Chamberlain PhD Thesis
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Variation in species interactions and their evolutionary consequences
Scott Alan ChamberlainPh.D. Thesis Defense
Wedenesday, 30 May, 2012
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Species interactions are important across domains of ecology
• Species interactions contribute to:– Population dynamics– Formation and dynamics of food webs– Evolutionary change through natural selection
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Variation in species interactions
• Not error variation in outcome in one context
• The variation in outcomes among more than one context
Site 1
Site 1 Site 2
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Variation in outcomes is common
Palmer et al. 2008, Callaway et al. 2002
Competition/FacilitationMutualism
More E.G.: Cushman and Whitham 1989, Thompson and Cunningham 2002, Pennings and Silliman 2005, Navarrete and Berlow 2006
Herbivory outcome for Acacia trees varies with ant species identity
Plan
ts p
rodu
cing
flow
ers
or fr
uit (
%)
Low Elevation High Elevation
Outcomes vary from competition at low elevation to facilitation at high elevation
With Ants Without Ants
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Variation in outcomes is important
Miller et al. 2009
Populations Communities Evolution
Kokkoris et al. 2002
Interaction Strength Mean
Inte
racti
on S
tren
gth
Varia
nce
Rudgers & Strauss 2004
Greater StabilityHigher species richness
Less StabilityLower species richness
Effec
t of H
erbv
iore
s on
Ca
ctus
Pop
ulati
on G
row
th
Elevation
Low Mid High Sele
ction
Str
engt
h
Site
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Questions
1. What are the evolutionary consequences of variation in species interactions?
2. How do types of species interactions differ in variation?
3. How do gradients differ in importance for variation in species interactions?
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What are the evolutionary consequences of variation in species interactions?
• Variation in abundance and community structure lead to variation in species interactions
• How is natural selection altered in response to these variable interactions?
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How do types of species interactions differ in variation?
- / - + / - + / +
Competition Predation Mutualism
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How do gradients differ in importance for variation in species interactions?
?
Space Time
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Outline
• Part I : What are the evolutionary consequences of agriculturally altered species interactions?
• Part II: How variable are species interaction outcomes?
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Part I--
What are the evolutionary consequences of agriculturally altered species interactions?
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12Foley et al. 2005 Science
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Mechanisms for altered evolution in agricultural landscapes
• Gene flow from crops to wild/weed plants• Evolution of resistance to genetically modified
crops (e.g., Bt cotton)• Evolution of resistance in plant weeds to
chemical herbicides
• Yet, little examination of altered natural selection via altered species interactions
13Ellstrand et al. 1999
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14
Mutualists
VS.
Natural selectionMeehan et al. 2011, Devictor et al. 2008, Ekroos et al. 2010, Dormann et al. 2007
Antagonists
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Spatial variation in importance of mutualists and antagonists on selection
15Gomez et al. 2009 Ecol. Monog.
Flower Traits
Mutualists
Plant Fitness
Flower Traits
Mutualists
Plant Fitness
Antagonists
Site 1 Site 2
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Abundance and community structureAbundance Community Structure
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Questions
Does proximity to crops:1. Alter abundance of mutualists and
antagonists?2. Alter community structure of mutualists and
antagonists? 3. Affect selection on native plant floral traits?4. Alter contribution of mutualists and
antagonists to selection on native plant floral traits?
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Study System: Helianthus annuusMutualistPollinators
Halictus ligatus
Megachile spp.
Apis mellifera
AntagonistsSeed predators
Neolasioptera (Diptera)
Isophrictis (Lepidoptera)
Wild sunflower(H. annuus texanus)
Crop sunflower(H. annuus)
Folivores
Smicronyx (Coleoptera)
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Study Design
Sunflower Crop
Near
Far
Distance≤ 10 m
Distance~ 2.5 km
Agricultural landscape
Other Crop[corn/sorghum/wheat/cotton]
Natural habitat
Proximity to sunflowers (2 levels)X
Seed source (2 levels)
@ 5 sites in ‘10, @ 2 sites in ‘11
Data Collected• Pollinators: pollinator observations• Seed predators: counted damaged seeds• Folivores: leaf damage
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Abundance - mutualistsGreater Near vs. Far
Far
Near
Proximity to cropsunflowers
Abun
danc
e
Far Near
Abun
danc
e
Visi
ts in
flore
scen
ce-1
min
-1
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Abundance - antagonistsGreater Far vs. Near
Far
Near
Proximity to cropsunflowers
Abun
danc
e
Far Near
Abun
danc
e
Smic
rony
xIs
ophr
ictis
Neo
lasi
opte
ra
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Abundance - antagonistsGreater Far vs. Near
Far Near
Abun
danc
e
Suck
ing
foliv
ore
abun
danc
eCh
ewin
g fo
livor
e ab
unda
nce
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Community structure - mutualists & antagonistsDiffers Near vs. Far for both M and A
Far
Near
Mutualists
Antagonists
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Proximity to cropsunflowers
Abun
danc
e
Beta-diversity
• This pattern may be due to large crop sunflower resource pulse driving greater diversity among sites
* No difference for antagonists
Proximity, P = 0.004
Abun
danc
e
Proximity to cropsunflowers
Far
Near
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How does proximity to crop sunflowers affect selection on H.a. texanus flower traits?
-> Five of nine heritable in narrow-sense (sire-offspring regression)
Throat width
Floral tube size
Proximal throat size
Throat length
Petal size
Disk diameter
Ray width
Ray length
Number of rays
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Phenotypic selection analysis
• Total selection (s’)– Measures direct + indirect selection– Simple regression measures calculates covariance
between standardized trait (mean=0, sd=1) and relative fitness
• Direct selection (β)– Measures direct selection on a trait by removing
indirect selection on all other traits in a multiple regression
– Multiple regression with standardized traits (mean=0, sd=1) and relative fitness
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Testing for differences in selection by proximity
• Analysis of Covariance– 2010: five sites
• Model: relative fitness ~ site * proximity * trait• trait * proximity• trait * site * proximity
– 2010 & 2011: two sites• Model: relative fitness ~ year * site * proximity * trait• trait * year * proximity• trait * year * site * proximity
– Total selection• Separate models for each floral trait
– Direct selection• One model including all floral traits
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ANCOVAtrait * proximity
trait * site * proximitytrait * year * proximity
trait * year * site * proximity
Natural selection Differs Near vs. Far in some traits
Throat width
Floral tube size
Proximal throat size
Throat length
Petal size
Disk diameter
Ray width
Ray length
Number of rays
Total Selection (s’) Direct Selection (β)
NS
NS
NS
NS
NS
NS
NS
NS
NS
Far Near Far Near
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Natural selection – Dispersion
Far NearProximity to crop sunflowers
Sele
ction
(s’ o
r β)
• This pattern may be due to large crop sunflower resource pulse driving greater diversity among sites
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Do mutualists and antagonists contribute to selection on floral traits differently?
Antagonists Mutualists
Flower traits
Plant fitness
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Floral Traits Inflorescence Traits
W = Relative Plant Fitness
Neolasioptera helianthiIsophrictis sp Pollen
Seed predators andpollen depositionstandardized to mean = 0, sd = 1
Multi-group analysis to compare pathsbetween treatments (Near vs. Far)
Principal componentsAnalysis: reduced dimensionality, using just PC1 for each
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Site 1 2011
Far Near
Site 22011
-0.07 0.02-0.06 0.004
-0.010.002
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Conclusions Part I
• Sunflower mutualists more abundant near, antagonists more abundant far from crops
• Beta-diversity of mutualists greater near crops• Natural selection altered by proximity to sunflower
crops• Changes in mutualist/antagonist communities drive
differences in selection near vs. far from crops• This is one of few studies to show agricultural
effects on natural selection across a landscape in a native plant species
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Implications
• Mutualist-antagonist framework may be useful in understanding agricultural effects on plant evolution
• Natural selection altered in agricultural landscapes, BUT contrary to expectation
• These results may not be found in non-intensive agricultural landscapes
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Questions
1. What are the evolutionary consequences of variation in species interactions?
2. How do types of species interactions differ in variation?
3. How do gradients differ in importance for variation in species interactions?
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Part II--
How variable are species interaction outcomes?
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Questions
• A) How do different species interaction types differ in variation in outcomes?
• B) What are relative importance of drivers of variation in outcomes?
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Meta-analysis Web of Science search Experimental studies only Interaction outcome w/ & w/o competitor, predator, or mutualist Error estimates & sample sizes available Response variables: abundance, population growth,
reproduction, etc. Responses measured over >1 year, population, or species, etc.
Final dataset 353 papers
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Variation in Interaction Outcome Magnitude
Mean Interaction Outcomefrom Armas et al. (2004)
Site A
Site C Site D Site E
Change in sign of Interaction Outcome
0
0
-1-11
Site B
Site BSite A
Site D
Site C
Site E
Site BSite A
Site D
Site C
Site E
0 or 1
Negative RII = better w/o herbivoryPositive RII = better with herbivory
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Gradients that drive variation in interaction outcome
Time
Species identity
3rd party presence
Abiotic
Space
Nutrients
Across hours, days, years
Sp. A interacts with either sp. B or sp. C
Two species w/ or w/o 3rd species
Across sites
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How do different species interaction types differ in variation in outcomes?
• Mean strength– Mutualisms weaker than antagonisms (Morris et al. 2007)– General sense in literature that mutualisms less important
because so variable (Sachs & Simms 2006)– Weak interactions the most variable (Berlow et al. 1999)
• Interaction complexity– Predation more specialized than mutualism (Gomez et al.
2010)– Strength greater with fewer interactions (Edwards et al.
2010)
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How do different species interaction types differ in variation in outcomes?
Predation
Competition
Mutualism
Interaction ComplexityMean Strength
More specialized
??
More generalized
Expected Varation
Low
High
Strong
Weak
?? ??
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How do different species interaction types differ in variation in outcomes?
p c m
Pro
port
ion
of s
tudi
es
0.0
0.2
0.4
0.6
CV
* ef
fect
siz
e
0
50
100
150
A
bB
(120) (143) (90)
c
a
< <
= =
Prop
ortio
n of
stud
ies
with
sig
n ch
ange
CV o
f Effe
ct S
ize
Predation Competition Mutualism
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CV
* e
ffe
ct s
ize
0
50
100
150
200
250
(53) (46) (117) (97) (40)
ab
ab
a
bb
What are relative importance of drivers of variation in outcomes?
Species id
entity
AbioticSpace
CV o
f Effe
ct S
ize
3rd party
presence
Time
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Variation highly dependent on context in which the interaction occurs
CV
* ef
fect
siz
e
0
100
200
300
400
aba
b
p c m
Pro
port
ion
of s
tudi
es
0.0
0.2
0.4
0.6
0.8
p c m p c m p c m p c m
a a
b
(21) (26) (6) (11) (16) (19) (53) (37) (27) (26) (47) (24) (9) (17) (14)
a a
b
a
bb a
b
c
a
b b
abiotic spatial species identity temporal third party presence
Prop
ortio
n of
stud
ies
with
sig
n ch
ange
CV o
f Effe
ct S
ize
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Variation highly dependent on context in which the interaction occurs
CV
* ef
fect
siz
e
0
100
200
300
400
aba
b
p c m
Pro
port
ion
of s
tudi
es
0.0
0.2
0.4
0.6
0.8
p c m p c m p c m p c m
a a
b
(21) (26) (6) (11) (16) (19) (53) (37) (27) (26) (47) (24) (9) (17) (14)
a a
b
a
bb a
b
c
a
b b
abiotic spatial species identity temporal third party presence
Prop
ortio
n of
stud
ies
with
sig
n ch
ange
CV o
f Effe
ct S
izeC
V*
effe
ct s
ize
0
100
200
300
400
aba
b
p c m
Pro
port
ion
of s
tudi
es
0.0
0.2
0.4
0.6
0.8
p c m p c m p c m p c m
a a
b
(21) (26) (6) (11) (16) (19) (53) (37) (27) (26) (47) (24) (9) (17) (14)
a a
b
a
bb a
b
c
a
b b
abiotic spatial species identity temporal third party presence
Predation
Mutualism
- Opposite of prediction that specialized predation may lead to less variation
- Instead, when you interact with more species, each interaction is more equivalent, and are not that variable
Prop
ortio
n of
stud
ies
with
sig
n ch
ange
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Variation highly dependent on context in which the interaction occurs
CV
* ef
fect
siz
e
0
100
200
300
400
aba
b
p c m
Pro
port
ion
of s
tudi
es
0.0
0.2
0.4
0.6
0.8
p c m p c m p c m p c m
a a
b
(21) (26) (6) (11) (16) (19) (53) (37) (27) (26) (47) (24) (9) (17) (14)
a a
b
a
bb a
b
c
a
b b
abiotic spatial species identity temporal third party presence
CV
* ef
fect
siz
e
0
100
200
300
400
aba
b
p c m
Pro
port
ion
of s
tudi
es
0.0
0.2
0.4
0.6
0.8
p c m p c m p c m p c m
a a
b
(21) (26) (6) (11) (16) (19) (53) (37) (27) (26) (47) (24) (9) (17) (14)
a a
b
a
bb a
b
c
a
b b
abiotic spatial species identity temporal third party presence
CV o
f Effe
ct S
ize - In predation studies, species were largely animals, which are more mobile than plants
- In competition and mutualism studies, species were largely plants, which are immobile
- Interactions involving immobile plants may be more variable along abiotic gradients as they cannot escape them
Prop
ortio
n of
stud
ies
with
sig
n ch
ange
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Conclusions• Types of species interactions differed in outcome variation
– Implications: • We can’t treat different species interactions as equivalent• In interaction webs, it may be most important to understand variation in
mutualistic links
• Types of gradients differed in outcome variation
– Implications: • Some sources of variation in species interactions should be given priority (i.e.,
species identity), especially in new study systems
>
SpaceSpecies identity Abiotic> > >
>
Time 3rd party presence
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Future work• Add other species interaction types: herbivory,
parasitism, facilitation
• Do any variables correlate with variation in species interaction outcomes?– Do body size ratios predict variable outcomes?
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Questions
1. What are the evolutionary consequences of variation in species interactions?
2. How do types of species interactions differ in variation?
3. How do gradients differ in importance for variation in species interactions?
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Thanks to• Committee
– Jennifer Rudgers– Ken Whitney– Volker Rudolf– Dennis Cox
• Help– Toby Liss– Wael Al Wawi– Charles Danan– Yosuke Akiyama– Neha Deshpande– Rohini Sigireddi– Prudence Sun– Morgan Black– Edward Realzola
• Microscopy– John Slater– Robert Langsner
• Meta-analysis– Tens of authors who
provided data
• Discussion– The R-W lab– Steve Hovick– Tom Miller
• Of course: Katherine Horn
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Predation
Competition
Mutualism/Facilitation
Mean / Variation Argument
Interaction ComplexityArgument
+
-
- -
+
+-
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OK, BUT WHAT ARE THE CONSEQUENCES?
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Consequences of Variation in OutcomeEcological
Outcomes between membracids and antsvaried with:
- Time (among years)- Membracid life stage- Membracid abundance
And these likely will influence population dynamics of the interaction
Cushman & Whitham (1989)
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Consequences of Variation in OutcomeEvolutionary
Thompson (2005), Bronstein (1994)
Interaction Outcome CV
Distributed OutcomesRaw Material for Evolution of Species Interactions
β
1
0
-10 100
John Thompson - Distributed Outcomes
% o
f Int
erac
tions
Antagonistic Mutualistic (+)(-)
Population 1
Population 2
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Drivers of Variation in Outcome?-An example of species identity variation
Moth attack
(% of fruits of Opuntia imbricata)
Miller (2007)
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What are the consequences of agriculture
• Populations– ????????
• Communities– Communities often simplified, made more similar
across sites (decreased beta-diversity)– Interaction networks are simplified in agricultural
landscapes• Evolution
– Antagonists (predators, competitors) often XXXX– Mutualists often XXXX
Ekroos et al. 2010, Tylianakis et al. 2007
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Predation
Mutualism
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Presence of both mutualists and antagonists may increase trait diversity
59Siepielski & Benkman 2010
Principal Component Axis (cone & seed traits)
Num
ber o
f Tre
es