My phd thesis defense presentation.

1. Variation in species interactions and
their evolutionary consequences
Scott Alan Chamberlain
Ph.D. Thesis Defense
Wedenesday, 30 May, 2012

2. 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

3. Variation in species interactions
• Not error variation in outcome
in one context
Site 1
• The variation in outcomes
among more than one context
Site 1 Site 2

4. Variation in outcomes is common
Mutualism Competition/Facilitation
With Ants Without Ants
Plants producing flowers or fruit (%)
Low Elevation High Elevation
Herbivory outcome for Acacia trees Outcomes vary from competition at low
varies with ant species identity elevation to facilitation at high elevation
Palmer et al. 2008, Callaway et al. 2002 More E.G.: Cushman and Whitham 1989, Thompson and Cunningham 2002,
Pennings and Silliman 2005, Navarrete and Berlow 2006

5. Variation in outcomes is important
Populations Communities Evolution
Cactus Population Growth
Effect of Herbviores on
Less Stability
Selection Strength
Interaction Strength
Lower species richness
Variance
Greater Stability
Low Mid High Higher species richness
Elevation Interaction Strength Site
Mean
Miller et al. 2009 Kokkoris et al. 2002 Rudgers & Strauss 2004

6. 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?

7. 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?

8. How do types of species interactions
differ in variation?
Competition Predation Mutualism
-/- +/- +/+

9. How do gradients differ in importance
for variation in species interactions?
?
Space Time

10. Outline
• Part I : What are the evolutionary
consequences of agriculturally altered species
interactions?
• Part II: How variable are species interaction
outcomes?

11. Part I
--
What are the evolutionary
consequences of agriculturally altered
species interactions?

12. 12
Foley et al. 2005 Science

13. 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
13
Ellstrand et al. 1999

14. Mutualists Antagonists
VS.
Natural selection
Meehan et al. 2011, Devictor et al. 2008,
Ekroos et al. 2010, Dormann et al. 2007 14

15. Spatial variation in importance of
mutualists and antagonists on selection
Site 1 Site 2
Flower Flower
Traits Traits
Mutualists Mutualists Antagonists
Plant Plant
Fitness Fitness
15
Gomez et al. 2009 Ecol. Monog.

16. Abundance and community structure
Abundance Community Structure

17. 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?

18. Study System: Helianthus annuus
Wild sunflower
Mutualist Antagonists
(H. annuus texanus)
Pollinators Seed predators
Halictus ligatus Neolasioptera (Diptera)
Isophrictis (Lepidoptera)
Megachile spp.
Crop sunflower
(H. annuus) Smicronyx (Coleoptera)
Apis mellifera Folivores

19. Study Design
Natural habitat
Agricultural
landscape
Other Crop
[corn/sorghum/wheat/cotton]
Far
Distance
~ 2.5 km
Sunflower
Crop
Distance
Near ≤ 10 m
Data Collected
• Pollinators: pollinator
Proximity to sunflowers (2 levels)
observations
X
• Seed predators: counted
Seed source (2 levels)
damaged seeds
• Folivores: leaf damage @ 5 sites in ‘10, @ 2 sites in ‘11

20. Abundance - mutualists
Abundance
Greater Near vs. Far
Far Near
Far
Abundance
Visits inflorescence-1 min-1
Near
Proximity to crop
sunflowers

21. Abundance - antagonists
Greater Far vs. Near
Abundance
Neolasioptera
Far Near
Far
Abundance
Near
Isophrictis
Proximity to crop
sunflowers
Smicronyx

22. Abundance
Far
Near
Sucking folivore abundance Chewing folivore abundance
Greater Far vs. Near
Abundance - antagonists

23. Community structure - mutualists & antagonists
Differs Near vs. Far for both M and A
Mutualists
Far
Near
Antagonists

24. Abundance
Beta-diversity
Proximity to crop
sunflowers
Proximity, P = 0.004
• This pattern may
be due to large
crop sunflower
Abundance
Far resource pulse
driving greater
Near
diversity among
sites
Proximity to crop
sunflowers
* No difference for antagonists

25. How does proximity to crop sunflowers affect selection
on H.a. texanus flower traits?
Disk diameter
Ray width
Ray length
Number of rays
-> Five of nine heritable in narrow-
Petal size
sense (sire-offspring regression)
Throat width
Throat length
Proximal throat size
Floral tube size

26. 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

27. 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

28. Natural selection Differs Near vs. Far in some traits
Total Selection (s’) Direct Selection (β)
Far Near Far Near
Disk diameter
NS
Ray width
Ray length
Number of rays ANCOVA NS
trait * proximity
trait * site * proximity
NS
trait * year * proximity
Petal size
trait * year * site * proximity
Throat width NS NS
NS NS
Throat length
Proximal throat size
Floral tube size NS NS

29. Natural selection – Dispersion
• This pattern
may be due to
Selection (s’ or β) large crop
sunflower
resource pulse
driving greater
Far Near diversity
Proximity to crop sunflowers
among sites

30. Do mutualists and antagonists contribute to selection
on floral traits differently?
Flower traits
Antagonists Mutualists
Plant fitness

31. Multi-group analysis to compare paths
between treatments (Near vs. Far)
Principal components
Analysis: reduced Floral Traits Inflorescence Traits
dimensionality, using
just PC1 for each
Seed predators and
pollen deposition Isophrictis sp Neolasioptera helianthi Pollen
standardized to
mean = 0, sd = 1
W=
Relative Plant Fitness

32. Far Near
Site 1 -0.07
-0.06 0.02
0.004
2011
0.002 -0.01
Site 2
2011

33. 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

34. 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

35. 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?

36. Part II
--
How variable are species interaction
outcomes?

37. Questions
• A) How do different species interaction types
differ in variation in outcomes?
• B) What are relative importance of drivers of
variation in outcomes?

38. 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

39. Site B Site C Site D Site E
Site A Mean Interaction Outcome Negative RII = better w/o herbivory
from Armas et al. (2004) Positive RII = better with herbivory
RII = X C - X E X C + X E
Variation in Interaction Outcome Magnitude Change in sign of Interaction Outcome
Site A 0 Site A
Site B 1 Site B
SDRII Site C
CVRII = ´100 0 or 1 -1 Site C
X RII Site D -1 Site D
Site E 0 Site E

40. Gradients that drive variation in interaction outcome
Abiotic Nutrients
Space Across sites
Species identity Sp. A interacts with either sp. B or sp. C
Time Across hours, days, years
3rd party presence Two species w/ or w/o 3rd species

41. 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)

42. How do different species interaction types differ in variation in
outcomes?
Predation Mean Strength Interaction Complexity Expected Varation
Strong More specialized Low
Competition
?? ?? ??
Mutualism
Weak More generalized High

43. How do different species interaction
types differ in variation in outcomes?
A Predation Competition Mutualism
CV*of Effect Size
CV effect size
150
100 = =
50
0
B c
Proportion of studies
Proportion of studies
b
with sign change
0.6 a
0.4
< <
0.2
(120) (143) (90)
0.0
p c m

44. What are relative importance of
drivers of variation in outcomes?
250
ab a
CV of Effect Size
200
CV* effect size
ab
150
100 b
b
50
(53) (46) (117) (97) (40)
0
ic al ty ral ce
iot ati nti po en
ab sp ide s
es tem pre
ci rty
spe pa
rd
thi

45. Variation highly dependent on context
in which the interaction occurs
abiotic spatial species identity temporal third party presence
CV* Effect Size
400
CV ofeffect size
300
200 a
ab
100
b
0
b a
Proportion of studies
b
with sign of studies
0.8 b b
Proportion change
a c b
a b b
0.6
a a a
a
0.4
0.2
(21) (26) (6) (11) (16) (19) (53) (37) (27) (26) (47) (24) (9) (17) (14)
0.0
p c m p c m p c m p c m p c m

46. Variation highly dependent on context
in which the interaction occurs
abiotic spatial species identity temporal third party presence
Predation - Opposite of
CV of Effect Size
400
prediction that
CV* effect size
300
specialized predation
200 a
may lead to less
ab
Mutualism variation
100
b
0
Proportion of studies - Instead, when you
b a
interact with more
Proportion of studies
b
with sign change
with sign of studies
0.8 b b
Proportion change
a c species, each
b
a b b
0.6 interaction is more
a a a
a
0.4
equivalent, and are
not that variable
0.2
(21) (26) (6) (11) (16) (19) (53) (37) (27) (26) (47) (24) (9) (17) (14)
0.0
p c m p c m p c m p c m p c m

47. Variation highly dependent on context
in which the interaction occurs
abiotic spatial species identity temporal third party presence
400
CV* Effect Size
- In predation studies, species
CV ofeffect size
300 were largely animals, which
are more mobile than plants
200 a
ab
100 - In competition and mutualism
b
studies, species were largely
0
b a
plants, which are immobile
Proportion of studies
0.8 b b
with sign of studies
b
Proportion change
c b
0.6 a
a - Interactions involvingb
b
a
a immobile plants may be more a
a
0.4 variable along abiotic gradients
as they cannot escape them
0.2
(21) (26) (6) (11) (16) (19) (53) (37) (27) (26) (47) (24) (9) (17) (14)
0.0
p c m p c m p c m p c m p c m

48. 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
Species identity > Abiotic Space > Time > 3rd party presence
– Implications:
• Some sources of variation in species interactions should be given priority (i.e.,
species identity), especially in new study systems

49. 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?

50. 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?

51. Thanks to
• Committee • Microscopy
– Jennifer Rudgers – John Slater
– Ken Whitney – Robert Langsner
– Volker Rudolf • Meta-analysis
– Dennis Cox – Tens of authors who provided
• Help data
– Toby Liss • Discussion
– Wael Al Wawi – The R-W lab
– Charles Danan – Steve Hovick
– Yosuke Akiyama – Tom Miller
– Neha Deshpande • Of course: Katherine Horn
– Rohini Sigireddi
– Prudence Sun
– Morgan Black
– Edward Realzola

52. Mean / Variation Interaction Complexity
Predation Argument Argument
+
-
Competition
- -
Mutualism/Facilitation
+
-
+

53. OK, BUT WHAT ARE THE CONSEQUENCES?

54. Consequences of Variation in Outcome
Ecological
Outcomes between membracids and ants
varied with:
- Time (among years)
- Membracid life stage
- Membracid abundance
And these likely will influence population
dynamics of the interaction
Cushman & Whitham (1989)

55. Consequences of Variation in Outcome
Evolutionary
John Thompson - Distributed Outcomes Distributed Outcomes
Raw Material for Evolution of Species Interactions
Population 1
1
% of Interactions
β 0
-1
0 100
Population 2
Interaction Outcome CV
(-) Antagonistic  Mutualistic (+)
Thompson (2005), Bronstein (1994)

56. Drivers of Variation in Outcome?
-An example of species identity variation
Moth attack
(% of fruits of Opuntia imbricata)
Miller (2007)

57. 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

58. Predation
Mutualism

59. Presence of both mutualists and antagonists may
increase trait diversity
Number of Trees
Principal Component Axis
(cone & seed traits)
59
Siepielski & Benkman 2010