Transcript Document

Resolving the paradox of stasis:
models with stabilizing selection
explain evolutionary divergence on
all timescales
Suzanne Estes & Stevan J. Arnold
Introduction
The following slides illustrate the behavior of the
quantitative genetic models for trait evolution
used in Estes & Arnold 2007 Amer Nat 169: 227244. Additional details for the models are given
in that article and in the indicated references.
Disclaimer
The animations in the slides that follow are caricatures
of model behavior, they are not actual simulations. In
actual simulations of these stochastic models, behavior
would vary from replicate run to replicate run. For this
reason, the behavior of the trait mean at any
generation, t, can be characterized by a statistical
distribution, ( zt ) ,with an expected mean and a
variance.
Conventions
• The upper panel in each slide shows the
adaptive landscape (average populations fitness
as a function of average trait value).
• The lower panel in each slide shows the
frequency distribution of a normally-distributed,
phenotypic trait, z, as it evolves in response to the
adaptive landscape.
• In the case of landscapes with an intermediate
optimum, the vertical dotted line marks the
position of that optimum trait value, θ.
NEUTRAL MODEL
W
z
p(z)
z
Lande 1976
W
ADAPTIVE LANDSCAPE
WITH INTERMEDIATE
OPTIMUM
θ
z
p(z)
z
weak stabilizing
selection
W
ADAPTIVE LANDSCAPE
WITH INTERMEDIATE
OPTIMUM
θ
z
p(z)
z
strong stabilizing
selection
DISPLACED OPTIMUM MODEL
θ
W
z
p(z)
z
Lande 1976
MOVING OPTIMUM MODEL
θ
W
z
p(z)
z
Lynch & Lande 1995
STATIONARY OPTIMUM WITH WHITE NOISE MOTION
θ
W
z
p(z)
z
Lynch & Lande 1995
PEAK SHIFT MODEL
W
b
a
z
p(z)
z
Lande 1985
References
• Lande, R. 1976. Evolution 30: 314-334.
• Lande, R. 1985. PNAS USA 82: 7641-5.
• Lynch, M. & R. Lande 1995. Pp. 2234-250,
IN: Kareiva et al. (eds.), Biotic Interactions
and Global Change, Sinauer, Sunderland,
MA