest habitat patch or the area of the habitat patch. (b) Design focused on local land-use type. Thesestudies compare pollinator communities among different habitat types. The surrounding landscape coverand the spatial extent of the habitat type where pollinators are sampled are generally not reported.
Figure 4)]. Bees and butterflies both show strong negative responses to land-use change in extremesystems, but more mixed responses in moderate systems (Supplemental Tables 2 and 3). Extremeland use causes a strong decrease in abundance and/or richness (e.g., Aizen & Feinsinger 1994,Koh & Sodhi 2004, Kremen et al. 2002, Ockinger & Smith 2006), whereas studies in moderatelyanthropogenic landscapes find more varied responses (e.g., Bartomeus et al. 2010, Bergman et al.2008).
Study designs that make comparisons across habitat types, rather than across landscape gra-dients, find even fewer negative effects, and responses are predominantly positive for most taxa(Supplemental Table 4). For bees, the ratio of negative-to-positive responses decreases from8.2 for extreme landscape studies to 2.0 for moderate landscape studies, to 0.5 for across-habitatcomparisons. For butterflies, the ratios decrease from 6.0 to 3.0 to 1.1, respectively (Supple-mental Tables 2–4). The responses of syrphid flies and vertebrates are difficult to interpretdue to the limited number of landscape-scale studies that have been conducted (SupplementalTables 2 and 3).
The reason why pollinator abundance and/or richness often decrease with increasing humanland use in the surrounding landscape, but increase with conversion of natural to anthropogenic
8 Winfree · Bartomeus · Cariveau
Ann
u. R
ev. E
col.
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ES42CH01-Winfree ARI 26 September 2011 12:49
a Extreme habitat loss
Abundance (31)
Richness (17)
b Moderate habitat loss
–1.4 –1.2 –1.0 –0.8 –0.6 –0.4Hedge’s d
–0.2 0.0 0.2 0.4
Abundance (20)
Richness (13)
–1.2 –1.0 –0.8 –0.6 –0.4Hedge’s d
–0.2 0.0 0.2 0.4
Figure 4A meta-analysis of bee responses to land use. Weighted-mean effect sizes for changes in bee abundance andspecies richness in study systems where land use was (a) extreme (!5% natural habitat cover remaining in thesurrounding landscape, "1 km to the nearest natural habitat, or !1-ha habitat fragment) and (b) moderate(all other studies not classified as extreme). The effect size, Hedge’s d, can be interpreted as the inverse-variance-weighted difference in abundance or richness of bees between natural and disturbed conditions,measured in units of standard deviations (Gurevitch & Hedges 2001). Positive values of d imply positiveeffects of anthropogenic disturbance on bees, whereas negative d values imply negative effects. Error bars are95% confidence intervals. Sample sizes are given in parentheses. Modified from Winfree et al. (2009).
habitat types, is difficult to discern using only the information reported in the published literature.In particular, studies comparing across local land-use types rarely report the composition of thesurrounding landscape, thus leaving this variable uncontrolled. However, it seems probable thatthe comparisons across local land-use types are, on average, studying land-use change at a smallerspatial scale than are the comparisons across gradients in surrounding land cover. If this is thecase, then pollinators appear to respond increasingly negatively as both the spatial scale and extentof land-use conversion increase. It is difficult to generalize on this point because the few studiesthat have been designed to explicitly compare the relative effects of local habitat type conversionwith land-use change in the surrounding landscape have found mixed effects (Gabriel et al. 2010,Haenke et al. 2009, Holzschuh et al. 2010, Koh & Sodhi 2004, Williams & Kremen 2007).Furthermore, most of these studies contrasted organic versus conventional agriculture locallyrather than comparing natural to anthropogenic habitat types. Lastly, a related design has beenused in the context of pollinator restorations to investigate the effectiveness of small-scale habitatrestorations in different landscape contexts. These studies find an interaction between the localand the landscape scales, such that the transition from locally unrestored to restored habitat resultsin greater biodiversity benefits in intensively human-used landscapes (reviewed in Winfree 2010),as originally hypothesized by Tscharntke et al. (2005).
www.annualreviews.org • Pollinators in Anthropogenic Habitats 9
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For
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Causes:Climate change
Bartomeus et al. 2011 PNAS
days
from
1 Ja
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Phenology
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Mean April Temperature
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-10 species (Osmia, Andrena, Colletes & Bombus)-Early spring (Bombus queens)
days
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-Latitude-Sex-Day of collection
-3447 specimens-763 collectors
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{
~10 days of mean advance
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{
most dramatic advance in the last 40 years
{
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Males
Females
Photo: AD Howell
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Slope
By species:
a measure of flight season for each species
Adva
ncing
rate
(day
s/yea
r)
Andrena crataegi
May
Adva
ncing
rate
(day
s/yea
r)
Bombus impatiensAd
vanc
ing ra
te (d
ays/y
ear)
Osmia lignariaAdva
ncing
rate
(day
s/yea
r)
Colletes inaequalisApril
Adva
ncing
rate
(day
s/yea
r)
Why Bee phenology is important?
85% of world plants are to some degree pollinated by animals (Ollerton et al 2011)
Bees are the most effective pollinators (Neff & Simpson 1993)
Interactions have their own timing
1885-2003 1936-1999 1936-2002 1971-1999
-0.4
-0.3
-0.2
-0.1
0.0
Slope
We used 4 Published plant datasets in our study areaAll plants are commonly visited by the studied bees
Ad
vanc
ing ra
te (d
ays/y
ear)
1885-2003 1936-1999 1936-2002 1971-1999
-0.4
-0.3
-0.2
-0.1
0.0
Slope
Adva
ncing
rate
(day
s/yea
r)Primack et al. 2004 (Massachusetts)
No significant difference.27 Plant species
1885-2003 1936-1999 1936-2002 1971-1999
-0.4
-0.3
-0.2
-0.1
0.0
Slope
Adva
ncing
rate
(day
s/yea
r)Bradley et al. 1999 (Wisconsin)
24 Plant speciesNo significant difference.
1885-2003 1936-1999 1936-2002 1971-1999
-0.4
-0.3
-0.2
-0.1
0.0
Slope
Adva
ncing
rate
(day
s/yea
r)Cook et al. 2008 (New York State)
11 Plant speciesNo significant difference.
1885-2003 1936-1999 1936-2002 1971-1999
-0.4
-0.3
-0.2
-0.1
0.0
Slope
Adva
ncing
rate
(day
s/yea
r)Abu-Asab et al. 2001 (Washington DC )
44 Plant speciesNo significant difference.
1885-2003 1936-1999 1936-2002 1971-1999
-0.4
-0.3
-0.2
-0.1
0.0
Slope
Adva
ncing
rate
(day
s/yea
r)
1885-2003 1936-1999 1936-2002 1971-1999
-0.4
-0.3
-0.2
-0.1
0.0
Slope
Adva
ncing
rate
(day
s/yea
r)
1885-2003 1936-1999 1936-2002 1971-1999
-0.4
-0.3
-0.2
-0.1
0.0
Slope
Adva
ncing
rate
(day
s/yea
r)
Both “early” Bees and Plants show faster advances
Biodiversity as an insurance
Bartomeus et al (in review)
1960 1970 1980 1990 2000 2010
100
120
140
160
180
200
Year
Col
lect
ion
day
1960 1970 1980 1990 2000 2010
100
120
140
160
180
200
Year
Col
lect
ion
day
year : p = 0.8; interaction sp*year : p = 0.01
baseline asynchrony
stability
year : p = 0.8; interaction sp*year : p = 0.01
baseline asynchrony
stability
Consequencesfor ecosystem
servicesBartomeus & Winfree 2013 F1000Research
76% of crops are animal dependent (Klein et al 2007)
Reports
/ http://www.sciencemag.org/content/early/recent / 28 February 2013 / Page 1/ 10.1126/science.1230200
Human persistence depends on many natural processes, termed ecosys-tem services, which are usually not accounted for in market valuations. Global degradation of such services can undermine the ability of agricul-ture to meet the demands of the growing, increasingly affluent, human population (1, 2). Pollination of crop flowers provided by wild insects is one such vulnerable ecosystem service (3), as their abundance and diver-sity are declining in many agricultural landscapes (4, 5). Globally, yields of insect-pollinated crops are often managed for greater pollination through the addition of honey bees (Apis mellifera L.) as an agricultural input (Fig. 1) (6–8). Therefore, the potential impact of declines in wild pollinators on crop yields is largely unknown, as is whether increasing application of honey bees (9) compensates for losses of wild pollinators, or even promotes these losses.
Wild insects may increase the proportion of flowers that develop into mature fruits or seeds (fruit set), and therefore crop yield (e.g., Kg haí�, fig. S1), by contributing to pollinator abundance, species number (rich-ness), and (or) equity in relative species abundance (evenness). Increased pollinator abundance, and therefore visitation rate to crop flowers, should augment fruit set at a decelerating rate until additional individuals do not further increase (e.g., pollen saturation), or even decrease (e.g., pollen excess) fruit set (10–12). Richness of pollinator species should increase the mean, and reduce the variance, of fruit set (13), because of
complementary pollination among species (14, 15), facilitation (16, 17), or “sampling effects” (18), among other mechanisms (19, 20). Pollinator evenness may enhance fruit set via complementarity, or diminish it if a dominant species (e.g., honey bee) is the most effective pollinator (21). To date, the few studies on the im-portance of pollinator richness for crop pollination have revealed mixed results (22), the effects of evenness on pollination services remain largely unknown, and the impact of wild-insect loss on fruit set has not been evaluated globally for animal-pollinated crops.
We tested four predictions arising from the assumption that wild insects effectively pollinate a broad range of crops, and that their role can be re-placed by increasing the abundance of honey bees in agricultural fields: (1) for most crops, wild-insect and honey bee visitation enhances pollen deposition on stigmas of flowers; (2) consequently, for most crops, wild-insect and honey bee visitation im-proves fruit set; (3) visitation by wild insects promotes fruit set only when honey bees visit infrequently (i.e., negatively interacting effects between wild-insect visitation and honey bee visitation); and (4) pollinator assem-blages with more species benefit fruit set only when honey bees visit infre-quently (i.e., negatively interacting effects between richness and honey bee visitation).
To test these predictions we col-lected data at 600 fields on all conti-
nents, except Antarctica, for 41 crop systems (Fig. 1). Crops included a wide array of animal-pollinated, annual and perennial fruit, seed, nut, and stimulant crops; predominately wind-pollinated crops were not con-sidered (fig. S2 and table S1). Sampled fields were subject to a diversity of agricultural practices, ranging from extensive monocultures to small and diversified systems (fig. S2 and table S1), fields stocked with low to high densities of honey bees (Fig. 1 and table S2), and fields with low to high abundance and diversity of wild insects (fig. S3 and table S2). For each field, we measured flower visitation per unit of time (hereafter “visitation”) for each insect species, from which we estimated species richness and evenness (23). We quantified pollen deposition for 14 sys-tems as the number of pollen grains per stigma, and fruit set (a key com-ponent of crop yield, fig. S1) for 32 systems as the percentage of flowers setting mature fruits or seeds. Spatial or temporal variation of pollen deposition and fruit set were measured as the coefficient of variation (CV) over sample points or days within each field (10). The multilevel data provided by fields within systems were analyzed with general linear mixed-effects models that included crop system as a random effect, and wild-insect visitation, honey bee visitation, evenness, richness, and all their interactions as fixed effects. Best-fitting models were selected based on Akaike’s Information Criterion (AIC) (23).
In agreement with the first prediction, crops in fields with more
Wild Pollinators Enhance Fruit Set of Crops Regardless of Honey Bee Abundance Lucas A. Garibaldi,1* Ingolf Steffan-Dewenter,2 Rachael Winfree,3 Marcelo A. Aizen,4 Riccardo Bommarco,5 Saul A. Cunningham,6 Claire Kremen,7 Luísa G. Carvalheiro,8,9 Lawrence D. Harder,10 Ohad Afik,11 Ignasi Bartomeus,12 Faye Benjamin,3 Virginie Boreux,13,14 Daniel Cariveau,3 Natacha P. Chacoff,15 Jan H. Dudenhöffer,16 Breno M. Freitas,17 Jaboury Ghazoul,14 Sarah Greenleaf,7 Juliana Hipólito,18 Andrea Holzschuh,2 Brad Howlett,19 Rufus Isaacs,20 Steven K. Javorek,21 Christina M. Kennedy,22 Kristin Krewenka,23 Smitha Krishnan,14 Yael Mandelik,11 Margaret M. Mayfield,24 Iris Motzke,13,23 Theodore Munyuli,25 Brian A. Nault,26 Mark Otieno,27 Jessica Petersen,26 Gideon Pisanty,11 Simon G. Potts,27 Romina Rader,28 Taylor H. Ricketts,29 Maj Rundlöf,5,30 Colleen L. Seymour,31 Christof Schüepp,32,33 Hajnalka Szentgyörgyi,34 Hisatomo Taki,35 Teja Tscharntke,23 Carlos H. Vergara,36 Blandina F. Viana,18 Thomas C. Wanger,23 Catrin Westphal,23 Neal Williams,37 Alexandra M. Klein13
*To whom correspondence should be addressed. E-mail: [email protected]
Affiliations are listed at the end of the text
Diversity and abundance of wild-insect pollinators have declined in many agricultural landscapes. Whether such declines reduce crop yields, or are mitigated by managed pollinators such as honey bees, is unclear. Here we show universally positive associations of fruit set with wild-insect visits to flowers in 41 crop systems worldwide, and thus clearly demonstrate their agricultural value. In contrast, fruit set increased significantly with visitation by honey bees in only 14% of the systems surveyed. Overall, wild insects pollinated crops more effectively, because increase in their visitation enhanced fruit set by twice as much as an equivalent increase in honey bee visitation. Further, visitation by wild insects and honey bees promoted fruit set independently, so high abundance of managed honey bees supplemented, rather than substituted for, pollination by wild insects. Our results suggest that new practices for integrated management of both honey bees and diverse wild-insect assemblages will enhance global crop yields.
on
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d Ecosystem Services Providers
*Richness weakly declining, except for Bombus
*Specific responses are heterogenous. Only 4 species with steep declines.
*Bees with short niche breadth and large body size are more likely to be affected.
*ESP are less affected
Bees and plants have similar responses
Climate change is altering bee phenology
Thank you
This project is been possible thanks to...All collectors that collected the bees
Co-authors: Rachael Winfree, John Ascher, Jason Gibbs, Bryan Danforth, David Wagner, Shannon Hedtke, Sheila Colla, Mia Park adn Dan Cariveau.
Local scale data from Burkle et al 2013
Science
April temperature is highly correlated with collection day.