Viviparity imparts a macroevolutionary signature of ecological opportunity in the body size of female Liolaemus lizards
Nature Communications,
Journal Year:
2024,
Volume and Issue:
15(1)
Published: June 11, 2024
Abstract
Viviparity
evolved
~115
times
across
squamate
reptiles,
facilitating
the
colonization
of
cold
habitats,
where
oviparous
species
are
scarce
or
absent.
Whether
ecological
opportunity
furnished
by
such
reconfigures
phenotypic
diversity
and
accelerates
evolution
is
unclear.
We
investigated
association
between
viviparity
patterns
rates
body
size
in
female
Liolaemus
lizards,
most
species-rich
tetrapod
genus
from
temperate
regions.
Here,
we
discover
that
viviparous
evolve
~20%
larger
optimal
sizes
than
their
relatives,
but
exhibit
similar
evolution.
Through
a
causal
modeling
approach,
find
indirectly
influences
through
shifts
thermal
environment.
Accordingly,
habitats
favors
species,
reconfiguring
.
The
catalyzing
influence
on
arises
because
it
unlocks
access
to
otherwise
inaccessible
sources
opportunity,
an
outcome
potentially
repeated
tree
life.
Language: Английский
Nonidentifiability of state-dependent diversification models (SSEs) is ubiquitous but not problematic for phylogenetics
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2022,
Volume and Issue:
unknown
Published: July 5, 2022
A
recent
study
(Louca
and
Pennell,
2020)
spotlighted
the
issue
of
model
congruence,
or
asymptotic
unidentifiability,
in
time-dependent
birth-death
models
used
for
reconstructing
species
diversification
histories
on
phylogenetic
trees.
The
present
work
investigates
this
state-dependent
speciation
extinction
(SSE)
models,
commonly
to
trait-dependent
diversification.
We
found
that
unidentifiability
is
universal
due
hidden
states,
with
every
SSE
belonging
an
infinite
congruence
class.
Notably,
any
trait-independent
congruent
raising
concerns
hypothesis
testing.
To
address
this,
we
propose
analytical
solution
resolves
selection
within
a
Our
findings
show
type
only
one
possible,
our
place,
SSEs
becomes
absolutely
harmless
inference.
However,
across
classes
remains
challenging
extremely
high
false
positive
rates.
discovered
offers
clear
explanation
suggests
potential
ways
forward.
Language: Английский