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The relative contribution of local habitat and landscape context
to metapopulation processes: a dynamic occupancy modeling
approach
Sarah J. K. Frey, Allan M. Strong and Kent P. McFarland
S. J. K. Frey (sarah.frey@oregonstate.edu), Dept of Forest Ecosystems and Society, Oregon State Univ., Corvallis, OR 97331, USA. – A. M. Strong,
Rubenstein School of Environment and Natural Resources, Univ. of Vermont, Burlington, VT 05405, USA. – K. P. McFarland, Vermont Center
for Ecostudies, PO Box 420, Norwich, VT 05055, USA.
Changes in site occupancy across habitat patches have often been attributed to landscape features in fragmented systems,
particularly when considering metapopulations. However, failure to include habitat quality of individual patches can mask
the relative importance of local scale features in determining distributional changes. We employed dynamic occupancy
modeling to compare the strength of local habitat variables and metrics of landscape patterns as drivers of metapopulation
dynamics for a vulnerable, high-elevation species in a naturally fragmented landscape. Repeat surveys of Bicknell’s thrush
Catharus bicknelli presence/non-detection were conducted at 88 sites across Vermont, USA in 2006 and 2007. We used an
organism-based approach, such that at each site we measured important local-scale habitat characteristics and quantified
landscape-scale features using a predictive habitat model for this species. We performed a principal component analysis on
both the local and landscape features to reduce dimensionality. We estimated site occupancy, colonization, and extinction
probabilities while accounting for imperfect detection. Univariate, additive, and interaction models of local habitat and
landscape context were ranked using AICc scores. Both local and landscape scales were important in determining changes
in occupancy patterns. An interaction between scales was detected for occupancy dynamics indicating that the relation-
ship of the parameters to local-scale habitat conditions can change depending on the landscape context and vice versa.
An increase in both landscape- and local-scale habitat quality increased occupancy and colonization probability while
decreasing extinction risk. Colonization and extinction were both more strongly influenced by local habitat quality relative
to landscape patterns. We also identified clear, qualitative thresholds for landscape-scale features. Conservation of large
habitat patches in high-cover landscapes will help ensure persistence of Bicknell’s thrushes, but only if local scale habitat
quality is maintained. Our results highlight the importance of incorporating information beyond landscape characteristics
when investigating patch occupancy patterns in metapopulations.
Understanding distributional patterns of organisms in space
and time is a fundamental question in ecology. Variations in
species occurrence patterns can elucidate drivers of important
population processes such as site occupancy, colonization,
and local extinction (Gaston 1990). By linking these pro-
cesses to environmental features we can begin to understand
the ecological factors that motivate habitat selection and
drive changes in species distributions. Landscape structure
(MacArthur and Wilson 1967, Hanski 1998) and composi-
tion (With et al. 1997), local patch characteristics (Mortelliti
et al. 2010), and species’ dispersal capabilities (Thomas 2000)
have all been implicated as important drivers of distribution
dynamics.
Incorporation of spatial structure into population
dynamics is a central concept of metapopulation models
(Hanski 1998). A metapopulation is defined as a network
of sub-populations that are linked by migration. Changes
in occupancy state, through subpopulation extinction and
colonization, depends on the size and isolation of the habi-
tat patch (Hanski 1998). However, most landscape studies
only consider features at the landscape-scale (i.e. patch size
and isolation), while ignoring local habitat quality within
patches (Mortelliti et al. 2010). This can be an oversimpli-
fication (Hastings and Harrison 1994), especially in hetero-
geneous ecosystems where distributions are likely driven by
factors at multiple scales. There is increasing evidence that
this variation in local habitat quality is an important fac-
tor in population dynamics and should be incorporated into
metapopulation models (Thomas et al. 2001, Fleishman
et al. 2002, Armstrong 2005), however, there have been few
empirical tests (Mortelliti et al. 2010). Further, investigations
of the influence of landscape structure on metapopulation
processes are generally conducted in anthropogenically frag-
mented forest surrounded by an agricultural matrix (Opdam
1991), as opposed to naturally fragmented systems.
Dynamic (or multi-season) occupancy models (MacKenzie
et al. 2003) can be used to assess distributional patterns at a
variety of scales. Dynamic occupancy models allow estimation
of the probability that a site will be occupied, as well as colo-
nization and extinction probabilities. Occupancy modeling
Ecography 34: 001–009, 2011
doi: 10.1111/j.1600-0587.2011.06936.x
© 2011 The Authors. Journal compilation © 2011 Ecography
Subject Editor: Michel Baguette. Accepted 8 July 2011
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can be used to address an array of questions about distribu-
tional patterns through inclusion of survey- and site-specific
covariates to calculate unbiased colonization and extinction
rates through the incorporation of detection probabilities
(MacKenzie et al. 2003). Including detection probabilities
into dynamic occupancy models avoids issues associated
with false absences thought to be the largest source of bias in
traditional approaches to the estimation of metapopulation
parameters (Moilanen 2002).
Species with spatially isolated subpopulations, especially
those that occupy naturally restricted ranges, are well suited
for this type of approach (Hanski 1998). Bicknell’s thrush
Catharus bicknelli is a montane fir-forest specialist that
inhabits a naturally fragmented breeding range in the north-
eastern United States, southeastern Québec, and Maritime
Canada (Rimmer et al. 2001, Lambert et al. 2005). It
occupies ephemeral, disturbance-driven, mid-successional,
fir-dominated forests within montane or highland regions.
Bicknell’s thrush is ranked as a top conservation prior-
ity among Nearctic-Neotropical migrants in the northeast
(Rich et al. 2004) with a global status of vulnerable (BirdLife
International 2000). A habitat model for Bicknell’s thrush
(Lambert et al. 2005) allowed us to define landscape ele-
ments from a species-specific perspective (Betts et al. 2006).
Here we used dynamic occupancy modeling (MacKenzie
et al. 2003) and Akaike’s information criterion (AIC) model
selection techniques (Burnham and Anderson 2002) to test
the relative importance of local-scale habitat characteristics
versus landscape-scale features in determining Bicknell’s
thrush site occupancy patterns over time. We used this anal-
ysis to assess metapopulation processes within an existing
potential habitat model (Lambert et al. 2005) in Vermont
and determine how metapopulation processes relate to
habitat features at multiple scales.
Methods
Field surveys
Detection/non-detection data were collected over a two-
year period from 2006 to 2007 within the Bicknell’s thrush
breeding range across the state of Vermont, USA. We
focused on the metapopulation of the Green and Taconic
Mountains, and Northeastern Highlands of Vermont, where
sub-populations were defined by high-elevation habitat
islands delineated using an existing habitat model for this
species (Lambert et al. 2005). A total of 88 sites between 733
and 1236 m elevation were surveyed (Fig. 1). Twenty-nine
sites (hereafter, SF sites) were added to 59 sites surveyed in
Vermont through a citizen-science program called Mountain
Birdwatch (MBW, Hart and Lambert 2007). Each site con-
sisted of a 1-km transect of five points separated by 200–
250 m (seven sites contained 3–4 points due to patch size
constraints). Bird sample locations covered a rectangular area
of roughly ∼25 ha (1 km by ∼250 m), which approximates
the size of five to 10 Bicknell’s thrush breeding home ranges
(2.33–4.53 ha, Rimmer et al. 2001).
MBW sites were selected through random selection of
high-elevation forests (montane areas  823 m, Hart and
Lambert 2007). SF sites were chosen from the remaining
un-surveyed MBW sites in Vermont and filled gaps in MBW
sampling by surveying marginal habitat and sites without
hiking trails. The 1-km transects were fit into the habitat
polygons defined by Lambert et al. (2005), following a
straight line wherever possible, often along ridgelines.
Surveys were conducted during the peak of the breeding
season (late May–mid-July) at optimal activity times (dawn
and dusk) under favorable weather conditions. A maxi-
mum of three surveys were conducted at each site each year
(mean  SD  2.1  0.9) with slight differences between
MBW and SF sites (see following two paragraphs for details).
In the MBW survey protocol, the first survey period occurred
between 04:30 and 06:30 h EST and consisted of a 10-min
point count at each point along the transect. If no Bicknell’s
thrush were detected during the first survey period, up to
two additional surveys were conducted to increase oppor-
tunity for detection. The second survey period directly fol-
lowed the first survey and consisted of a 1-min playback of
Bicknell’s thrush songs and calls followed by a 2-min silent
listening period at each point. If no Bicknell’s thrush were
detected on either the first or second surveys, a third survey
was conducted within two weeks following the initial sur-
veys (or before 15 July). The third survey occurred between
either 04:30 and 06:30 h or 20:00 and 21:00 h and was done
by broadcasting the 1-min playback and listening for 2 min
every 100 m along the transect.
For SF sites, the three surveys were almost always con-
ducted during a single visit to the site, weather permitting.
This was achieved by conducting an evening survey followed
by two morning surveys. During the evening survey a 5-min
point count was conducted followed by broadcasting a 1-min
playback and a 2-min listening period. Both morning sur-
veys followed the same protocol as MBW. Detections were
categorized as within or outside a 50-m radius around the
survey point, although all observations were counted assum-
ing an approximate detection limit of 125 m. For each sur-
vey at a given site (MBW and SF), either 1 (detection) or 0
(non-detection) was recorded based on whether a Bicknell’s
thrush was heard or seen anywhere along the transect. We
tested for an effect of survey technique on detection prob-
ability during the modeling process and found little support
for survey type to influence detection probability (Table 1).
Local-scale habitat measurements
Local habitat conditions were quantified once in either 2006
or 2007 and were assumed to be constant within this time
period. Because within-site variation was negligible, local
habitat measurements were averaged across all points to
obtain a single site value. We measured site variables rep-
resentative of habitat quality for Bicknell’s thrush based on
the species’ natural history (Table 2, Rimmer et al. 2001),
assuming these variables are linked to resource availability
(Strong et al. 2004). To quantify coniferous shrub density
at each point, we used the point-centered quarter method
(Cottam and Curtis 1956). We measured basal area of snags
(using a wedge prism), as snags are a useful structural indica-
tor of the two main causes of natural disturbance in montane
ecosystems in the northeastern US: severe weather and fir
waves (Sprugel 1976), both of which result in areas of forest
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