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Semeletal. Movement Ecology (2022) 10:20
https://doi.org/10.1186/s40462-022-00320-x
RESEARCH
Environmental andanthropogenic
inuences onmovement andforaging
inacritically endangered lemur species,
Propithecus tattersalli: implications forhabitat
conservation planning
Meredith A. Semel1* , Heather N. Abernathy2, Brandon P. Semel2 , Michael J. Cherry3,
Tsioriniaina J. C. Ratovoson4 and Ignacio T. Moore1
Abstract
Background: Wildlife conservation often focuses on establishing protected areas. However, these conservation
zones are frequently established without adequate knowledge of the movement patterns of the species they are
designed to protect. Understanding movement and foraging patterns of species in dynamic and diverse habitats
can allow managers to develop more effective conservation plans. Threatened lemurs in Madagascar are an example
where management plans and protected areas are typically created to encompass large, extant forests rather than
consider the overall resource needs of the target species.
Methods: To gain an understanding of golden-crowned sifaka (Propithecus tattersalli) movement patterns, includ-
ing space use and habitat selection across their range of inhabited forest types, we combined behavior data with
Dynamic Brownian Bridge Movement Models and Resource Selection Functions. We also examined the influence of
abiotic, biotic, and anthropogenic factors on home range size, movement rates, and foraging patterns.
Results: We found that home range size and movement rates differed between seasons, with increased core area
size and movement in the rainy season. Forest type also played a role in foraging behavior with sifaka groups in the
humid forest avoiding roads in both seasons, groups in the dry deciduous forest avoiding road networks in the rainy
season, and groups in the moderate evergreen forest displaying no selection or avoidance of road networks while
foraging.
Conclusion: Our study illustrates the importance of studying primate groups across seasons and forest types, as
developing conservation plans from a single snapshot can give an inaccurate assessment of their natural behavior
and resources needs of the species. More specifically, by understanding how forest type influences golden-crowned
sifaka movement and foraging behavior, conservation management plans can be made to the individual forest types
inhabited (dry deciduous, moderate evergreen, humid, littoral, etc.), rather than the region as a whole.
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Open Access
*Correspondence: merak91@vt.edu
1 Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061,
USA
Full list of author information is available at the end of the article
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Page 2 of 16
Semeletal. Movement Ecology (2022) 10:20
Background
Conservation biologists have long recognized the impor-
tance of establishing protected areas to facilitate popu-
lation persistence of wildlife in landscapes that are
threatened by increasing human encroachment, habitat
fragmentation, and habitat loss [1–4]. However, efforts
to conserve wildlife and preserve biodiversity often are
based on an incomplete understanding of animal move-
ment as well as variability in movement patterns among
groups or populations that the areas are meant to pro-
tect [5]. While a number of studies have demonstrated
the relevance of incorporating movement, particularly
animal foraging and home range size, into protected
area design [6–9], integration between the disciplines
of conservation biology and movement (coined “conser-
vation behavior”) is limited [10, 11]. Yet, knowledge of
movement behavior, specifically how, when, and where
animals move and forage within their habitat, would illu-
minate how populations navigate and utilize resources
within their environment and thus develop better man-
agement plans [12, 13]. Specifically, species, populations,
or even groups often respond differently to factors such
as seasonality, habitat characteristics, and anthropogenic
pressures and therefore a better understanding of their
role is crucial when developing management plans and
establishing protected areas.
In many tropical regions, seasons are often divided into
dry and rainy, with primary productivity varying season-
ally as a function of rainfall. is seasonality thus influ-
ences the distribution and availability of resources on
the landscape and as a result animal movement strate-
gies shift to increase foraging efficiency [14–16]. For
example, the black-fronted titi monkey (Callicebus nigri-
fons) [17] and collared brown lemur (Eulemur collaris)
[18] cope with dry season food shortages by reducing
movement rates, while the common bumble bee (Bom-
bus vosnesenskii) [19] and African elephant (Loxodonta
africana) [20], respond by increasing foraging and move-
ment rates. us, animals are coping with dry season
conditions by shifting home range size or location [21]
and altering time spent foraging [22]. Understanding
how seasonal fluctuations influence movement and for-
aging patterns in free-living animals can allow managers
to more effectively design protected areas and protect
critical resources [23].
In addition to abiotic factors, biotic factors such as hab-
itat type, strongly influence animal movement and forag-
ing [24]. Various studies demonstrate that animals adjust
their home range size and foraging patterns in response
to habitat type and structure (e.g. roe deer (Capreolus
capreolus) [25] and coyote (Canis latrans) [26]); indi-
cating that landscape heterogeneity is a key factor influ-
encing the movement of species. While studies of canids,
ungulates, and primates have examined the influence of
habitat type on home range size, a large proportion of
studies are limited to examining metrics of habitat struc-
ture (e.g., forest maturity, vegetation density, food scar-
city, microhabitat preference) on animal movement and
home range size [27, 28]. e benefit of understanding
movement behavior across distinct habitat types is that
management strategies can be designed for each habitat
type a species occupies.
Importantly, anthropogenic influences affecting animal
movement behaviors can have deleterious effects on wild-
life, and must be considered when establishing protected
areas [29, 30]. e presence of human developments and
road networks may negatively influence animal move-
ment behavior by increasing human-wildlife interactions
(e.g., hunting, poaching, vehicle collisions) and pushing
animals out of prime habitat [31, 32]. Large mammals
may be especially affected by human encroachment due
to their larger home range size, lower population density,
more narrow geographic distributions, and large por-
tions of their distributions being shared with humans
[33]. For instance, black bears (Ursus americanus) have
been found to avoid areas with human development dur-
ing daylight hours [34] and woodland caribou (Rangifer
tarandus caribou) avoid high use roads, mines, and cab-
ins during months of high human activity [35]. Few stud-
ies have examined the influence of human infrastructure
on primate movement, although they often are strongly
affected by anthropogenic activities [36, 37].
e lemurs of Madagascar face significant anthropo-
genic threats [38]. Between 1953 and 2014, Madagascar
lost 44% of its forests due to clearing for slash and burn
agriculture, resulting in 46% of the remaining forests
being located within 100 m of a forest edge [39]. is
high degree of forest destruction and increasing pres-
ence of edge forest habitat has influenced lemur behav-
ior and their ability to meet nutritional demands. While
our understanding of lemur movement is limited, a few
studies have examined lemur home range size [40, 41],
dietary flexibility [42], species abundance [43], and
reproduction in various forest types [44, 45]. Within the
genus Propithecus, groups of diademed sifakas (P. dia-
dema) in humid fragmented habitats had reduced home
Keywords: Movement, Space use, Foraging, Resource selection, Brownian bridge modeling, Home range, Road
avoidance, Primates, Lemurs
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Page 3 of 16
Semeletal. Movement Ecology (2022) 10:20
range size and daily path length and foraged on sub-
optimal food items compared to sifaka groups in con-
tiguous forest environments [40]. In contrast, groups of
Milne-Edwards’ sifakas (P. edwardsi) inhabiting humid
logged forests traveled shorter distances each day to feed
in a low-quality food environment, yet maintained larger
home ranges than groups in contiguous forests [41].
Further, groups of Verreaux’s sifakas (P. verreauxi) in
Madagascar’s dry deciduous forests exhibited significant
home range reduction from the rainy to the dry season
[46]. While these studies have shed light on Propithecus
behavioral responses to abiotic and biotic factors in
extremes of the humid-dry forest gradient of forest types,
we do not understand how species in the genus Pro-
pithecus respond in a moderate forest type. Knowledge of
Propithecus movement behavior in regards to these fac-
tors would enable us to predict how these lemurs would
adapt to changes in forest habitat and design a reserve
accordingly.
Golden-crowned sifaka (Propithecus tattersalli) are a
critically endangered lemur endemic to naturally frag-
mented forests of northeastern Madagascar [47]. Unlike
the other eight species of sifaka (Propithecus spp.) on
Madagascar that are restricted to dry or humid forest
types, P. tattersalli inhabit a range of forest types [48,
49]. Variation of forest types they inhabit makes them a
unique opportunity to examine the influence of seasonal-
ity, forest type, and anthropogenic factors on movement
and foraging behavior in a primate. Studies of golden-
crowned sifaka have documented a major decline in the
overall population in the last decade and studies have
informed researchers of the species selective use of for-
ests in a naturally fragmented landscape. However, no
studies have examined the influence of movement on
space use and foraging tree selection across their range
[50, 51]. An understanding of how abiotic, biotic, and
anthropogenic factors influence golden-crowned sifaka
space use and foraging throughout their range would
allow unique management plans to be developed for dis-
tinct populations within each particular forest type occu-
pied rather than the species as a whole.
In this study, we analyzed location and foraging behav-
ior of six golden-crowned sifaka groups to evaluate the
effects of abiotic (seasonality: rainy and dry season),
biotic (forest type: dry deciduous, moderate evergreen,
and humid forests), and anthropogenic (disturbance:
edge and interior forests) factors on their movement pat-
terns and space use. Approaches to studying nonhuman
primate space use typically are limited to examining daily
path length and home range overlap through the use of
area estimators (minimum convex polygon, line-based
kernel density, etc.) [52, 53]. More modern and sophis-
ticated approaches such as Dynamic Brownian Bridge
movement models (DBBMM) and Bayesian methods
[54, 55] reduce the likelihood of both Type I and Type II
errors which can bias our understanding of animal space
use and habitat selection [56]. By selecting DBBMM to
estimate space use we were able to incorporate both tem-
poral and behavioral characteristics of movement trajec-
tories into estimation of an animal’s home range [57].
To test our first objective, we predicted that seasonal
movement rates would be greater in the rainy season,
when we expected that sifakas would search out energy
rich but spatially limited resources (i.e. fruits). In con-
trast, we expected that sifakas in the dry season would
be conserving limited energy resources and thus restrict
their movements. We also expected greater movement
rates in more extreme forest types (dry and humid for-
ests) and edge forests compared to moderate evergreen
and interior forests for similar energetic reasons [58], as
well as differences in sifakas densities between the three
forest types [59]. Second, we predicted that home range
size and core area range size would be larger in the rainy
season compared to the dry season, as sifakas would
maximize their foraging area to exploit energy rich, rainy
season resources. We also expected home range and core
areas to be larger along forest edges, where energy-rich
resources may be more limited [58]. Additionally, we
predicted that home range and core areas sizes would
be larger in the dry and humid forests where golden-
crowned sifaka densities are lower, and smaller in the
moderate forests where golden-crowned sifaka densities
are higher [59]. ird, we predicted that sifakas would
select foraging locations with the largest feeding trees
within their home ranges, which we expected to have
the most available fruits [60], and avoid locations near
human settlements or man-made structures, where we
expected forest disturbance to be greatest [61].
Methods
Study area
Research was conducted in the Loky-Manambato Pro-
tected Area (49°56ʹE, 13°31ʹS) of northeastern Madagas-
car (Fig. 1). is protected area encompasses a unique
biogeographical transition zone from Madagascar’s
northern and western dry deciduous forests to southern
humid forests. e Loky-Manambato region contains a
mosaic of various forest types including dry deciduous,
dry evergreen, humid, and littoral forests separated by
agricultural areas and savanna [50]. e total forest cover
of this protected area is 475.3 km2 and individual forest
fragments range from 11.6 to 46.3 km2. e region expe-
riences a 4-month rainy season from December to March
followed by an 8-month dry season [62]. e study sites
include three distinct forest types: humid forest, moder-
ate evergreen forest, and dry deciduous forest.
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Semeletal. Movement Ecology (2022) 10:20
Study species andsubjects
Golden-crowned sifaka live in semi-cohesive social
groups ranging in size from 3 to 12 individuals with one
or more adult males, several adult females, and several
immature individuals of both sexes. Group members
typically travel in a coordinated fashion and generally
remain in visual or auditory contact with at least one
other group member [62]. us, we assume that all ani-
mals within a given social group share a home range, and
therefore treated each group as a distinct unit of analysis.
Golden-crowned sifaka are frugo-folivores, but also con-
sume seeds, petioles, buds, flowers, and bark.
We studied six groups of golden-crowned sifaka dis-
tributed across the three distinct forest types (two groups
each in dry deciduous, moderate evergreen, and humid
forest) in the Loky-Manambato Protected Area. Prior
to data collection, all groups were habituated to human
presence. Habituation was considered complete when
lemurs no longer alarm called, fled from human presence,
or moved closer to observers out of curiosity. Similar to
studies conducted with other lemur species, this process
took less than 2 months [63]. We selected three of the
11 large forest fragments containing golden-crowned
sifaka due to their accessibility: Solaniampilana (dry
deciduous), Bekaraoka (moderate evergreen), and Binara
(humid) (Fig.1). Sifaka densities within these fragments
were variable with 26.7 sifakas/km2 (95% CI 16.2–44.1) in
Solaniampilana, 78.17 sifakas/km2 (95% CI 53.1–114.8)
in Bekaraoka, and 20.77 sifakas/km2 (95% CI 11.2–38.0)
in Binara [59]. Within each forest type, we followed one
group in primary forest towards the center of the for-
est (hereafter interior; characterized by lemurs having
a home range at least 300m from the forest edge) and
one group on the edge of the forest fragment (hereafter
Fig. 1 Map of the golden-crowned sifaka (Propithecus tattersalli) range within the Loky-Manambato Protected Area in northeastern Madagascar, as
indicated in the box on the inset of Madagascar. Different shades of green indicate the three main forest types and hatched black lines indicate the
three forest fragments surveyed: dry (light green, Solaniampilana), moderate (green, Bekaroaka), and wet (dark green, Binara). The thin orange line
depicts the unpaved national road in the region
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Page 5 of 16
Semeletal. Movement Ecology (2022) 10:20
edge; characterized by having a home range adjacent to
the forest edge). Average group size was six individuals
and ranged from five to eight (Table1). Although lemur
groups were not marked or collared, we identified indi-
vidual lemurs by their distinct, permanent physical fea-
tures (e.g. missing eye, ear cuts, coloration) to ensure we
were following the target group.
Group location data
We collected golden-crowned sifaka group location data
during two periods, February-April 2019 (rainy season)
and June–August 2019 (dry season). Each group was
followed for 7–9 consecutive days during the rainy sea-
son and the dry season. We followed groups from sleep
tree to sleep tree (~ 12h per day) and collected location
data at 15-min intervals. If no animals were visible at the
15-min interval, observers waited to establish visual con-
tact with the social group before recording any locations.
During behavioral follows, we maintained a distance of at
least 10m from the lemurs and followed slowly behind
the groups in an effort to minimize disrupting their nat-
ural behaviors. While the use of telemetry based track-
ing technology has been shown to reduce disturbances
to wildlife behavior, we chose behavioral follows due to
a lack of tracking equipment but also to avoid subjecting
the animals to the stress of capture and immobilization
[64]. In addition to daytime activity, golden-crowned
sifaka are known to exhibit nocturnal movements, specif-
ically during periods of bright moon light [65], and thus
groups were not always located in the same sleep tree the
following morning. In those instances, we reestablished
contact with the group as quickly as possible. Group
locations were recorded using a GPS receiver (Garmin
64s), using the Universal Transverse Mercator (UTM)
coordinate system (zone 39L), and points were logged at
the group’s approximate geometric center.
Foraging andlandscape data
We recorded foraging data at the same 15-min intervals
using scan sampling to record the behavior, height in the
tree, and nearest neighbor of each individual in a group
[66]. If an individual was actively feeding during the scan,
the plant species and part (e.g., young/mature leaf, leaf
petiole, un/ripe fruit, seed, or flower) were identified,
GPS location recorded, and data concerning tree species,
size, and current phenology collected. In addition to col-
lecting foraging data specific to each of the lemur groups,
we also collected general landscape data throughout each
of the six lemur home ranges in both the rainy and dry
season. We did this by randomly generating forty GPS
points within each of the six home ranges (in both rainy
and dry seasons) and collected data from potential feed-
ing trees (species, size, phenology) within five m of each
location. is allowed us to gain an understanding of the
entire landscape of all six home ranges, not just the spe-
cific feeding trees utilized by each of the groups.
Home range estimation
Utilization distributions (i.e., 95% isopleth, hereaf-
ter home ranges and 50% isopleth, hereafter core area)
were estimated for each golden-crowned sifaka group
using Dynamic Brownian Bridge Movement Models
(DBBMM); [57]. Home range DBBMMs use behavior
and movement trajectory data of the animal group that
is collected in sequential relocation studies. is method
provides a spatially explicit model, which describes the
probability of the given animal group occurring in a given
location during a specified period. is approach also
accounts for temporal autocorrelation, spatial uncer-
tainty, irregularly sampled data, and shifts in an animal’s
behavior (resting, foraging, thermoregulating, corridor
use, etc.), making it specifically applicable to studies of
group living primates [56, 57, 67]. Using DBBMMs to
estimate group home ranges requires a Brownian motion
variance parameter (σ2, in meters), which quantifies the
degree of diffusion or irregularity of an animal’s path
[57]. A moving window analysis identifies changes in
the movement behavior and estimates σ2 for each step.
Because the σ2 parameter is estimated using a “leave-one-
method”, the size of the moving window must include an
Table 1 Composition of golden-crowned sifaka (Propithecus tattersalli) focal groups within each forest fragment, fragment size, forest
type, and forest disturbance classification of the Loky-Manambato protected area in northeastern Madagascar
Groups were followed during the dry (June–August 2019) and rainy (February–April 2019) seasons
Forest fragment Fragment size (km2) Forest type Forest location Group size
Solaniampilana 14.7 Dry deciduous Interior 5
Solaniampilana Dry deciduous Edge 5
Bekaraoka 26.2 Moderate evergreen Interior 7
Bekaraoka Moderate evergreen Edge 8
Binara 43.6 Wet humid Interior 7
Binara Wet humid Edge 5
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Page 6 of 16
Semeletal. Movement Ecology (2022) 10:20
odd number of GPS locations and a margin of greater
than three locations bounding each end of the window in
which no behavioral changes can occur [57]. We param-
eterized the DBBMM with a 21-step window size, a
9-step margin size, and a 15m location error for all lemur
groups, as visual inspection indicated these settings were
sufficient to identify changes in home range size and
overall animal movement [57]. Home ranges were esti-
mated for each lemur group using the DBBMM function
in R package ‘move’ [68, 69]. We conducted a three-way
analysis of variance (ANOVA) predicting for both home
range and core areas sizes, respectively, to determine if
season, forest type, interior or edge forests, and the inter-
action of forest type and season influenced core area and
home range size. All analyses were conducted in version
3.6.1 of program R [70]. We used Akaike’s Information
Criterion corrected for small samples sizes (AICc) to
identify a top model from the set of candidate ANOVA
models and the delta of two was as a threshold for equally
plausible models [71].
Seasonal core area overlap
To determine the percent of joint home range overlap
between the rainy and dry season core areas, we calcu-
lated the total area of each home range and then divided
the area of overlap between seasons by the total home
range size [72].
Areaαβ is the seasonal core area overlap area common
to α and β, and core-area α and core-area β are the sea-
sonal core areas of the same group during the rainy and
dry season, α and β, respectively. Possible core area over-
lap ranged from 0% overlap, indicating no shared space
use between seasons, to 100% overlap, indicating the
dry and rainy season core area ranges overlapped com-
pletely. To determine if the core area overlap between
the rainy and dry seasons varied as a function of forest
type (humid, moderate, or dry), we conducted a one-way
ANOVA comparing core area overlap as a function of
degree of forest type. All analyses were conducted in ver-
sion 3.6.1 of program R [70].
Movement rates
We calculated movement rates (meters/monitoring
interval [15-min]) for each lemur group using the col-
lected relocation data. e step length (i.e., the distance
between sequential recorded locations) was divided by
the time elapsed between each sequential location (15-
min) to calculate speed for each golden-crowned sifaka
group to characterize movement rates. To determine how
movement varied across season (rainy and dry), forest
area
αβ
/core - areaα
×
area
αβ
/core - area
β0.5
disturbance (edge or interior), and forest types (dry, mod-
erate, and humid) we calculated movement rates at both
the daily and seasonal scale.
Daily movement rates were bootstrapped to calculate a
mean for each observational day. Bootstrapping is a pro-
cess that involves repeatedly drawing independent sam-
ples from a data set (x) to create bootstrap data sets (x1,
x2,…, xn). Our samples were performed with replacement
which allowed for the same observation to be sampled
more than once such that each bootstrapped sample was
the same length as our raw lemur speed data (m/15-min).
To calculate seasonal movement rates (
SMR
), we drew
1000 independent samples (
α1,
α2,...,
αB)
to calculate
means and standard error (
SEB
), which we then used
to generate 95% confidence intervals for comparison of
means among seasons and groups,
where
SEB
served as our estimate of the standard error
of
α
estimated from the raw lemur speed data (m/h). We
calculated seasonal movements rates using the boot-
strapping approach outlined above but employed the
method for each observation season [73, 74].
To determine how environmental variables influenced
daily movement rates, we fit LMMs to predict movement
rate as a function of all combinations of season (rainy or
dry), forest disturbance (edge or interior), and forest type
(dry, moderate, and humid), while treating forest type-
forest fragmentation per group intercepts as random
effects [75]. We used Akaike’s Information Criterion
corrected for small sample size (AICc) to identify a top
model from the set of candidate models [76]. We used
the Satterthwaite method to approximate the degrees of
freedom and computed p-values for direct effects and
interactions using t-statistics [77].
Finally, to determine how environmental variables
influenced seasonal movement rates, we conducted a
three-way ANOVA of seasonal movement rates as a
function of forest type (dry, moderate, and humid), for-
est disturbance (edge and interior), and season (dry and
rainy). We used Akaike’s Information Criterion corrected
for small sample size (AICc) to identify a top model from
the set of candidate models [76]. All analyses were con-
ducted in version 3.6.1 of program R [70].
Habitat selection
To quantify habitat selection of golden-crowned sifaka
groups, in relation to tree size and proximity to anthropo-
genic factors, we fit a Resource Selection Function (RSF)
using a use-available design. A RSF is defined as any func-
tion producing a value proportional to the probability of
SE
B=
B
b=1
ˆαi−ˆαB
2
(
B−1
)
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Page 7 of 16
Semeletal. Movement Ecology (2022) 10:20
selection of a given habitat [78, 79]. Any estimate derived
from an RSF is dependent on the definition of available
habitats [54, 78, 80]. For our RSF, selection by golden-
crowned sifaka availability was considered within home
range selection (Johnson’s third order [80]) as defined by
a 95% seasonal home range using DBBMMs. Within our
seasonal home ranges, we characterized availability by
systematically identifying available locations at intervals
of 10m, as this was the spatial resolution of all spatial
data used in the RSF [81].
We created our RSFs by fitting generalized linear
mixed-effects model (GLMM) with a binomial expo-
nential family and logit link function, which included a
group-specific (forest type and disturbance) random
intercept term to account for non-independence of habi-
tat associations within groups [82, 83]. For our RSF,
we used GPS locations of all feeding trees that golden-
crowned sifaka utilized during the rainy and dry field
seasons and possible locations within their known home
ranges. We extracted tree basal area (cross-sectional area
of trees at breast height), Euclidian distance to village,
road, and habitat fragment edge for each golden-crowned
sifaka feeding tree and each available location. ese
data were generated using satellite imagery and habitat
sampling of resources within each of the six lemur home
ranges.
To relate tree basal area and crown volume to lemur
GPS location data, we created continuous surfaces of tree
basal area and crown volume estimates across our study
area by using inverse distance weighting (IDW) inter-
polation in the package gstat [84]. IDW uses a weighted
average of estimates from nearby sampling locations to
predict tree basal area and crown volume estimates to
the surrounding pixels of a sampling location composed
of user-specified areas [85]. Our user-specified areas of
inference were 169 m2 because it most closely matched
the mean distance between vegetation sampling locations
(148.85m). is interpolation process provided spatially
explicit estimates of tree basal area and crown volume
estimates which we could then associate with our lemur
GPS data.
To examine if lemur habitat selection varied across for-
est types and seasons, we developed candidate models
using various combinations of distance to habitat fea-
ture (i.e., village, road, and habitat fragment), and basal
area, and used Akaike’s Information Criterion (AICc)
corrected for small samples sizes to identify a top model
from the set of candidate models [71] to determine if (1)
differences in habitat selection vary as a function of for-
est type, and (2) differences in habitat selection vary as a
function of season at each site. To account for behavioral
differences in lemur groups, we accounted for random
effects using an ‘animal ID’ that consisted of each lemur
group’s respective forest type (dry, moderate, or humid),
forest disturbance classification (edge or interior), and
season (rainy or dry). We tested for collinearity and no
environmental variables used in model development
exhibited high correlation (i.e., |r|> 0.7). All coefficients
were estimated using the “lme4” package [70, 75].
Overdispersion of the models was examined by calcu-
lating the sum of squared Pearson (SSQ) residuals, the
ratio of (SSQ residuals/residual degrees-of-freedom), the
residual df, and the p-value based on the appropriate χ2
distribution. Additionally, each individual model was a
GLM which allowed us to test overdispersion using a chi-
squared comparing the model deviance by the residual
degrees-of-freedom [86]. To estimate the explanatory
power of the models, we calculated a conditional, mar-
ginal, and pseudo R2 for each model [87, 88].
Results
Home range andcore area size estimations
Overall, home range sizes for golden-crowned sifaka
groups in the Loky-Manambato Protected Area were
highly variable, ranging from 2.78 to 31.56 hectares
(Table 2). Our top ANOVA model (Table 3), revealed
that golden-crowned sifaka core areas varied signifi-
cantly with season (p = 0.006, F(1,10) = 11.84, residual
SE = 0.005) with core areas being larger in the rainy sea-
son (average of 1.74 hectares in the rainy season, 0.81
hectares in the dry season). However, while our ANOVA
model candidate set for home ranges did include season
as a top model (dry or rainy; p = 0.136, F(1,10) = 2.63,
SE = 0.07), it was no better than our null model (Table3).
Seasonal core area overlap
Seasonal core area overlap varied from 16.7 to 53.9%
(Table 2; Fig. 2). Core area overlap between the rainy
and dry season did not vary with forest type (p = 0.824,
F(2.3) = 0.214, SE = 0.072) or forest disturbance
(p = 0.617, F(1.4) = 0.343, residual SE < 0.091).
Daily andseasonal movement rates
Our top model (Table4) indicated that seasonal movement
rates varied as a function of season (Sum Squares = 0.405,
95% CI [0.13, 0.65], F(1,10) = 11.27, p = 0.007, residual
S.E. = 0.04), with higher rates in the rainy season (rainy
season: 83.47 m/h; dry season: 56.70 m/h; Fig. 3; Addi-
tional file1: TableS1). When investigating daily movement
rates, our LMM analysis supported our seasonal move-
ment results, as the top model included season; however,
there was not support for effects of forest type or for-
est disturbance (β = 0.36, 95% CI [0.11, 0.60]; p = 0.019;
Table4; Additional file1: TableS2).
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Page 8 of 16
Semeletal. Movement Ecology (2022) 10:20
Habitat selection
We found that lemur habitat selection varied between
humid, moderate, and dry forest types as indicated by
AICc (Table5). We also found that selection by lemurs
varied between the wet and dry season, within forest
types, as indicated by AICc (Table 6). Given selection
varied by forest type and season, we elected to make
inferences on selection by forest type and by season. is
necessitated we change our models from GLMMs to
generalized linear models (GLMs) wherein we dropped
the group-specific (forest type and disturbance) random
intercept term given our final models retained only two
groups [89]. Tests for overdispersion and explanatory
power raised no concern (Additional file1: Tables S3 and
S4).
We found that groups in dry deciduous forests selected
locations with greater crown volume in the dry season
(β = 1.22, S .E. ± 0.11, p < 0.001). During the rainy season,
groups in dry forest selected locations with greater crown
volume (β = 1.04, S.E. ± 0.12, p < 0.001) and greater tree
basal area (β = 2.89, S.E. ± 0.73, p < 0.001), and avoided
habitat closer to villages (β = 3.06, S.E. ± 0.74, p < 0.001)
and roads (β = 2.42, S.E. ± 0.50, p < 0.001; Fig.4).
Lemur groups in moderate evergreen forests
selected locations with greater crown volume (β = 0.52,
S.E. ± 0.07, p < 0.001), greater tree basal area (β = 0.35,
S.E. ± 0.17, p = 0.03), and locations farther from vil-
lages (β = 1.30, S.E. ± 0.32, p < 0.001) in the dry season.
In the rainy season, groups selected feeding locations
with greater tree crown volume (β = 1.24, S.E . ± 0.07,
p < 0.001) and greater tree basal area (β = 0.55, S.E. ± 0.19,
p = 0.003) and avoided habitats closer to villages
(β = 1.91, S.E . ± 0.38, p < 0.001; Fig.4).
Finally, we found that lemur groups in the humid
forests selected feeding locations characterized with
greater crown volume (β = 0.98, S.E . ± 0.07, p < 0.001),
closer to villages (β = -0.76, S.E . ± 0.30, p = 0.01),
and closer to the forest edge (β = − 1.04, S.E. ± 0.17,
p < 0.001), and avoided locations near roads (β = 2.79,
S.E. ± 0.93, p = 0.003) in the dry season. In the rainy
season groups in humid forests selected locations with
greater tree basal area (β = 0.085, S.E. ± 0.04, p = 0.049)
Table 2 Data summary of six golden-crowned sifaka (Propithecus tattersalli) groups followed in different forest types (dry, moderate,
and humid) in three forest fragments (Solaniampilana, Bekaraoka, Binara) of two levels of forest disturbance (interior or edge) in the
Loky-Manambato Protected Area in northeastern Madagascar
The number of consecutive follow days, the number of GPS locations recorded, home range size (hectares), and core area size (hectares) are indicated for both the dry
(June–August 2019) and rainy (February–April 2019) seasons. Percent core area overlap between seasons also is included
Lemur group ID Number of follow days Number of GPS
locations Home range (ha) Core area (ha) Core Area
(% overlap)
Dry Rainy Dry Rainy Dry Rainy Dry Rainy
Dry-interior 9 7 285 206 6.04 7.95 0.88 1.91 16.7%
Dry-edge 8 7 270 216 8.19 31.6 0.89 2.62 51.2%
Moderate-interior 8 9 266 334 2.93 9.16 0.63 1.87 41.0%
Moderate-edge 8 8 299 269 2.78 4.83 0.57 0.78 16.3%
Humid-interior 8 9 282 320 3.69 25.1 0.68 1.71 32.0%
Humid-edge 9 8 290 278 12.5 11.1 1.18 1.90 53.9%
Table 3 Linear mixed effects models (LMMs) to explain core area
size and home range size of golden-crowned sifaka (Propithecus
tattersalli) groups in the Loky-Manambato Protected Area in
northeastern Madagascar during the dry (June–August 2019)
and rainy (February-April 2019) seasons
Season, disturbance, and forest type were included in the model. Columns
indicate the number of parameters (K), log-likelihood (LL), the relative dierence
in AICc values compared to the top-ranked model (ΔAICc), and the AICc model
weights (W) of the model-selection procedure
Model K LL AICc ΔAICc W
Core area size
Season 1 48.407 − 87.8 0.00 0.816
Disturbance + season 2 48.484 − 83.3 4.56 0.083
Null 0 43.720 − 82.1 5.71 0.047
Forest type + season 3 50.968 − 81.9 5.88 0.043
Disturbance 1 43.755 − 78.5 9.30 0.008
Forest type 2 44.759 − 75.8 12.01 0.002
Forest type + season + disturbance 4 51.086 − 73.4 14.44 0.001
Forest type + disturbance 3 44.801 − 69.6 18.21 0.000
Home range size
Null 0 13.999 − 22.7 0.00 0.465
Season 1 15.398 − 21.8 0.87 0.301
Disturbance 1 14.558 − 20.1 2.55 0.130
Disturbance + season 2 16.113 − 18.5 4.15 0.058
Forest type 2 15.538 − 17.4 5.30 0.033
Forest type + season 3 17.417 − 14.8 7.83 0.009
Forest type + disturbance 3 16.271 − 12.5 10.12 0.003
Forest type + disturbance + season 4 18.443 − 8.1 14.58 0.000
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 9 of 16
Semeletal. Movement Ecology (2022) 10:20
and greater crown volume (β = 1.34, S.E. ± 0.06,
p < 0.001) that were closer to villages (β = -1.28,
S.E. ± 0.19, p < 0.001), and forest edges (β = − 0.24,
S.E. ± 0.05, p < 0.001), and avoided habitats near roads
(β = 3.26, S.E . ± 0.73, p < 0.001). While the effects of
crown volume, villages, forest edges and roads were
the same across seasons, these effects were stronger in
the rainy season (Fig.4).
Fig. 2 Maps of the Brownian Bridge utilization distributions depicting core area use for golden-crowned sifaka (Propithecus tattersalli) groups in
the Loky-Manambato Protected Area of northeastern Madagascar during the dry (June–August 2019; dark gray) and rainy (February-April 2019;
light gray) seasons. Overlapping areas were occupied during both seasons. The six boxes display the seasonal home ranges for all six lemur groups
followed. Columns indicate forest disturbance classification (interior or edge) and rows indicate the occupied forest type (dry, moderate, or humid).
Solid lines correspond to the interior and the hashed lines correspond to the edge in the inset map of each site
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Page 10 of 16
Semeletal. Movement Ecology (2022) 10:20
Discussion
ere are three primary results from our study. First,
golden-crowned sifaka (Propithecus tattersalli) move-
ment rates are greater in the rainy season and in more
humid forests. Second, golden-crowned sifaka core
area size is impacted by season, with larger core areas
used in the rainy season. ird, golden-crowned sifa-
kas select foraging locations where the largest trees
in their home range are located. Similarly, we also
detected variation in behavioral responses to villages,
road networks, and the forest edge. Golden-crowned
sifaka groups in humid and dry deciduous forest frag-
ments specifically avoided foraging locations near road
networks in the rainy season, while lemurs in the mod-
erate evergreen forest did not select or avoid locations
near road networks. In sum, groups of golden-crowned
sifaka showed marked variation in behavioral responses
to human disturbance, but for all groups, higher-use
zones were characterized by locations having larger
trees. us, season, forest type, and disturbance all
have effects on golden-crowned sifaka space use and
ranging behavior.
Across seasons and regardless of forest type or distur-
bance, golden-crowned sifaka group daily movement
rates shifted, with groups moving farther per unit time
in the rainy season. is contrasts with previous studies
on Milne-Edwards’ sifaka groups that found no seasonal
effects on distance moved per day (i.e., daily path length)
[41]. us, there exists some degree of variability among
sifaka species. Movement rates in golden-crowned sifaka
groups were also closely linked to home range size in that
as home range size increased in the rainy season, so did
the average distance moved per hour. is finding is con-
sistent with other studies of highly mobile mammals that
found that movement rates and resource availability deter-
mined home range size of white-tailed deer (Odocoileus
virginianus) and Iberian ibex (Capra pyrenaica) [90, 91].
Golden-crowned sifaka group home range sizes var-
ied between 3 and 32 ha. ese home range sizes were
smaller than those of diademed sifaka groups in Mada-
gascar’s eastern humid forests, which range from 19 to
79ha [92], but were larger than those of Verreaux’s sifaka
groups in Madagascar’s southern dry forests, which have
Table 4 Competing models to explain seasonal and daily movement rates of golden-crowned sifaka (Propithecus tattersalli) groups in
the Loky-Manambato Protected Area in northeastern Madagascar during the dry (June–August 2019) and rainy (February–April 2019)
seasons
Season, disturbance, forest type, and all interactions (*) were included in the model. Columns indicate the number of parameters in the model (K), the log-likelihood
(LL), the relative dierence in AICc values compared to the top-ranked model (ΔAICc), and the AIC model weights (W) of the model-selection procedure
Model K LL AICc ΔAICc W
Seasonal movement rates
Season 1 3.382 2.2 0.00 0.733
Disturbance + season 2 4.394 4.9 2.69 0.191
Null 0 − 1.145 7.6 5.39 0.050
Disturbance 1 − 0.691 10.4 8.15 0.012
Forest type + season 2 4.779 10.4 8.21 0.012
Forest type 2 − 0.529 14.8 12.54 0.001
Forest type + season + disturbance 4 6.086 16.6 14.39 0.001
Forest type + disturbance 3 − 0.023 20.0 17.81 0.000
Forest type + season + forest type*season 5 6.158 29.7 27.45 0.000
Forest type + disturbance + season + forest
type*season 6 7.856 48.3 46.05 0.000
Daily movement rates
Season 1 − 27.381 63.3 0.00 0.586
Null 0 − 29.393 65.1 1.82 0.236
Disturbance + season 2 − 28.186 67.1 3.87 0.085
Disturbance 1 − 30.082 68.7 5.40 0.039
Forest type + season 2 − 28.022 69.1 5.87 0.031
Forest type 1 − 30.101 71.0 7.70 0.012
Foresttype + season + disturbance 3 − 28.845 73.2 9.89 0.004
Forest type + season + forest type*season 4 − 27.815 73.6 10.28 0.003
Forest type + disturbance 2 − 30.777 74.6 11.38 0.002
Forest type*season + disturbance 5 − 28.634 77.7 14.43 0.000
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Semeletal. Movement Ecology (2022) 10:20
home range sizes ranging from 5 to 10ha [93]. Similar
to this trend, mouse lemurs (Microcebus spp) inhabiting
western dry forests were able to maintain higher popula-
tion densities than mouse lemur species inhabiting east-
ern humid forests [94]. Contrary to previous findings,
Fig. 3 Seasonal movement rates (meters/hour) of golden-crowned sifaka (Propithecus tattersalli) groups in the Loky-Manambato Protected Area
in northeastern Madagascar. Data was collected during the dry (June–August 2019) and rainy (February-April 2019) seasons using relocation data
collected every 15 min. The step length (e.g., the distance between sequential locations) was divided by the time elapsed between each step to
calculate speed for each lemur group. Black lines correspond to 95% confidence intervals
Table 5 Generalized linear models (GLMs) of golden-crowned
sifakas (Propithecus tattersalli) depicting differences in foraging
tree selection among lemurs occupying different forest types
in the Loky-Manambato Protected Area in northeastern
Madagascar during the dry (June–August 2019) and the rainy
(February–April 2019) seasons
Columns indicate the number of parameters (K), the relative dierence in AICc
values compared to the top ranked model (ΔAICc), the AICc weights (W), and
the log-likelihood (LL) of the model-selection procedure examining foraging
tree selection of lemurs based on occupied forest type (humid, moderate, and
dry). CV: Crown Volume, TBA: Tree basal area, V: Distance to village, R: Distance
to roads, F: Distance to forest edge, FT: Forest type. Based on the models, forest
types could not be grouped and were parsed to make assumptions
K AICc ΔAICc W LL
(CV + TBA + V + R + F)*FT 19 11,353.62 0.00 1.00 − 5657.81
CV + TBA + V + R + F 7 11,425.18 71.56 0.00 − 5705.59
Table 6 Generalized linear models (GLMs) of golden-crowned
sifakas (Propithecus tattersalli) foraging tree selection based on
occupied forest type in the Loky-Manambato Protected Area in
northeastern Madagascar during the dry (June–August 2019)
and rainy (February–April 2019) seasons
Columns indicate the number of parameters (K), the relative dierence in AICc
values compared to the top ranked model (ΔAICc), the AICc weights (W), and
the log-likelihood (LL) of the model-selection procedure examining foraging
tree selection of lemurs based on occupied forest type (dry, moderate, and
humid). CV: Crown Volume, TBA: Tree basal area, V: Distance to village, R:
Distance to roads, F: Distance to forest edge, FT: Forest type
K AICc ΔAICc W LL
Dry forest
(CV + TBA + V + R + F)*Season 13 4085.42 0.00 1.00 − 2029.71
CV + TBA + V + R + F 7 4105.11 19.7 0.00 − 2045.56
Moderate forest
(CV + TBA + V + R + F)*Season 13 2944.24 0.00 1.00 − 1459.12
CV + TBA + V + R + F 7 3043.27 99.04 0.00 − 1514.64
Humid forest
(CV + TBA + V + R + F)*Season 13 4158.31 0.00 1.00 − 2066.15
CV + TBA + V + R + F 7 4206.98 48.68 0.00 − 2096.49
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Semeletal. Movement Ecology (2022) 10:20
and our predictions, we found that golden-crowned
sifaka groups in dry deciduous and humid forests did
not occupy significantly larger home range or core area
sizes compared to groups living in moderate evergreen
forest fragments. is finding was unexpected because
golden-crowned sifaka densities were substantially larger
in moderate forest fragments compared to dry deciduous
and humid forest fragments [59]. In sum, our study was
the first determining that the same species of sifaka can
inhabit drastically different forest types and display great
variation in home range size. However, while animal den-
sities have implications for spatial ecology [95], golden-
crowned sifaka densities did not appear to predict home
range and core areas sizes [59].
Our prediction that golden-crowned sifaka home range
sizes would vary between the rainy season and the dry
season was partially supported. While home range sizes
were not significantly different between seasons, core
area size was statistically larger for golden-crowned sifaka
groups in the rainy season compared to the same groups’
core area range sizes in the dry season. Similar to findings
of Milne-Edwards’ sifaka, we found that golden-crowned
sifaka maintained similar home range locations in both
seasons, but displayed considerable seasonal shifts in
core area locations [41]. is difference was likely due
to the non-uniform and seasonal variation in resource
distribution that influenced how golden-crowned sifaka
distributed their space use to forage efficiently [96]. Sur-
prisingly, the degree of core area overlap we observed did
not vary based on the forest type or forest disturbance
level occupied.
We predicted that golden-crowned sifaka groups in
more degraded, edge, habitats would occupy larger home
ranges and have larger core areas than those in interior
forests; however, our data did not support that assump-
tion. Previous studies have demonstrated varying effects
of disturbance on home range size of eastern sifaka spe-
cies in rainforest habitats. For instance, diademed sifaka
living along forest edges occupied significantly smaller
home range sizes than conspecifics in interior, undis-
turbed forests [40], as is consistent with many other
mammalian species [97]. However, Milne-Edwards’
sifaka in disturbed (logged) forests maintained larger
home range sizes than those in undisturbed forests [41].
Unfortunately, the majority of lemur studies (87%) exam-
ining the effects of forest disturbance on lemur health,
genetics, biodiversity, and behavior were conducted
in the humid forests of eastern Madagascar [98]. Fur-
ther, lemur responses to habitat edges in dry forest are
often highly variable, with groups avoiding, selecting, or
Fig. 4 Selection coefficient plot for golden-crowned sifakas (Propithecus tattersalli) in the Loky-Manambato Protected Area in northeastern
Madagascar in the dry (June–August 2019) and rainy (February-April 2019) seasons within three forest types (dry, moderate, and wet). This
coefficient plot displays beta estimates for tree basal area and tree crown volume and distance to forest edge, roads, and villages. Blue points
represent habitat selection during the rainy season and red points represent habitat selection during the dry season. Solid lines above and below
each point represent the 95% confidence intervals around each beta estimate
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Page 13 of 16
Semeletal. Movement Ecology (2022) 10:20
demonstrating no response in regards to feeding along
forest edges [98, 99]. As a result, further investigation
of home ranges of golden-crowned sifaka and other dry
forest lemurs are needed to understand how increasing
anthropogenic changes are influencing lemur ecology
and conservation.
While we expected golden-crowned sifaka groups to
avoid villages and roads, we found a mixed response. In
some forest types and seasons, sifaka groups selected
for foraging locations near roads, while in other forest
types and seasons sifaka groups avoided foraging loca-
tions near roads. e same mixed response was found in
regard to foraging locations near villages. Other studies
have found similar mixed responses to anthropogenic
influences [100, 101]. Additionally, the national road that
bisects the global range of golden-crowned sifaka is cur-
rently being paved to improve access to mineral reserves
and transportation through the region. While infra-
structure improvement will likely provide much needed
improvement to local economies, our results demon-
strate that even narrow road networks can restrict suit-
able sifaka habitat. Improved road access also is likely
to increase resource extraction within the region (e.g.,
selective logging of hardwoods and gold mining), with
negative impacts expected for sifakas [38]. e negative
impacts of road networks are well documented for mam-
malian species. For example, elk (Cervus canadensis) and
caribou (Rangifer tarandus) tend to avoid road crossings
and seek cover when in close proximity to road networks
[102]. Road expansion and paving also increases the
prevalence of vehicle collisions with wildlife (e.g., Asiatic
cheetah (Acinonyx jubatus venaticus) [103] and Florida
panther (Puma concolor coryi)) [104]. Importantly, even
low vehicle traffic (0–30 vehicles/12h) caused wolverines
(Gulo gulo) to alter their movement patterns and to avoid
areas with road networks [105]. Consequently, increas-
ing human activity and road prevalence is likely to impact
foraging and space use behavior of wildlife species, with
potentially disastrous consequences for already crucially
endangered golden-crowned sifaka.
Conclusions
Limitations andfuture directions
Although our data revealed various patterns in golden-
crowned sifaka movement and foraging patterns, we
could only establish general conclusions due to our lim-
ited monitoring efforts (15–18days/year for each group)
and small sample size (six sifaka groups). Additionally,
due to our rotation-based field schedule, we were only
able to follow one group of sifaka at a time. Future work
with more continuous monitoring, preferably with the
use of remote tracking devices, would enable us to bet-
ter tease apart the relationships between season, forest
type, anthropogenic factors, and movement, as well as
to increase model robustness. Second, there were limi-
tations regarding the covariates used in the RSF. Specifi-
cally, we assumed that all village disturbance was equal.
However, each village differed in population size, degree
of infrastructure, and distance from the forest edge. As
a result, some villages could have had greater anthropo-
genic influences than others. ird, we could not claim
that human disturbance was directly related to golden-
crowned sifaka groups selecting for the largest trees
within their respective home ranges. Feeding on the
largest trees could have been related to increased food
availability and security, rather than human driven fac-
tors. Fourth, we used simple categories (e.g., ‘rainy’ and
‘dry’) to reflect seasons, forest types, and disturbance lev-
els. While this uncovered broad patterns, more sophis-
ticated resource measurements, such as precipitation
amounts or Landsat imagery, would improve the context
within which we interpret sifaka movement and resource
selection.
Conservation implications
Our study illustrates the complex anthropogenic and
ecological processes that influence movement behavior
of golden-crowned sifaka groups. We found evidence
that human settlements and road networks play an
important role in shaping sifaka foraging and ranging
behavior. Additionally, ecological factors such as sea-
son are drivers of home range size and space use in this
species. Our study enforces the importance of study-
ing primate groups in both the rainy and dry seasons
to ensure that conservation efforts meet the full range
of a species’ movement, home range size, and resource
needs. By understanding how forest type influences
golden-crowned sifaka movement and foraging behav-
ior, conservation management plans can be appro-
priately crafted to the unique forest types throughout
the Loky-Manambato Protected Area (humid, moder-
ate evergreen, dry deciduous, littoral, etc.), rather than
the region as a whole. Our findings can also be used
to inform Malagasy infrastructure and road develop-
ment plans by working with local conservation NGOs,
government officials, and construction teams to limit
construction nearby lemur home ranges that are most
impacted by human activity. We would advise that the
national road not be re-routed towards Binara, the
humid forest fragment, due to the strong avoidance
lemurs display towards existing road networks and
the increased movement of lemurs within this forest
fragment. We detected the least avoidance of anthro-
pogenic activity for lemurs in the moderate evergreen
forest type, suggesting they are more resilient to the
negative effects of human infrastructure. Overall, as
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Page 14 of 16
Semeletal. Movement Ecology (2022) 10:20
anthropogenic disturbance continues to alter habitat
structure throughout Madagascar, a deeper knowledge
of how fragmentation, habitat loss, and infrastructure
development influence golden-crowned sifaka space
use, density, and population health will be essential for
wildlife managers to make well informed decisions that
improve conservation plans for at-risk species.
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s40462- 022- 00320-x.
Additional le1. TableS1. Mean seasonal speed for golden-crowned
sifaka (Propithecus tattersalli) groups. TableS2. Mean daily speed for
golden-crowned sifaka (Propithecus tattersalli) groups. TableS3. GLM of
golden-crowned sifaka (Propithecus tattersalli) foraging tree selection.
TableS4. Formulation of the resource selection GLM of golden-crowned
sifaka (Propithecus tattersalli) groups.
Acknowledgements
We would like to sincerely thank Amidou Souleimany, Aylett Lipford, Giovanni
Walters, our local guides (Amadou, Andre, Augiste, Bezily, Christone, Da,
Edward, Ishmael, Jaojoby, John, Justin, Lahimena, Laurent, Lucien, Mamoud,
Michelle, Moratombo, Patrice, Pierre, Seraphin, Sylvano, Theodore, Thierry,
Zoky), cooking staff (Ayati, Fatomia, Francia, Jao Fera, Nicole), and porters,
Fanamby (Serge Rajaobelina, Richelin, Narcisse, Tiana Andriamanana, Sylvano
Tsialazo), and Madagascar Institute for the Conservation of Tropical Environ-
ments (MICET; Benjamin Andriamihaja, Benji Randrianambinina, Claude, Nary)
for their assistance with data collection and logistics.
Author contributions
MS and IM designed the study. MS, BS, and TR conducted the fieldwork. MS,
HA, and MC conducted the coding and data analyses. MS wrote the first draft
of the manuscript and all authors contributed substantially to revisions. All
authors read and approved the final manuscript.
Funding
We acknowledge funding from the Rufford Foundation and the National
Science Foundation GRFP (DGE 1651272). Opinions, findings, conclusions, or
recommendations expressed are those of the authors and do not necessarily
reflect the views of the NSF.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from
the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
This research was conducted with permission from the Ministry of For-
eign Affairs of Madagascar, Madagascar National Parks, the Ministry of the
Environment, Forests, and Tourism (MEFT), and Madagascar Institute for the
Conservation of Tropical Environments (MICET). MICET was also instrumental
in permit acquisition (N015/19/MEEF/SG/DGF/DSAP/SCB) and overall research
coordination. Our animal follow methods were approved by the Virginia Tech
Institutional Animal Care and Use Committee (IACUC) office (permit #17-127).
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061, USA.
2 Department of Fish & Wildlife Conservation, Virginia Tech, Blacksburg, VA
24061, USA. 3 Caesar Kleberg Wildlife Research Institute, Texas A&M University-
Kingsville, Kingsville, TX 78363, USA. 4 Département Zoologie et Biodiversité
Animale, Université d’Antananarivo, 566 Analamanga, 101 Antananarivo, BP,
Madagascar.
Received: 20 October 2021 Accepted: 4 April 2022
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