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Evolution of dispersal in heterogeneous
environments
Ace North, Stephen Cornell & Otso Ovaskainen
All species disperse (=move) at some part of their life-cycle. The
ability to disperse influences the demographic dynamics of
especially those species that live in fragmented landscapes. In
turn, the structure of the landscape is expected to impose
selection on dispersal.
How does evolution of dispersal depend on the
interplay between landscape structure and species
properties?
An example of a species living in fragmented
landscapes – the Glanville fritillary metapopulation
One of the most studied systems in population
biology, with >100 papers and several books
American Naturalist, Analytica Chimica Acta , Analytical And Bioanalytical Chemistry,
Annales Zoologici Fennici, Annals Of The Entomological Society Of America, Basic And
Applied Ecology, Behavioral Ecology, Biological Conservation, Biological Journal Of The
Linnean Society, Biological Reviews, Bulletin Of Mathematical Biology, Conservation
Biology, Ecography, Ecological Applications, Ecological Entomology, Ecological Modelling,
Ecology, Ecology Letters, Entomologica Fennica, European Physical Journal B, Evolution,
Evolutionary Ecology, Journal Of Animal Ecology, Journal Of Applied Ecology, Journal Of
Applied Probability, Journal Of Chemical Ecology, Journal Of Differential Equations, Journal
Of Natural History, Journal Of Theoretical Biology, Landscape Ecology, Mathematical
Biosciences, Molecular Ecology Notes, Nature, New Zealand Journal Of Ecology, Nucleic
Acids Research, Oecologia, Oikos, Plos Biology, PNAS, Proceedings Of The Royal Society
B-biological Sciences, Sexually Transmitted Diseases, Science, Theoretical Population
Biology, …
Variation among individuals is raw material for
selection
- There is great variation in movement behaviour
Ålandnew
new
Åland
5,460
5,460 mm
2,300mm
2,300
6:13:37
6:13:37
PgiAC
AC
Pgi
2/52
2/52
R2
R2
R3
R4
Estonia
Estonia
590mm
590
480mm
480
6:05:24
6:05:24
PgiAA
AA
Pgi
33/52
33/52
Tracking butterfly movements
with harmonic radar
Ovaskainen et al. PNAS 2008
R4
R5
Ålandold
old
Åland
110mm
110
100mm
100
6:16:22
6:16:22
PgiAC
AC
Pgi
31/52
31/52
R1
R1
Ålandnew
new
Åland
2,110mm
2,110
1,050mm
1,050
5:10:02
5:10:02
PgiAC
AC
Pgi
3/52
3/52
200 m
m
200
Mobility in the field is correlated with metabolic
performance, and it is heritable (partly genetically
controlled)
Measuring the flight metabolism (CO2 production during flight)
PGI (phosphoglucose isomerase) genotype:
AA homozygote
AC heterozygote
Niitepold et al. Ecology 2009
Does landscape structure matter for the evolution of
dispersal?
Key finding from the empirical and modelling
studies: rapid evolutionary changes in space and
time
• Isolated patches are colonized mainly by the most mobile
•
•
females
After colonization the local population evolves towards a less
mobile one: mobile individuals emigrate out while sedentary
individuals stay
At the network level, small networks with high turnover rate have
on average more mobile individuals
Patch level
New
Network level
pop
ulat
ions
ons
pulati
Old po
Zheng et al. Phil. Trans. B 2009
More generally, how does environmental heterogeneity
affect evolution of dispersal?
Incorporating environmental heterogeneity into continuous-space models
Landscape structure controlled by patch density, size, quality and turnove
•
Distribution of patches
p = ∑ δ ( xi )
i∈P
•
Patches appear at
random locations at
rate θσ (per unit area)
•
Patches disappear at
rate σ (per patch)
•
Landscape quality
ω = ΨP ∗ p
•
The kernel controls
patch size (length
scale) and patch
quality (integral)
Evolutionary model of dispersal
Individual with
short-ranged
dispersal kernel
•
Parameters at low density:
fecundity f, establishment
e, death d.
•
Density-dependence
affects death rate.
Countour lines: local
density of individuals
•
Landscape quality affects
fecundity
Individual with
long-ranged
dispersal
kernel
f = f 0ω
dN
dt
Mean-field model: logistic population growth:
= rN (1 − N / K )
Methods: ESS and ESFD
Evolutionary Stable Strategy and Evolutionary Stable Frequency Distribution
Residents, one realization
Mutants, one realization
Eigenvalue from
perturbation analysis
Mutants, average over realizations
h2=1-10-5
h2=0.75
h2=
0
h2=1-10-4
h2=1-10-3
Results I: effect of landscape structure
STATIC LANDSCAPES,
TOTAL AMOUNT OF
HABITAT CONSTANT
DYNAMIC LANDSCAPES,
TOTAL AMOUNT OF
HABITAT CONSTANT
STATIC LANDSCAPES
DYNAMIC LANDSCAPES
UNDERGOING HABITAT LOSS
UNDERGOING HABITA LOSS
Structural stability of the results?
ESS versus ESFD
Alternative assumptions on life-history
ESS and ESFD approaches tell the same
story
Alternative assumptions on life-history
Density-depence can...
• increase death rate
• reduce fecundity
• reduce establishment
Landscape quality can
affect...
• death rate (at low density)
• fecundity (at low density)
• establishment (at low density)
• carrying capacity
All 12 models tell the same qualitative
story...
DYNAMIC LANDSCAPES,
TOTAL AMOUNT OF
HABITAT CONSTANT
...but they differ in their quantitative
predictions
Density-depence affects:
Habitat quality affects:
STATIC
LANDSCAPES, TOTAL
AMOUNT OF
HABITAT CONSTANT
DYNAMIC
LANDSCAPES,
TOTAL AMOUNT
OF HABITAT
CONSTANT
Challenges for the future
Methods
• Extinction thresholds & other phase transitions
Applications
• Local adaptation (poster by Ace North)
Connection to reality
• Testing the predictions!