Presented by Julian D. Olden at the XX Brazilian Meeting of Ichthyology (2013)

1. Beyond
taxonomy:
A
traits-­‐based
approach
to
fish
community
ecology
Julian
D.
Olden
School
of
Aqua,c
and
Fishery
Sciences
University
of
Washington
olden@uw.edu

2. Big
Fish
Eat
Li,le
Fish
by
Pieter
Brueghel
the
Elder
(1557)

3. Threats
to
Freshwater
Fishes
Habitat loss Pollution
Fragmentation Climate change
Invasive species
Disease

4. Why
Trait-­‐based
Ecology?
• Enhances
our
mechanis,c
understanding
of
ecological
paHern
and
process
• Provides
greater
opportunity
for
generaliza,on
• Links
biodiversity
and
ecosystem
func,on

5. Traits
in
Fish
Community
Ecology
• The
study
of
fish
traits
can
be
used
to
understand
complex
phenomena,
including
why
organisms
live
where
they
do,
how
many
species
can
coexist
in
a
given
place,
and
how
they
will
respond
to
environmental
change
0
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120
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2012
#
publicaFons
ISI
Web
of
Science
search
on
Jan
20,
2013
using
the
query
“fish
AND
trait*
AND
(community
OR
assemblage)”

6. Research
PrioriFes
“In
an
ideal
world,
an
understanding
of
how
fish
assemblages
change
in
response
to
natural
changes
along
different
,me
scales
would
be
necessary
…
This
is
no
longer
always
possible,
however,
since
most
aqua,c
environments
are
already
subject
to
some
form
of
human
interven,on
…
Therefore,
it
is
necessary
to
deal
with
mixed
signals,
and
part
of
the
challenge
lies
in
numerically
dis,nguishing
these
signals,
as
well
as
pucng
them
in
perspec,ve.”

7. Today’s
PresentaFon
1.
Do
species
traits
provide
predic,ve
insight
into
those
fish
species
at
greatest
risk
to
ex,nc,on?
2.
Does
a
traits-­‐based
approach
represent
a
unifying
framework
for
an,cipa,ng
how
fish
species
and
communi,es
will
response
to
environmental
change?
Biodiversity
and
Ecosystem
Func,oning
Ex,nc,on
Invasion

8. 1.
ExFncFon
Risk
of
Fishes
• Conserva,on
biology
is
faced
with
a
growing
urgency
to
iden,fy
and
protect
species
facing
the
greatest
risk
of
ex,nc,on
(Pimm
and
Jenkins
2005)
• This
is
a
challenging
task
because
direct
es,mates
of
ex,nc,on
risk
for
most
species
are
lacking
(O’Grady
et
al.
2004)
• Ecological
traits
can
help
iden,fy
species
that
are
vulnerable
to
ex,nc,on

9. Body
Size
and
Global
ExFncFon
Risk
• Body
size
is
a
fundamental
ecological
parameter
correlated
with
many
other
life-­‐
history
characteris,cs
• Ecological
theory
and
global-­‐scale
analyses
of
bird
and
mammal
faunas
suggest
that
small-­‐bodied
species
are
less
vulnerable
to
ex,nc,on
• We
compared
body-­‐size
distribu,ons
of
22,800
freshwater
and
marine
fishes
under
different
levels
of
global
ex,nc,on
risk

10. YES.
Dip
sta,s,c
=
0.12,
d.f.
=
14,
P
=
0.042
NO.
Dip
sta,s,c
=
0.07,
d.f.
=
16,
P
=
0.889
Olden,
J.D.,
Hogan,
Z.S.,
and
M.J.
Vander
Zanden.
2007.
Small
fish,
big
fish,
red
fish,
blue
fish:
size-­‐biased
ex,nc,on
risk
of
the
world’s
freshwater
and
marine
fishes.
Global
Ecology
and
Biogeography
16:694-­‐701.
Is
the
distribu,on
significantly
bi-­‐modal?

11. ImplicaFons
• Given
limited
resources
for
conduc,ng
detailed
species
assessments,
iden,fying
trait-­‐
based
indicators
of
ex,nc,on
risk
could
be
extremely
valuable
for
conserva,on
ranking
schemes
• Traits
may
provide
insight
into
the
ecosystem
implica,ons
of
species
losses
(and
invasions)
Castello
et
al.,
in
press.
The
vulnerability
of
Amazon
freshwater
ecosystems.
Conserva;on
Le,ers.

12. 2.
Life-­‐histories
and
the
habitat
templet
Trade-­‐offs
among
energeFc
investments
in
growth,
reproducFon,
and
survivorship
have
resulted
in
the
evoluFon
of
life
history
strategies
that
enable
an
organism
to
cope
with
ecological
challenges
Southwood
(1988)

13. Fish
Life-­‐history
Theory
• Life
history
theory
has
sparked
new
perspec,ves
in
understanding
the
paHerns
and
drivers
of
freshwater
biodiversity
Olden
&
Kennard
(2010)
• Life-­‐history
strategies
have
evolved
from
trade-­‐offs
among
traits
that
have
direct
consequences
for
fitness
in
different
environments
(Winemiller
and
Rose
1992)
Fecundity

14. Fish
Life-­‐history
Theory
Fecundity
OPPORTUNISTIC
•
small
•
rapidly
matura,on
•
low
fecundity
•
unpredictable
env.
PERIODIC
•
large
•
late
matura,on
•
high
fecundity
•
seasonal
env.
EQUILIBRIUM
•
medium
•
low
fecundity
•
↑parental
care
•
constant
env.

15. OpportunisFc
Periodic
Equilibrium
Life-­‐histories
of
North
American
fishes
Mims,
M.C.,
Olden,
J.D.,
ShaHuck,
Z.R.,
and
N.L.
Poff.
2010.
Life
history
trait
diversity
of
na,ve
freshwater
fishes
in
North
America.
Ecology
of
Freshwater
Fish
19:390-­‐400.

16. • It
is
hypothesized
that
a
species’
life
history
strategy
dictates,
in
large
part,
its
response
to
environmental
factors
describing
the
variability,
predictability,
and
seasonality
of
favorable
habitat
condi,ons
Modified
from
Bunn
and
Arthington
(2002,
Env.
Man.)

17. • Hydrological
variability
plays
a
dominant
role
in
shaping
physical
processes
in
riverine
ecosystems,
and
a
number
of
recent
studies
have
supported
the
associa,on
between
hydrology
and
fish
life
history
strategies

18. ObjecFve
Test
life
history
theory
by
quan,fying
rela,onships
between
variability,
predictability,
and
seasonality
of
natural
flow
regimes
and
the
life
history
composi,on
of
na,ve
fish
assemblages
throughout
the
con,nental
United
States.

19. Meryl
Mims

20. Approach
>15
years
con,nuous
gage
data
prior
to
fish
survey?
Gage-­‐survey
pair
within
10
river
km?
Any
tributaries
between
the
pair?
YES
YES
NO
Acceptable
pair
(n=109)
Flow
Gages
Fish
Surveys

23. Approach
• Assign
each
fish
species
to
a
life
history
strategy
and
calculate
rela,ve
strategy
richness
for
each
site
• Calculate
hydrologic
metrics
that
summarize
the
major
components
of
the
flow
regime
Predictability
Variability
Seasonality

24. PredicFons
from
Life
History
Theory
Flow
dimension
Hydrologic
metric
Predicted
relaFonship
with
proporFonal
LH
(slope
direcFon)
OpportunisFc
Periodic
Equilibrium
VARIABILITY
Annual
Coef.
Varia,on
+
-­‐
-­‐
High
Pulse
Count
+
-­‐
-­‐
PREDICTABILITY
Base
Flow
Index
-­‐
0
+
Flow
Predictability
-­‐
+
+
SEASONALITY
Constancy/Predictability
0
-­‐
+
High
Pulse
Dura,on
-­‐
+
0
Used
quan,le
regression
to
test
for
rela,onships
between
LHs
and
hydrologic
metrics

25. • The
majority
(two-­‐thirds)
of
rela,onships
were
sta,s,cally
significant
(P<0.05)
for
at
least
one
quan,le
• 82%
of
significant
rela,onships
supported
predic,ons
from
life
history
theory
Opp
Per
Equ
Mims,
M.C.,
and
J.D.
Olden.
2012.
Life
history
theory
predicts
streamflow
effects
on
fish
assemblage
response
to
hydrologic
regimes.
Ecology
93:35-­‐45.

26. • The
majority
(two-­‐thirds)
of
rela,onships
were
sta,s,cally
significant
(P<0.05)
for
at
least
one
quan,le
• 82%
of
significant
rela,onships
supported
predic,ons
from
life
history
theory
Opp
Per
Equ
Mims,
M.C.,
and
J.D.
Olden.
2012.
Life
history
theory
predicts
streamflow
effects
on
fish
assemblage
response
to
hydrologic
regimes.
Ecology
93:35-­‐45.
Flow
Variability

27. • The
majority
(two-­‐thirds)
of
rela,onships
were
sta,s,cally
significant
(P<0.05)
for
at
least
one
quan,le
• 82%
of
significant
rela,onships
supported
predic,ons
from
life
history
theory
Mims,
M.C.,
and
J.D.
Olden.
2012.
Life
history
theory
predicts
streamflow
effects
on
fish
assemblage
response
to
hydrologic
regimes.
Ecology
93:35-­‐45.
Flow
Seasonality

28. Flow
dimension
Hydrologic
metric
Predicted
relaFonship
with
proporFonal
LH
(slope
direcFon)
OpportunisFc
Periodic
Equilibrium
VARIABILITY
Annual
Coef.
Varia,on
+
-­‐
-­‐
High
Pulse
Count
+
-­‐
-­‐
PREDICTABILITY
Base
Flow
Index
-­‐
0
+
Flow
Predictability
-­‐
+
+
SEASONALITY
Constancy/Predictability
0
-­‐
+
High
Pulse
Dura,on
-­‐
+
0
=
Supported
by
theory
=
Inconclusive
=
Not
support
by
theory
Life
history
theory
predicts
fish
assemblage
response
to
hydrologic
regimes

29. ImplicaFons
• The
flow
regime
as
a
key
determinant
of
fish
life
history
composi,on
across
a
broad
biogeographical
scale
• A
traits-­‐based
approach
is
useful
because
it
facilitates
the
transfer
of
scien,fic
knowledge
between
regions
that
naturally
differ
due
to
zoogeography,
but
in
which
life
history
strategies
and
trait
adapta,ons
are
hypothesized
to
converge
across
diverse
taxonomies
• These
findings
have
implica,ons
for
predic,ng
the
consequences
of
flow
altera,on
and
for
informing
flow-­‐management
recommenda,ons

30. • Fish
life-­‐history
strategies
are
predic,ve
of
how
fish
assemblages
response
to
damming
and
altered
flow
regimes
Mims,
M.C.,
and
J.D.
Olden.
2013.
Fish
assemblages
respond
to
altered
flow
regimes
via
ecological
filtering
of
life
history
strategies.
Freshwater
Biology
58:50-­‐62.

31. Key
Challenges
Does
a
trait-­‐based
approach
provide
new
insight
into
paHerns
and
processes
of
fish
biogeography,
and
if
so,
can
this
informa,on
inform
conserva,on
strategies?
What
traits
predispose
fish
species
to
ex,nc,on
vs.
invasion?
Given
the
lack
of
trait
data
for
many
fish
species
in
par,cular
regions,
which
subset
of
traits
are
most
appropriate
for
defining
func,onal
diversity
and
offer
the
most
promise
for
predic,ng
responses
to
environmental
change?
What
are
the
ecosystem
consequences
of
changes
in
fish
func,onal
composi,on?

32. PredicFng
ExFncFon
Risk
“More
appropriate
biological
knowledge
is
s;ll
required
to
improve
species
assignment
to
the
IUCN
Red
List
categories
at
the
regional
level”
Transferring
Knowledge
“One
of
the
major
problems
facing
fish
conserva;on
in
South
America
is
the
lack
of
basin-­‐wide
approaches.
Usually,
both
knowledge
and
interest
are
limited
to
the
local
…”

33. Julian
D.
Olden
University
of
Washington
olden@uw.edu
Special
thanks
to
Meryl
Mims!