Identifying priority conservation areas for the Andean Condor in Colombia

Abstract

The Andean Condor (Vultur gryphus) is a globally threatened species. Its highly mobile capability presents important challenges for conservation planning, especially in extremely geographically complex regions such as Colombia, where little is known about its ecology. Over the past three decades, financial and technical conservation efforts have primarily focussed on reintroduction and local management strategies. However, these initiatives did not properly prioritize the various conservation measures undertaken. We utilized roosting locations across Colombia to identify suitable roosting distribution with high risk because of the anthropogenic impact on a Systematic Planning Tool for decision-making based on robust spatial habitat modelling to define where and how should focus the Andean condor conservation actions in the country. Specifically, we aimed to develop a conservation planning tool to facilitate spatially explicit decision-making. Our results showed that Colombia has at least 19,571.33 km2 of suitable roosting habitat for this species, but over 30% of this area is currently considered to be under conservation risk due to severe anthropogenic impacts. Considering this, we suggested different actions for each proposed area according to potential threats generated by human communities.

Full text

ARTICLE IN PRESS
G Model
PECON-330;
No.
of
Pages
9
Perspectives
in
Ecology
and
Conservation
xxx
(xxxx)
xxx–xxx
Supported
by
the
National
Council
for
Scientific
and
Technological
Development
-
CNPq
www.perspectecolconserv.com
Research
Letters
Identifying
priority
conservation
areas
for
the
Andean
Condor
in
Colombia
María
Alejandra
Parrado-Vargasa,b,e,∗∗,
José
Fernando
González-Mayad,e,
Björn
Reua,
Antoni
Margalidaf,g,
Fausto
Sáenz-Jiménezc,
Félix
Hernán
Vargasb,∗
aEscuela
de
Biología,
Universidad
Industrial
de
Santander,
Carrera
27
Calle
9,
P.C.
2768002,
Bucaramanga,
Santander,
Colombia
bThe
Peregrine
Fund,
Isla
Santa
Cruz,
C.P.
200102,
Galápagos,
Ecuador
cEscuela
de
Biología,
Universidad
Pedagógica
y
Tecnológica
de
Colombia-UPTC,
Sede
Central
Tunja–Boyacá–Colombia;
Avenida
Central
del
Norte
39-115,
PC-150003
dDepartamento
de
Ciencias
Ambientales,
CBS,
Universidad,
Autónoma
Metropolitana
Unidad
Lerma,
Av.
de
las
Garzas
10,
Col.
El
Panteón,
C.P.
52005,
Lerma
de
Villada,
Estado,
de
México,
México
eProyecto
de
Conservación
de
Aguas
y
Tierras,
ProCAT
Colombia,
Cra
8
#
127c-36,
Of.
101,
C.P.
110121,
Bogotá,
Colombia
fPyrenean
Institute
of
Ecology
(CSIC).
Avda.
Nuestra
Se˜
nora
de
la
Victoria
12,
C.P.
22700,
Jaca,
Spain
gInstitute
for
Game
and
Wildlife
Research
IREC
(CSIC-UCLM-JCCM),
Ronda
de
Toledo,
12,
C.P.
13071,
Ciudad
Real,
Spain
h
i
g
h
l
i
g
h
t
s
•Priority
conservation
areas
(PCA)
were
determined
for
Andean
condors
in
Colombia.
•Less
than
30%
of
the
PCA
for
condors
are
in
protected
areas.
•Areas
with
Low,
Medium,
and
High
Human
Footprint
Index
require
dif-
ferent
strategies
for
prioritization
conservation
Areas.
•We
propose
an
area-based
roadmap
to
optimize
Andean
condor
conserva-
tion
in
the
northern
Andes
of
South
America.
g
r
a
p
h
i
c
a
l
a
b
s
t
r
a
c
t
a
r
t
i
c
l
e
i
n
f
o
Article
history:
Received
22
May
2023
Accepted
5
May
2024
Available
online
xxx
Keywords:
Vultur
gryphus
Decision
making
tools
Roosting
selections
Habitat
suitability
New
world
vultures
a
b
s
t
r
a
c
t
The
Andean
Condor
(Vultur
gryphus)
is
a
globally
threatened
species.
Its
highly
mobile
capability
presents
important
challenges
for
conservation
planning,
especially
in
extremely
geographically
complex
regions
such
as
Colombia,
where
little
is
known
about
its
ecology.
Over
the
past
three
decades,
financial
and
tech-
nical
conservation
efforts
have
primarily
focussed
on
reintroduction
and
local
management
strategies.
However,
these
initiatives
did
not
properly
prioritize
the
various
conservation
measures
undertaken.
We
utilized
roosting
locations
across
Colombia
to
identify
suitable
roosting
distribution
with
high
risk
because
of
the
anthropogenic
impact
on
a
Systematic
Planning
Tool
for
decision-making
based
on
robust
spatial
habitat
modelling
to
define
where
and
how
should
focus
the
Andean
condor
conservation
actions
in
the
country.
Specifically,
we
aimed
to
develop
a
conservation
planning
tool
to
facilitate
spatially
explicit
decision-making.
Our
results
showed
that
Colombia
has
at
least
19,571.33
km2
of
suitable
roosting
habi-
tat
for
this
species,
but
over
30%
of
this
area
is
currently
considered
to
be
under
conservation
risk
due
to
severe
anthropogenic
impacts.
Considering
this,
we
suggested
different
actions
for
each
proposed
area
according
to
potential
threats
generated
by
human
communities.
©
2024
Associac¸ ˜
ao
Brasileira
de
Ciˆ
encia
Ecol ´
ogica
e
Conservac¸ ˜
ao.
Published
by
Elsevier
B.V.
This
is
an
open
access
article
under
the
CC
BY-NC-ND
license
(http://creativecommons.org/licenses/by-nc-nd/4.0/
).
∗Corresponding
author.
E-mail
addresses:
maria2208194@correo.uis.edu.co
(M.A.
Parrado-Vargas),
jfgonzalezmaya@gmail.com
(J.F.
González-Maya),
breu@uis.edu.co
(B.
Reu),
a.margalida@csic.es
(A.
Margalida),
fsaenzj@gmail.com
(F.
Sáenz-Jiménez),
vargas.hernan@peregrinefund.org
(F.H.
Vargas).
∗∗ https://www.researchgate.net/profile/Maria-Parrado-Vargas
https://doi.org/10.1016/j.pecon.2024.05.002
2530-0644/©
2024
Associac¸ ˜
ao
Brasileira
de
Ciˆ
encia
Ecol ´
ogica
e
Conservac¸ ˜
ao.
Published
by
Elsevier
B.V.
This
is
an
open
access
article
under
the
CC
BY-NC-ND
license
(http://
creativecommons.org/licenses/by-nc-nd/4.0/).
Please
cite
this
article
as:
M.A.
Parrado-Vargas,
J.F.
González-Maya,
B.
Reu
et
al.
Identifying
priority
conservation
areas
for
the
Andean
Condor
in
Colombia,
Perspectives
in
Ecology
and
Conservation,
https://doi.org/10.1016/j.pecon.2024.05.002

ARTICLE IN PRESS
G Model
PECON-330;
No.
of
Pages
9
M.A.
Parrado-Vargas,
J.F.
González-Maya,
B.
Reu
et
al.
Perspectives
in
Ecology
and
Conservation
xxx
(xxxx)
xxx–xxx
Introduction
One
of
the
greatest
challenges
facing
conservation
planning
(Knight
et
al.,
2006)
is
deciding
how
and
where
to
invest
limited
financial
and
technical
resources
to
conserve
biodiversity
(Wilson
et
al.,
2007).
This
situation
becomes
even
more
complex
for
mobile
threatened
species
that
are
highly
mobile
with
large
home
ranges,
which
are
usually
susceptible
to
large-scale
threats
throughout
their
distribution
range
(Nandintsetseg
et
al.,
2019).
For
this
reason,
single
actions
at
specific
local
scales
are
often
insufficient
to
secure
species
persistence,
and
large-scale
approaches,
including
trans-
boundary
management
and
conservation
strategies,
are
required
(Lambertucci
et
al.,
2014;
Runge
et
al.,
2014).
The
Andean
Condor
(Vultur
gryphus)
is
one
of
the
largest
and
most
mobile
species
in
the
Neotropical
region,
with
its
distribu-
tion
spanning
most
of
the
Andes.
Classified
as
Vulnerable
(VU),
its
populations
are
in
decline
(BirdLife
International,
2020)
and
the
situation
is
particularly
critical
in
the
northern
part
of
its
range
(Naveda-Rodríguez
et
al.,
2016;
Padró
et
al.,
2023).
In
Colombia,
the
Andean
Condor
is
considered
Critically
Endangered
(CR)
(Renjifo
et
al.,
2016):
This
critical
situation
was
identified
in
Colombia
in
the
1980s,
a
decade
during
which
it
was
believed
to
be
extinct
in
several
localities
(Rodríguez
et
al.,
2006).
Consequently,
a
reintro-
duction
program
was
implemented
between
1989
and
2013
and
71
individuals
were
released
at
eight
repopulation
sites
(Sáenz-
Jiménez,
2020).
However,
to
date
only
one
successful
reproduction
of
the
released
condors
was
reported
in
Los
Nevados
Natural
Park
(Restrepo-Cardona
et
al.,
2018).
At
present,
little
is
known
about
the
ecological
requirements
and
survival
of
reintroduced
individ-
uals
and
the
threats
they
may
face,
hindering
the
development
of
effective
technical
and
financial
strategies
for
their
long-term
conservation
in
the
country.
Andean
Condors
can
travel
more
than
300
km/day
(Lambertucci
et
al.,
2014;
Padró
et
al.,
2023)
and
prefer
to
roost
on
cliffs
and
steep
mountain
slopes,
which
offer
refuge
from
threats
and
adverse
weather
conditions
(Lambertucci
and
Ruggiero,
2013).
Condors
regularly
frequent
the
same
roosting
sites
(Padró
et
al.,
2018),
with
conditions
that
offer
safety
and
facilitate
easy
take-off
and
land-
ing
(H.J.
Williams
et
al.,
2020).
The
roosting
sites
are
preserved
within
Priority
Conservation
Areas
(PCAs)
to
guarantee
safe
habi-
tats
that
facilitate
efficient
take-off
and
landing,
nesting,
and
the
overall
survival
of
Andean
Condors
(Plaza
and
Lambertucci,
2020).
Additionally,
these
sites
serve
as
vital
conservation
and
gather-
ing
spots
for
other
bird
species,
supporting
their
populations
and
the
ecosystem
services
provided
(Lambertucci
and
Ruggiero,
2016).
These
areas
also
create
stepping-stone
corridors
between
regions,
promoting
gene
flow
among
populations
(Padró
et
al.,
2023),
Thus,
the
protection
of
roosting
sites
should
help
to
reduce
discrete
loss
of
genetic
variability
(Padró
et
al.,
2018),
and
reduce
the
effects
of
inbreeding
(Padró
et
al.,
2020).
Here,
we
highlight
the
significance
of
modelling
suitable
roost-
ing
sites
as
an
effective
systematic
planning
tool
to
inform
condor
conservation
strategies
in
Colombia,
a
region
characterized
by
sub-
stantial
research
gaps
on
habitat
use
and
movement
ecology
of
the
Andean
Condor.
This
study
aims
to
identify
PCA’s
for
the
Andean
Condor
in
Colombia
based
on
the
available
information
on
con-
firmed
roosting
areas
used
by
the
species
and
the
potential
risks
defined
by
the
Human
Footprint
Index
(HFI,
Correa
Ayram
et
al.,
2020).
The
delineation
of
these
areas
will
serve
as
a
valuable
decision-making
tool,
providing
guidelines
for
better
prioritization
of
Andean
Condor
conservation
efforts
and
effective
mitigation
of
population
threats
at
the
landscape
scale.
Material
and
methods
Study
Area
The
study
was
carried
out
within
the
historical
distribution
of
the
Andean
Condor
in
the
Colombian
Andes
(Rodríguez
et
al.,
2006)
in
an
area
located
between
1800
and
5500
m
asl.
The
study
area
was
defined
according
to
the
most
up-to-date
data
on
the
presence
and
distribution
of
Andean
Condors
in
Colombia
(Sáenz-Jiménez,
2020),
and
comprises
an
area
of
83,808
km2.
We
gathered
roost
site
data
from
three
sources:
(i)
satellite
data
from
two
tagged
wild
condors,
a
non-breeding
adult
female
and
an
immature
male,
tracked
in
north-eastern
Colombia
between
2019
and
2021
using
Geotrack
65
G
Solar
PTT
trackers
(eight
GPS
fixes/day);
(ii)
data
collected
from
three
condors
tagged
between
2014–2019
in
Ecuador,
comprising
one
juvenile
male
and
two
subadult
females,
using
microwave
telemetry
satellite
trackers
(PTT-100
50
gram
solar
patagial
tags)
programmed
to
provide
one
fix
per
hour
from
05:00
to
19:00
local
Ecuador
time
(GMT-5);
and
iii)
direct
observations
at
communal
and
occasional
roosts,
and
one
nesting
site,
between
2014
and
2021
across
different
parts
of
the
Colombian
Andes
(Fig.
1).
Roosting
condor
locations
were
identified
using
the
satellite
tracking
data
collected
between
sunset
and
sunrise
(18:00
to
05:00
h),
when
condors
are
less
active
and
birds
with
movement
speeds
of
zero
knots
could
be
assumed
to
be
resting
(Perrig
et
al.,
2020).
Roost
sites
in
areas
without
satellite
tracking
data
were
con-
firmed
by
observation
between
18:00
and
05:00
h
(Lambertucci
and
Ruggiero,
2013).
GPS
errors
potentially
resulting
from
multiple
closely
spaced
roosting
locations
were
eliminated
by
aggregating
all
observations
within
a
100
m
radius
and
assuming
that
they
corresponded
to
the
same
roost
sites.
We
identified
the
roost-
ing
sites
using
Package
tidyr
in
R
(Wickham
and
Girlich,
2022)
and
assumed
that
all
the
identified
roosting
sites
had
the
same
importance.
Selection
of
predictive
variables
We
explored
climatic
and
geomorphological
variables
to
iden-
tify
those
that
could
explain
roosting
site
selection
(data
for
all
records
are
shown
at
doi:
10.17632/trgd5tnwxp.1).
The
climatic
variables
selected
were
expressed
at
a
spatial
resolution
of
50
m
and
included
wind
speed,
air
density
(air
mass
per
unit
volume)
(Badger
et
al.,
2015),
and
solar
radiation
on
inclined
surfaces
(Solargis,
World
Bank
Group,
2019)
all
of
which
are
known
to
influence
the
flight
and
soaring
capabilities
of
condors
(H.J.
Williams
et
al.,
2020),
or
to
pro-
vide
protection
against
extreme
weather
conditions
(Lambertucci
and
Ruggiero,
2013).
In
addition,
six
geomorphological
variables
were
included
at
a
spatial
resolution
of
90
m,
including
roughness
(topographic
com-
plexity),
convergence
(dissected
terrain
with
valleys
and
ridges),
elevation,
degree
of
northerly
orientation,
degree
of
easterly
orienta-
tion
(measures
of
orientation
combined
with
slope
to
the
north
or
to
the
east),
and
slope
(rate
of
change
of
elevation)
(Amatulli
et
al.,
2020).
These
variables
are
associated
with
cliff
structures
(Amatulli
et
al.,
2020),
which
provide
condors
with
refuge
from
predators
and
adverse
weather
conditions
(Lambertucci
and
Ruggiero,
2013)
(SI
1).
All
variables
with
a
spatial
resolution
less
than
90
m
were
resam-
pled
to
90
m
using
the
resample
function
with
bilinear
interpolation
method
in
the
Package
raster
of
R
(Hijmans
et
al.,
2023).
Data
were
collected
in
areas
within
the
extent
of
the
potential
distribution
of
condors
in
Colombia.
2

ARTICLE IN PRESS
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9
M.A.
Parrado-Vargas,
J.F.
González-Maya,
B.
Reu
et
al.
Perspectives
in
Ecology
and
Conservation
xxx
(xxxx)
xxx–xxx
Fig.
1.
Study
Area.
Roosting
sites
identified,
dots
in
colours
represent
the
origin
of
the
data;
polygons
correspond
to
Minimal
convex
polygons
for
tagged
wild
condors.
The
Gray
area
represents
potential
Andean
condor
distribution
(Sáenz-Jiménez,
2020).
Distribution
patterns
of
potential
roosting
sites
We
analysed
roosting
sites
used
by
condors
(denoted
1)
and
500
random
points
(denoted
0)
located
between
2000
and
5500
m
asl
within
the
potential
condor
distribution
in
Colombia
and
ran-
domized
the
data
using
the
resample
function
with
Package
caret
in
R
(Wickham,
2017).
We
tested
for
correlations
among
all
vari-
ables
and
excluded
those
that
were
highly
correlated
(>0.7)
(SI
2)
3

ARTICLE IN PRESS
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PECON-330;
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Pages
9
M.A.
Parrado-Vargas,
J.F.
González-Maya,
B.
Reu
et
al.
Perspectives
in
Ecology
and
Conservation
xxx
(xxxx)
xxx–xxx
Table
1
Summary
of
the
Generalized
Linear
Model
(GLM).
The
table
shows
the
first
ten
models
obtained,
along
with
their
Akaike
delta
value
(AICc),
Akaike
value
(AIC),
degrees
of
freedom
(df),
weight,
log-likelihood
(LogLike),
and
prediction
error
for
K-fold
Cross-validation
(K-fold
err).
The
combined
value
of
the
variables
corresponding
to
each
model
are
shown
in
the
variables
row.
*Indicates
the
best
competitive
models.
Models
AICc
df
AICw
AIC
K-fold
Err
LogLike
Intercept
Air
Density
Wind
Speed
Slope
Convergence
Radiation
Northeness
Mod81*
0
6
0.5
740.87
0.12
−364.43
−0.25
−0.78
0.42
1.9
−0.01
0.55
–
Mod63
1.56
5
0.2
742.45
0.12
−366.22
−0.22
−0.80
0.44
1.9
–
0.56
–
Mod90
2
7
0.2
742.83
0.12
−364.43
−0.22
−0.79
0.42
1.9
−0.01
0.55
−0.02
Mod.all
3.07
8
0.1
743.87
0.12
−363.93
–
–
–
–
–
–
–
Mod64
16.71
5
<0.01
757.6
0.12
−373.8
–
–
–
–
–
–
–
Mod83
18.56
6
<0.01
759.42
0.13
−373.71
–
–
–
–
–
–
–
Mod82
18.64
6
<0.01
759.5
0.12
−373.75
–
–
–
–
–
–
–
Mod39
20.49
4
<0.01
761.4
0.13
−376.7
–
–
–
–
–
–
–
Mod66
22.43
5
<0.01
763.33
0.13
−376.66
–
–
–
–
–
–
–
Mod65
22.46
5
<0.01
763.36
0.13
−376.67
–
–
–
–
–
–
–
Avg
Model
−0.22
−0.73
0.39
1.75
−0.01
0.51
−0.02
(Hosmer
and
Lemeshow,
2000).
All
variables
were
standardized
to
mean
zero
and
unit
variance.
We
analysed
the
potential
influence
of
variables
using
the
Generalized
Linear
Model
(GLM)
approach
based
on
the
Binomial
Logistic
family
and
logit
link
to
relate
the
species
presence-absence,
using
the
‘glm’
function
using
Package
stats
in
R
(Venables
and
Ripley,
2002)
and
generated
93
models,
including
all
the
potential
variable
combinations
without
interac-
tions.
We
used
the
Akaike
information
criterion
(AIC)
corrected
for
small
samples,
Delta
AIC,
and
AIC
weight
(AICw)
values
using
the
bbml
R
package
(Bolker
et
al.,
2009)
to
choose
the
most
parsi-
monious
models
based
on
delta
AIC
values
(AICc
<
2)
as
the
best-performing
models
for
downstream
analyses
(Table
1).
Where
a
predictive
model
was
identified
as
competitive,
we
averaged
the
selected
models
using
AICw
and
estimated
the
weighted
regression
coefficient
values
of
each
variable
(Table
1)
(Imam
and
Kushwaha,
2013).
To
validate
the
most
competitive
models,
we
used
K-fold
cross-validation
with
a
training
set
and
data
test
set
(80%–20%),
repeated
in
10
cross-validation
runs
(Yates
et
al.,
2023),
and
cal-
culated
the
prediction
error
for
GLMs
using
R
Package
boot
(Canty
and
Ripley,
2022).
After
identifying
and
averaging
a
group
of
mod-
els,
we
extrapolated
the
model
values,
considering
the
coefficient
of
predictor
variables,
the
AICw,
and
the
Intercept
(Table
1),
using
the
raster
calculator
in
QGIS
3.16.16
to
generate
a
predictive
map
of
suitable
roosting
areas
for
Andean
Condors
within
their
potential
distribution
in
Colombia.
Identifying
priority
roosting
sites
for
conservation
To
define
priority
conservation
roosting
sites,
we
first
selected
areas
with
values
equal
or
high
to
43%
of
suitability
as
areas
of
medium
and
high
suitability
for
roosting
(third
quartile
of
the
data)
(Allen
et
al.,
2023;
De
Kerckhove,
2008).
Then,
we
overlapped
these
areas
with
the
HFI
identified
by
Correa
Ayram
et
al.
(2020)
using
QGis
3.16.16,
with
a
resolution
of
300
m,
as
a
proxy
of
landscape
anthropization,
such
as
human
population
density,
land
use
inten-
sity,
and
other
anthropogenic
ecosystem
impacts
(Correa
Ayram
et
al.,
2020).
Given
the
lack
of
spatially
explicit
information
regarding
direct
threats
to
condors
in
Colombia,
the
HFI
can
be
estimated
either
directly
or
indirectly
from
known
anthropogenic
impacts
(Plaza
and
Lambertucci,
2020).
While
the
HFI
is
a
continuous
index
that
responds
to
underlying
spatial
processes,
Correa
Ayram
et
al.
(2020)
defined
areas
with
high
anthropogenic
impacts
as
those
with
an
index
>40%.
We
adopted
a
discrete
division
of
the
HFI
into
three
categories:
low
(<40%),
medium
(40%–60%)
and
high
(>60%).
Considering
the
decision
tree
proposed
(Fig.
2),
We
suggested
three
types
of
PCA:
(i)
Type
I
Maintenance
Priority
Areas
(MPAs),
defined
as
suitable
areas
with
only
natural
threats
or
minimal
threats
according
to
their
HFI
(Correa
Ayram
et
al.,
2020);
(ii)
Type
II
Socio-ecological
Actions
and
Restoration
Priority
Areas
(SERPAs),
defined
as
areas
with
medium
anthropogenic
pressure
and
suit-
able
roosting
sites;
and
(iii)
Type
III
Socio-ecological
Actions
and
Priority
Diagnostic
Areas
(SEDPAs)
(Fig.2),
defined
as
areas
with
high
anthropogenic
pressure
and
suitable
roosting
sites,
probably
very
close
to
urban
centres
or
major
cities.
This
final
mapping
was
done
using
QGis
3.16.16
(Fig.
3).
Using
the
defined
PCAs,
we
proposed
a
roadmap
for
the
best
conservation
actions
in
each
PCA
type
(SI
4),
considering
the
particular
threats
affecting
condors
in
Colom-
bia
(Restrepo-Cardona
et
al.,
2022)
and
South
America
(Plaza
and
Lambertucci,
2020),
and
more
generally
for
other
vulture
species
elsewhere
in
the
world
(Botha
et
al.,
2017).
Results
The
satellite
data
recorded
4640
GPS
locations,
leading
to
the
identification
of
461
roost
sites
in
Colombia.
Ten
of
these
sites
were
verified
through
direct
observations
and
the
detailed
data
for
all
records
are
available
at
doi:
10.17632/trgd5tnwxp.1.
Our
best
model
indicated
that
roost
sites
were
predominantly
selected
on
cliffs
with
low
air
density,
high
wind
speed,
high
radiation,
and
high
slope,
in
areas
such
as
ridges
or
cliff
ledges,
and
south-facing
(Table
1
and
SI
3).
The
probability
distribution
of
roosting
site
selec-
tion
in
the
three
categories
was:
Low,
<40%;
Medium,
40%–60%;
High,
61%–80%;
and
Very
High,
>80%.
The
resulting
map
of
poten-
tial
roosts
within
the
potential
distribution
of
the
Andean
Condor
in
Colombia
is
shown
in
SI
5.
The
third
quartile
data
(>43%)
repre-
sents
suitable
roosting
areas
for
the
Andean
Condor
and,
therefore,
we
only
considered
areas
above
this
threshold
as
PCAs.
Priority
conservation
areas
for
the
Andean
Condor
in
Colombia
The
PCAs
for
Andean
Condor
conservation
in
Colombia
covered
an
area
of
19,571.34
km2,
which
represents
23.35%
of
the
study
area.
Of
this
area,
5628.25
km2(29%)
are
currently
included
in
National
Natural
Parks,
and
of
this:
13,715.58
km2(70%)
corre-
spond
to
Type
I
MPAs;
4757.59
km2(24.3%)
are
Type
II
SERPAs;
and
1098.16
km2(5.6%)
are
Type
III
SEDPAs
(Figs.
2
and
3).
Most
of
the
Type
I
PCAs
were
in
northern
Andean
region
and
the
National
Natural
Park
Sierra
Nevada
de
Santa
Marta
(NNP-SNSM).
In
contrast,
Type
II
and
III
areas
were
primarily
located
outside
the
NNP-SNSM
and
the
north-eastern
Andean
region
of
Colom-
bia
(Fig.
3).
However,
the
paramo
corridor
in
the
eastern
Andes
Mountain
range,
spanning
the
departments
of
Cundinamarca,
Boy-
acá,
Santander,
and
Norte
de
Santander,
serves
as
a
critical
region
with
the
highest
concentration
of
all
PCA
types.
Our
spatial
model
highlighted
the
fact
that
the
central
and
southern
regions
of
the
Colombian
Andes
offer
fewer
suitable
resting
and
refuge
habitats
and
are
characterized
by
a
high
HFI.
Consequently,
these
areas
have
fewer
Type
I
PCAs
and
a
higher
prevalence
of
Type
II
and
III
PCAs
4

ARTICLE IN PRESS
G Model
PECON-330;
No.
of
Pages
9
M.A.
Parrado-Vargas,
J.F.
González-Maya,
B.
Reu
et
al.
Perspectives
in
Ecology
and
Conservation
xxx
(xxxx)
xxx–xxx
Fig.
2.
Proposed
Decision
Tree
for
Identifying
Actions
in
Priority
Conservation
Areas
(PCAs)
for
Andean
Condor
Conservation.
The
figure
shows
a
decision
tree
outlining
strategies
for
Andean
Condor
conservation
within
various
PCA
types.
The
primary
focus
is
on
addressing
the
intersection
of
suitable
roosting
habitats
and
their
Human
Footprint
Indexes
(HFIs),
which
pose
conservation
risks
to
the
species.
Green
areas
signify
proposed
actions
designed
for
Type
I
PCAs,
Yellow
areas
indicate
strategies
tailored
for
Type
II
PCAs,
and
Red
areas
represent
approaches
for
Type
III
PCAs.
The
priority
decisions
highlighted
in
this
figure
serve
as
guidelines
for
potential
actions
to
be
undertaken
for
the
conservation
of
Andean
Condors
across
various
PCAs
in
Colombia.
due
to
elevated
levels
of
human
impact
(Fig.
3).
Our
prioritization
exercise
enabled
us
to
propose
a
roadmap
with
recommendations
for
conservation
actions
within
each
PCA
type,
addressing
potential
threats
across
the
territory
(SI
4).
Discussion
Our
study
provides
baseline
ecological
and
spatial
information
and
a
systematic
planning
tool
for
designing
and
implementing
conservation
strategies
for
the
Andean
Condor
in
Colombia.
These
are
key
for
decision-making
and
action
to
reduce
the
extinction
risk
for
this
species
and
represent
one
of
the
first
systematic
approaches
to
the
selection
of
critical
areas
for
this
Critically
Endangered
species
in
Colombia.
We
found
that
south-facing
cliffs
on
high
slopes
located
on
ridges
and
cliff
faces
with
high
solar
radiation,
low
air
densities,
and
high
wind
speeds
are
more
likely
to
be
selected
for
condor
roosting
sites
(Table
1).
Condors
seem
to
choose
these
condi-
tions
to
seek
refuge
from
threats
and
adverse
weather
conditions
(Lambertucci
and
Ruggiero,
2013),
in
accordance
with
previous
findings
in
Colombia
(Sáenz-Jiménez,
2020).
Other
birds
of
prey,
including
vultures
such
as
the
Griffon
Vulture
Gyps
fulvus
(Aresu
et
al.,
2022)
and
the
Bearded
Vulture
Gypaetus
barbatus
(Margalida
et
al.,
2008),
and
other
raptors
such
as
Bonelli’s
Eagle
(Hieraae-
tus
fasciatus)
(López-López
et
al.,
2006),
also
select
resting
sites
based
on
these
criteria.
Similarly,
Peregrine
Falcons
Falco
pere-
grinus
(Wightman
and
Fuller,
2005)
exhibit
a
preference
for
high
cliffs
or
steep
slopes,
which
provide
favourable
conditions
for
ther-
moregulation,
energy
conservation
during
flight,
and
refuge
from
terrestrial
predators
(Aresu
et
al.,
2022).
Systematic
conservation
planning
tools
require
ecological
and
biological
knowledge
at
various
scales
to
design
informed,
species-specific
strategies,
resulting
in
more
cost-efficient
species
conservation
over
time
(Nandintsetseg
et
al.,
2019;
Nori
et
al.,
2020).
In
Colombia,
technical
and
financial
efforts
have
been
invested
in
Andean
Condor
conservation
for
over
30
years,
includ-
ing
public
policies,
localized
conservation
programs,
(Rodríguez
et
al.,
2006),
and
reintroductions
of
captive-bred
individuals
(Sáenz-Jiménez,
2020).
However,
the
repopulation
nuclei
defined
for
the
species
between
1989
and
2013
(Sáenz-Jiménez,
2020)
do
not
coincide
with
the
most
suitable
areas
and
many
threats,
such
as
poisoning,
shooting,
and
power
lines,
that
have
caused
population
declines
and
impacted
wild
and
reintroduced
individ-
uals
(Restrepo-Cardona
et
al.,
2022).
These
factors
and
the
limited
information
regarding
threats
and
their
distribution,
have
resulted
in
ineffective
conservation
strategies
(Carwardine
et
al.,
2008;
Buechley
et
al.,
2019;
Santangeli
et
al.,
2022).
Understanding
the
conservation
and
magnitude
of
the
threats
faced
by
condors
at
different
scales
in
the
PCAs,
and
the
magnitude
of
the
pressures
they
face
(Wallace
et
al.,
2021,
2022),
will
enable
to
focus
conservation
action
at
the
landscape
scale
in
both
the
medium
and
long
term
(Guerrero
et
al.,
2013),
and
will
assist
in
generating
Systematic
Conservation
Planning
Tool
(Gordon
et
al.,
2011).
Identifying
Priority
Conservation
Areas
for
the
Andean
Condor
in
Colombia
Our
results
indicate
that
the
19,570
km2which
could
be
con-
sidered
for
PCA
status
(PCAs),
represents
only
23%
of
the
potential
distribution
of
this
species
in
Colombia
(Sáenz-Jiménez,
2020).
This
limitation
may
stem
from
our
focusing
solely
on
roosting
areas,
neglecting
suitable
feeding
and
flight
areas
(Perrig
et
al.,
2020).
Of
the
potential
PCAs,
only
29%
are
situated
within
the
national
pro-
tected
areas
system
(Fig.
3),
constituting
only
a
small
fraction
of
the
overall
PCAs
for
the
species
in
Colombia.
This
is
consistent
with
previous
studies
and
emphasises
the
necessity
for
concerted
con-
servation
strategies
on
private
lands
owned
by
ranchers,
farmers,
and
local
communities
(Sáenz-Jiménez,
2020).
A
similarly
low
rep-
resentation
of
PCAs
in
protected
areas
has
been
reported
in
Ecuador
(Naveda-Rodríguez
et
al.,
2016)
and
the
southern
distribution
of
condors
in
Argentina
(Perrig
et
al.,
2020;
Plaza
and
Lambertucci,
2020).
This
situation
represents
a
significant
challenge
for
condor
conservation,
especially
considering
the
importance
of
well-chosen
protected
areas
critical
for
biodiversity
conservation
(Tittensor
et
al.,
2014).
Previous
studies
have
found
that
anthropogenic
pressures
clearly
influence
the
presence
of
condors
(Lambertucci
et
al.,
2009;
Lambertucci
and
Ruggiero,
2013;
Perrig
et
al.,
2020).
The
HFI
in
Colombia
has
increased
from
1979
to
2015
and
caused
consider-
able
loss
of
natural
areas,
resulting
in
many
ecosystems
becoming
5

ARTICLE IN PRESS
G Model
PECON-330;
No.
of
Pages
9
M.A.
Parrado-Vargas,
J.F.
González-Maya,
B.
Reu
et
al.
Perspectives
in
Ecology
and
Conservation
xxx
(xxxx)
xxx–xxx
Fig.
3.
Priority
Conservation
Areas
(PCAs)
for
Andean
Condor
Conservation
in
Colombia.
Colours
represent
priority
areas
at
the
landscape
scale.
Green:
low-risk
areas
with
a
high
probability
of
roost
selection
>43%
(Type
I
PCAs);
Yellow:
areas
with
medium-risks
for
conservation
and
a
high-probability
of
roost
selection
(>43%)
and
areas
between
40–60%
of
anthropogenic
pressure
overlap
(Type
II
PCAs);
Red:
high-risk
areas
for
Andean
Condor
conservation
where
there
is
a
high
probability
of
roost
selection
(>43%)
and
high
anthropogenic
pressure
(>60%)
(Type
III
PCAs).
6

ARTICLE IN PRESS
G Model
PECON-330;
No.
of
Pages
9
M.A.
Parrado-Vargas,
J.F.
González-Maya,
B.
Reu
et
al.
Perspectives
in
Ecology
and
Conservation
xxx
(xxxx)
xxx–xxx
vulnerable
(Correa
Ayram
et
al.,
2020).
These
conditions
are
more
pronounced
in
the
geographically
and
climatically
diverse
Colom-
bian
Caribbean
and
Andean
regions
because
of
human
population
growth
and
urban
expansion
and
the
resulting
increase
in
land
devoted
to
providing
food
security
for
human
communities
(Etter
and
Wyngaarden,
2016).
This
increasing
human
footprint
may
have
caused
the
Andean
Condor
decline
in
the
Colombian
Andes
(Rodríguez
et
al.,
2006).
Because
of
the
local
population
extinctions
of
condors
in
Colombia,
a
reintroduction
program
was
developed,
with
71
individuals
bring
released
between
1989
and
2013
(Sáenz-
Jiménez,
2020).
However,
only
55%
of
the
condors
released
survived
to
2010
(Sáenz-Jiménez,
2020)
and
many
died
from
anthropogenic
causes
(Restrepo-Cardona
et
al.,
2022).
This
high
mortality
rate
could
be
due
to
poor
planning
and
a
lack
of
proper
identifica-
tion
of
suitable
areas
for
condor
reintroduction.
Better
spatially
explicit
models
guiding
reintroductions
could
reduce
the
risks
due
to
human
persecution
and
ensure
that
birds
are
released
into
more
suitable
habitats
and
have
better
survival
chances
(Coz
and
Young,
2020).
Our
strategy
for
identifying
PCAs
for
Andean
Condors
in
Colom-
bia
centres
on
pinpointing
suitable
roosting
sites
in
areas
where
the
species
is
more
vulnerable.
Roosting
sites
in
PCAs
in
Colombia
serve
as
vital
refuges
(Lambertucci
and
Ruggiero,
2013),
safeguarding
against
low
genetic
variability
(Padró
et
al.,
2020)
and
facilitat-
ing
connectivity
and
gene
flow
between
robust
populations
within
Colombia
and
across
the
continent
(Padró
et
al.,
2023).
Our
findings
show
that
Type
II
and
III
PCAs
in
the
central
and
southern
Colombian
Andes
lie
outside
the
national
protected
areas
scheme
and
have
medium
and
high
HFIs
(Fig.
3),
which
could
explain
the
species’
decline
in
these
localities
(Renjifo
et
al.,
2016).
Conserving
roosts
in
southern
Colombia
could
facilitate
gene
flow
between
populations
north
and
south
of
the
equator,
potentially
reducing
the
genetic
impoverishment
observed
in
the
country’s
condors
(Padró
et
al.,
2023,
2020).
The
Type
I
PCAs
in
the
north-eastern
Andes
are
located
in
the
NNP-SNSM,
which
is
home
to
the
largest
wild
Andean
Condor
population
in
Colombia
(Rodríguez
et
al.,
2006)
and
is
under
the
protection
of
the
Kogui,
Wiwa,
Arhuaco,
and
Kankuamo
indigenous
people.
Multicultural
and
community
actions
to
reduce
the
threats
inside
these
terri-
tories
should
be
considered
(Prieto,
2014).
Furthermore,
satellite
tracking
data
has
shown
that
condors
move
between
the
NNP-
SNSM
and
the
NNP
El
Cocuy,
using
a
dispersal
corridor
of
paramo
complexes
throughout
Boyacá,
Santander,
Norte
de
Santander,
and
Cesar,
where
over
70%
of
the
human
persecution
events
for
Andean
Condor
have
been
reported
(Restrepo-Cardona
et
al.,
2022).
To
avoid
misguided
conservation
actions,
the
definition
of
PCAs
should
vary
based
on
the
measures
to
be
implemented
in
them
(Carwardine
et
al.,
2008).
For
this
reason,
we
developed
a
roadmap
with
strategies
for
maintaining
or
improving
the
conditions
in
the
various
PCA
types
(SI
4).
Suitable
roosting
areas
with
low
HFIs
were
termed
Type
I
MPAs,
where
action
should
prioritize
to
maintain
viable
natural
low-risk
conditions.
Type
II
SERPAs,
where
socio-
ecological
and
community
programs
are
essential,
especially
on
private
land,
and
Type
III
SEDPAs
(Fig.
2),
should
focus
efforts
on
assessing
population
and
habitat
status
to
determine
the
viability
of
direct
technical
and
financial
condor
conservation
(refer
to
Fig.
3,
SI
4).
While
our
study
has
provided
valuable
insights
into
the
con-
servation
of
the
Andean
Condor
in
Colombia,
it
is
important
to
recognize
certain
limitations
inherent
in
our
approach.
One
notable
limitation
is
our
exclusive
focus
on
roosting
sites,
which
may
not
encompass
the
entirety
of
suitable
condor
habitats
(Frans
et
al.,
2018).
Our
analysis
did
not
include
supplementary
feeding
sites,
or
take
account
of
the
fact
that,
in
common
with
most
obligate
avian
scavengers
(Moreno-Opo
et
al.,
2015;
Delgado-González
et
al.,
2022),
Andean
Condors
can
cover
large
distances
in
their
forag-
ing
trips,
selecting
high
quality
food
patches
and
predictable
food
resources
such
as
feeding
sites
(Perrig
et
al.,
2020).
In
this
context,
it
is
essential
to
reiterate
that
while
very
little
is
known
regard-
ing
the
movement
ecology
of
the
Andean
Condor
in
Colombia,
this
study
was
based
on
the
most
complete
dataset
available.
The
data
in
this
set
clustered
within
isolated
patches
in
the
northern
part
of
Colombia,
potentially
introducing
bias
into
our
model.
This
cluster-
ing
phenomenon
has
also
been
observed
in
studies
of
species
with
low
population
densities
confined
to
specific
habitat
patches,
and
any
bias
may
intensify
in
habitats
which
decline
in
quality
due
to
human
intervention
(Greene
and
Stamps,
2001).
Future
research
endeavours
should
investigate
additional
facets
of
the
species’
habitat
and
behaviour,
including
foraging
and
nest-
ing
sites,
to
obtain
a
more
comprehensive
understanding
of
its
conservation
requirements
(Frans
et
al.,
2018;
Perrig
et
al.,
2020).
Consequently,
we
urge
international
collaboration
to
consolidate
data
gathered
throughout
South
America
pertaining
to
all
areas
suitable
for
Andean
Condors.
Such
a
collaborative
effort
is
essential
to
predict
Andean
Condor
PCAs
across
the
whole
of
South
America
and
to
develop
a
continent-wide
spatial
decision-making
roadmap
for
the
implementation
of
conservation
actions
throughout
the
geo-
graphical
distribution
of
the
species
(Jahn
et
al.,
2017;
H.J.
Williams
et
al.,
2020).
While
our
model
effectively
identified
a
combination
of
geo-
morphological
and
climatic
variables
related
to
roost
selection,
the
exploration
of
ecological
and
biological
factors
remains
largely
uncharted.
For
instance,
information
on
food
availability,
micro-
climatic
variables,
and
other
biological
factors
could
significantly
enrich
the
model’s
predictive
power,
because
these
variables
influ-
ence
population
distribution
and
dynamics
(Perrig
et
al.,
2020).
Despite
the
large
information
gaps,
we
identified
condor
PCAs
in
Colombia
for
the
first
time,
and
proposed
conservation
actions
appropriate
to
the
conditions
in
each
PCA
type,
which
will
serve
as
both
regional
and
national
decision-making
tools.
Conflict
of
interest
The
authors
declare
no
conflict
of
interests.
Funding
sources
This
work
corresponds
to
the
results
of
the
first
author’s
master’s
research,
and
was
supported
by
The
Peregrine
Fund,
[Grant
num-
ber
TPF-COL-1-
FY21-FY22);
Alejandro
Ángel
Escobar
Fund
[Grant
Colombia
Biodiversa
number
2020-I)
and
Neotropical
Ornitholog-
ical
Society
[Grant
Francoise
Vieullimer
number,
FFV
2020).
Acknowledgments
We
acknowledge
The
Peregrine
Fund
and
GeoTrak
Inc
(Keith
LeSage)
for
the
donation
of
satellite
trackers
and
technical
advice
in
obtaining
the
data
on
the
movement
ecology
for
the
south
and
north
of
the
Colombian
Andes.
We
also
thank
Juan
Sebastián
Restrepo
for
providing
the
Condor
roosting
sites
monitored
in
the
Central
Andes
region
and
Francisco
Ciri
for
taking
this
research
into
account
in
the
initial
design
of
the
update
of
the
Andean
Condor
Conservation
Program
in
Colombia
2021-2035.
Appendix
A.
Supplementary
data
Supplementary
material
related
to
this
article
can
be
found,
in
the
online
version,
at
doi:https://doi.org/10.1016
/j.pecon.2024.05.002.
7

ARTICLE IN PRESS
G Model
PECON-330;
No.
of
Pages
9
M.A.
Parrado-Vargas,
J.F.
González-Maya,
B.
Reu
et
al.
Perspectives
in
Ecology
and
Conservation
xxx
(xxxx)
xxx–xxx
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