Ecology and Evolution,
Год журнала:
2020,
Номер
11(2), С. 900 - 911
Опубликована: Дек. 17, 2020
Abstract
Landscape
change
is
a
key
driver
of
biodiversity
declines
due
to
habitat
loss
and
fragmentation,
but
spatially
shifting
resources
can
also
facilitate
range
expansion
invasion.
Invasive
populations
are
reproductively
successful,
landscape
may
buoy
this
success.
We
show
how
modeling
the
spatial
structure
reproductive
success
elucidate
mechanisms
shifts
sustained
invasions
for
mammalian
species
with
attendant
young.
use
an
example
white‐tailed
deer
(deer;
Odocoileus
virginianus
)
in
Nearctic
boreal
forest,
North
American
phenomenon
implicated
severe
threatened
woodland
caribou
(
Rangifer
tarandus
).
hypothesized
that
linked
forage
subsidies
provided
by
extensive
via
resource
extraction.
measured
occurrence
using
data
from
62
camera
traps
northern
Alberta,
Canada,
over
three
years.
weighed
support
multiple
competing
hypotheses
about
multistate
occupancy
models
generalized
linear
AIC‐based
model
selection
framework.
Spatial
patterns
were
best
explained
features
associated
petroleum
exploration
extraction,
which
offer
early‐seral
vegetation
subsidies.
Effect
sizes
anthropogenic
eclipsed
natural
heterogeneity
two
orders
magnitude.
conclude
high
springtime
success,
mitigating
or
exceeding
winter
losses,
maintaining
populations.
Synthesis
Applications
.
Modeling
structuring
become
goal
remote
camera‐based
global
networks,
yielding
ecological
insights
into
invasion
inform
effective
decision‐making
conservation.
Conservation Biology,
Год журнала:
2020,
Номер
35(1), С. 88 - 100
Опубликована: Апрель 16, 2020
The
rapid
improvement
of
camera
traps
in
recent
decades
has
revolutionized
biodiversity
monitoring.
Despite
clear
applications
conservation
science,
have
seldom
been
used
to
model
the
abundance
unmarked
animal
populations.
We
sought
summarize
challenges
facing
estimation
animals,
compile
an
overview
existing
analytical
frameworks,
and
provide
guidance
for
practitioners
seeking
a
suitable
method.
When
records
multiple
detections
animal,
one
cannot
determine
whether
images
represent
mobile
individuals
or
single
individual
repeatedly
entering
viewshed.
Furthermore,
movement
obfuscates
definition
sampling
area
and,
as
result,
which
estimate
corresponds.
Recognizing
these
challenges,
we
identified
6
approaches
reviewed
927
camera-trap
studies
published
from
2014
2019
assess
use
prevalence
each
Only
about
5%
any
abundance-estimation
methods
identified.
Most
estimated
local
covariate
relationships
rather
than
predicting
density
over
broader
areas.
Next,
approach,
compiled
data
requirements,
assumptions,
advantages,
disadvantages
help
navigate
landscape
methods.
appropriate
method,
should
evaluate
life
history
focal
taxa,
carefully
define
frame,
consider
what
types
collection
are
possible.
challenge
estimating
populations
persists;
although
exist,
no
method
is
optimal
under
all
circumstances.
As
frameworks
continue
evolve
animals
becomes
increasingly
common,
will
become
even
more
important
informing
decision-making.Estimación
de
la
Abundancia
Animales
No
Marcados
con
Base
en
Datos
Cámaras
Trampa
Resumen
La
rápida
mejoría
las
cámaras
trampa
décadas
recientes
ha
revolucionado
el
monitoreo
biodiversidad.
A
pesar
su
clara
aplicación
ciencias
conservación,
han
sido
utilizadas
pocas
veces
para
modelar
abundancia
poblaciones
animales
marcados.
Buscamos
resumir
los
retos
que
enfrenta
estimación
marcados,
compilar
una
perspectiva
general
marcos
analíticos
trabajo
existentes
y
proporcionar
guía
aquellos
practicantes
buscan
un
método
adecuado.
Cuando
cámara
registra
múltiples
detecciones
se
puede
determinar
si
imágenes
representan
diferentes
individuos
movimiento
o
solo
individuo
entra
repetidamente
zona
visión
cámara.
Sumado
esto,
ofusca
definición
del
área
muestreo
y,
como
resultado,
cual
corresponde
estimado
abundancia.
Después
reconocer
estos
retos,
identificamos
seis
estrategias
analíticas
revisamos
estudios
publicados
entre
evaluar
uso
prevalencia
cada
método.
Solamente
usó
cualquiera
métodos
identificamos.
mayoría
estimaron
relaciones
covarianza
lugar
predecir
densidad
lo
largo
áreas
más
amplias.
Después,
estrategia
analítica,
recopilamos
requerimientos
datos,
suposiciones,
ventajas
desventajas
ayudar
navegar
paisaje
busquen
apropiado
deberán
historia
vida
taxón
focal,
definir
cuidadosamente
marco
considerar
cuáles
tipos
recolección
datos
son
posibles.
El
reto
estimar
marcados
persiste;
aunque
existan
muchos
métodos,
hay
único
óptimo
cumpla
todas
circunstancias.
Mientras
sigan
evolucionando
sea
vez
común,
serán
todavía
importantes
informar
toma
decisiones
conservación.近几十年来红外相机陷阱技术的快速发展已经彻底改变了生物多样性监测的现状。尽管红外相机陷阱法在动物保护科学中有明确的应用,
但它很少被用来模拟无标记动物的种群数量。本研究旨在总结无标记动物的丰度估计所面临的挑战,
总结现有的分析框架并为寻求合适方法的实践者提供指导意见。当红外相机多次记录到无标记的动物时,
人们无法确定这些图像代表的是多个个体还是一个重复进入相机拍摄范围的个体。此外,
动物的运动导致不能清晰地划定采样区域,
因此也模糊了所对应区域的丰度估计。面对这些挑战,
我们确定了六种分析方法,
并综述了
年至
年发表的
项红外相机陷阱研究,
以评估每种方法的使用情况和流行程度。结果发现,
只有约
的研究使用了至少一种我们确定的丰度估计方法。这些研究大多是估计局部丰度或协变量关系,
而不是预测更大范围内的动物丰度或密度。接下来,
我们总结了每种分析方法的数据需求、假设、优点和缺点,
以帮助实践者了解丰度估计方法的总体情况。实践者在寻找合适的方法时,
应评估研究所关注类群的生活史,
谨慎地确定采样范围,
并考虑可能收集到的数据类型。无标记动物的种群数量估计仍面临挑战,
虽然已存在多种方法,
但没有一种方法对于所有红外相机陷阱数据都是最优的。随着分析框架的不断发展和对无标记动物数量估计变得越来越普遍,
红外相机陷阱法在为指导保护决策中也将更加重要。【翻译:
胡怡思;
审校:
聂永刚】.
Conservation Science and Practice,
Год журнала:
2020,
Номер
2(8)
Опубликована: Июнь 19, 2020
Abstract
Camera
traps
(CTs)
are
an
increasingly
popular
method
of
studying
animal
behavior.
However,
the
impact
cameras
on
detected
individuals—such
as
from
mechanical
noise,
odor,
and
emitted
light—has
received
relatively
little
attention.
These
impacts
particularly
important
in
behavioral
studies
conservation
that
seek
to
ascribe
changes
behavior
relevant
environmental
factors.
In
this
article,
we
discuss
three
sources
bias
using
CTs:
(a)
disturbance
caused
by
cameras;
(b)
variation
animal‐detection
parameters
across
camera
models;
(c)
biased
detection
individuals
age,
sex,
classes.
We
propose
several
recommendations
aimed
at
mitigating
responses
CTs
wildlife.
Our
offer
a
platform
for
development
more
rigorous
robust
CT
technology
and,
if
adopted,
would
result
greater
applied
benefits
management.
Conservation Letters,
Год журнала:
2022,
Номер
15(2)
Опубликована: Янв. 26, 2022
Abstract
The
establishment
of
protected
areas
(PAs)
is
a
central
strategy
for
global
biodiversity
conservation.
While
the
role
PAs
in
protecting
habitat
has
been
highlighted,
their
effectiveness
at
mammal
communities
remains
unclear.
We
analyzed
dataset
from
over
8671
camera
traps
23
countries
on
four
continents
that
detected
321
medium‐
to
large‐bodied
species.
found
strong
positive
correlation
between
taxonomic
diversity
and
proportion
surveyed
area
covered
by
scale
(
β
=
0.39,
95%
confidence
interval
[CI]
0.19–0.60)
Indomalaya
0.69,
CI
0.19–1.2),
as
well
functional
PA
coverage
Nearctic
0.47,
0.09–0.85),
after
controlling
human
disturbances
environmental
variation.
Functional
was
only
weakly
(and
insignificantly)
correlated
with
0.22,
−0.02–0.46),
pointing
need
better
understand
response
protection.
Our
study
provides
important
evidence
conserving
terrestrial
mammals
emphasizes
critical
area‐based
conservation
post‐2020
framework.
Ecology and Evolution,
Год журнала:
2019,
Номер
9(24), С. 14031 - 14041
Опубликована: Ноя. 22, 2019
Abstract
Camera
traps
(CTs)
are
an
increasingly
popular
tool
for
wildlife
survey
and
monitoring.
Estimating
relative
abundance
in
unmarked
species
is
often
done
using
detection
rate
as
index
of
abundance,
which
assumes
that
has
a
positive
linear
relationship
with
true
abundance.
This
assumption
may
be
violated
if
movement
behavior
varies
density,
but
the
degree
to
density‐dependent
across
taxa
unclear.
The
potential
confounding
population‐level
indices
by
would
depend
on
how
regularly,
what
magnitude,
home‐range
size
vary
density.
We
conducted
systematic
review
meta‐analysis
quantify
relationships
between
rate,
size,
terrestrial
mammalian
taxa.
then
simulated
animal
movements
CT
sampling
test
effect
contrasting
scenarios
indices.
Overall,
were
negatively
correlated
density
positively
one
another.
strength
varied
significantly
populations.
In
simulations,
rates
related
underestimated
change,
particularly
slower
moving
small
home
ranges.
situations
where
space
use
changes
markedly
we
estimate
up
thirty
percent
change
missed
due
movement,
making
trend
estimation
more
difficult.
common
remains
constant
densities
therefore
wide
range
mammal
species.
When
studying
rates,
researchers
managers
should
explicitly
consider
such
reflect
both
movement.
Practitioners
interpreting
camera
aware
observed
differences
biased
low
Further
information
or
methods
do
not
assumptions
density‐independent
required
make
robust
inferences
population
trends.
Scientific Reports,
Год журнала:
2021,
Номер
11(1)
Опубликована: Ноя. 29, 2021
Abstract
Information
from
camera
traps
is
used
for
inferences
on
species
presence,
richness,
abundance,
demography,
and
activity.
Camera
trap
placement
design
likely
to
influence
these
parameter
estimates.
Herein
we
simultaneously
generate
compare
estimates
obtained
(a)
placed
optimize
large
carnivore
captures
(b)
random
placement,
infer
accuracy
biases
Both
setups
recorded
25
when
same
number
of
trail
cameras
(n
=
31)
were
compared.
However,
accumulation
rate
was
faster
with
cameras.
Relative
abundance
indices
(RAI)
surrogated
estimated
capture-mark-recapture
distance
sampling,
while
RAI
biased
higher
carnivores
Group
size
wild-ungulates
both
comparable.
Random
detected
nocturnal
activities
wild
ungulates
in
contrast
mostly
diurnal
observed
Our
results
show
that
setup
give
similar
richness
group
size,
but
differ
relative
activity
patterns.
Therefore,
made
each
designs
the
above
parameters
need
be
viewed
within
this
context.
Proceedings of the National Academy of Sciences,
Год журнала:
2022,
Номер
119(52)
Опубликована: Дек. 19, 2022
Human
disturbance
may
fundamentally
alter
the
way
that
species
interact,
a
prospect
remains
poorly
understood.
We
investigated
whether
anthropogenic
landscape
modification
increases
or
decreases
co-occurrence—a
prerequisite
for
interactions—within
wildlife
communities.
Using
4
y
of
data
from
>2,000
camera
traps
across
human
gradient
in
Wisconsin,
USA,
we
considered
74
pairs
(classifying
as
low,
medium,
high
antagonism
to
account
different
interaction
types)
and
used
time
between
successive
detections
measure
their
co-occurrence
probability
define
networks.
Pairs
averaged
6.1
[95%
CI:
5.3,
6.8]
d
low-disturbance
landscapes
(e.g.,
national
forests)
but
4.1
[3.5,
4.7]
high-disturbance
landscapes,
such
those
dominated
by
urbanization
intensive
agriculture.
Co-occurrence
networks
showed
higher
connectance
(i.e.,
larger
proportion
possible
co-occurrences)
greater
proportions
low-antagonism
disturbed
landscapes.
Human-mediated
abundance
(possibly
via
resource
subsidies)
appeared
more
important
than
behavioral
mechanisms
changes
daily
activity
timing)
driving
these
patterns
compressed
The
spatiotemporal
compression
co-occurrences
likely
strengthens
interactions
like
competition,
predation,
infection
unless
can
avoid
each
other
at
fine
scales.
Regardless,
human-mediated
with—and
hence
increased
exposure
to—predators
competitors
might
elevate
stress
levels
individual
animals,
with
cascading
effects
populations,
communities,
ecosystems.
Abstract
Optimizing
energy
acquisition
and
expenditure
is
a
fundamental
trade‐off
for
consumers,
strikingly
reflected
in
how
mobile
organisms
use
space.
Several
studies
have
established
that
home
range
size
decreases
as
resource
density
increases,
but
the
balance
of
costs
benefits
associated
with
exploiting
given
unclear.
We
evaluate
ability
consumers
to
exploit
their
resources
through
movement
(termed
“resource
exploitation”)
interacts
influence
size.
then
contrast
two
hypotheses
exploitation
influences
across
vast
gradient
productivity
human‐created
linear
features
(roads
seismic
lines)
are
known
facilitate
animal
movements.
Under
Diffusion
Facilitation
Hypothesis,
predicted
lead
more
diffuse
space
larger
ranges.
Exploitation
Efficiency
increase
foraging
efficiency,
resulting
less
being
required
meet
energetic
demands
therefore
smaller
Using
GPS
telemetry
data
from
142
wolves
(
Canis
lupus
)
distributed
over
than
500,000
km
2
,
we
found
wolf
was
influenced
by
interaction
between
efficiency.
Home
decreased
feature
increased,
supporting
Hypothesis.
However,
effect
on
diminished
productive
areas,
suggesting
efficiency
greater
importance
when
low.
These
results
suggest
ranges
will
occur
where
both
primary
higher,
thereby
increasing
regional
density.
Ecological Applications,
Год журнала:
2022,
Номер
33(1)
Опубликована: Сен. 15, 2022
Abstract
Estimating
habitat
and
spatial
associations
for
wildlife
is
common
across
ecological
studies
it
well
known
that
individual
traits
can
drive
population
dynamics
vice
versa.
Thus,
commonly
assumed
individual‐
population‐level
data
should
represent
the
same
underlying
processes,
but
few
have
directly
compared
contemporaneous
representing
these
different
perspectives.
We
evaluated
circumstances
under
which
collected
from
Lagrangian
(individual‐level)
Eulerian
(population‐level)
perspectives
could
yield
comparable
inference
to
understand
how
scalable
information
population.
used
Global
Positioning
System
(GPS)
collar
(Lagrangian)
camera
trap
(Eulerian)
seven
species
simultaneously
in
eastern
Washington
(2018–2020)
compare
inferences
made
survey
fit
respective
streams
resource
selection
functions
(RSFs)
occupancy
models
estimated
habitat‐
space‐use
patterns
each
species.
Although
previous
considered
whether
generated
information,
ours
first
make
this
comparison
multiple
specifically
ask
two
differed
depending
on
focal
found
general
agreement
between
predicted
distributions
most
paired
analyses,
although
specific
relationships
differed.
hypothesize
discrepancies
arose
due
differences
statistical
power
associated
with
GPS‐collar
sampling,
as
mismatches
data.
Our
research
suggests
individual‐based
sampling
methods
capture
coarse
population‐wide
a
diversity
of
species,
results
differ
when
interpreting
wildlife‐habitat
relationships.
Basic and Applied Ecology,
Год журнала:
2022,
Номер
61, С. 68 - 81
Опубликована: Март 7, 2022
The
use
of
camera
traps
to
estimate
population
size
when
animals
are
not
individually
recognizable
is
gaining
traction
in
the
ecological
literature,
because
its
applicability
conservation
and
management.
We
estimated
synthetic
with
four
trap
sampling-based
statistical
models
that
do
rely
on
individual
recognition.
Using
a
realistic
model
animal
movement
generate
data,
we
compared
random
encounter
model,
staying
time
association
time-to-event-model
investigated
impact
violation
assumptions
estimates.
While
under
ideal
conditions
these
provide
reliable
estimates,
movements
were
characterised
by
differences
speed
(due
diverse
behaviours
such
as
locomotion,
grazing
resting)
none
provided
both
unbiased
precise
density
results
but
tended
overestimate
size,
while
was
less
underestimate
size.
Lastly,
unable
results.
found
each
tested
very
sensitive
method
used
range
field-of-view
traps.
Density
estimates
from
also
biases
animals'
speed.
guidelines
how
get
could
be
useful
wildlife
managers
practitioners.