Population densities of curassows, guans, and chachalacas (Cracidae): Effects of body size, habitat, season, and hunting

Abstract

Understanding the factors that determine population densities is critical for conserving viable populations of threatened species. Half of the 50 species in the family Cracidae have experienced population declines. We conducted a literature review to explore the relations of population densities of cracids with body size, habitat, season, and hunting. We compiled 103 density data points for 27 species in 37 localities from Mexico to Argentina. There was no correlation between body mass and density. The larger cracines tended to have lower densities than penelopines, but densities in both subfamilies spanned a similar range of values. Intraspecific and interspecific densities varied among sites over 2 orders of magnitude (1-100 birds km-2). Some cracids exhibited plasticity in habitat use, with variable densities among habitats. There is evidence that some species performed local movements related to seasonality in rainfall or resource availability, leading to aggregations around water sources during the dry season or around seasonally abundant food sources. Hunting had a negative effect on population densities, but in some cases low to moderate hunting did not cause a decrease in density in comparison to nonhunted sites. Despite having similar ecologies, densities of cracid species are very variable, and each population seems to respond idiosyncratically to local factors, which requires care if data are extrapolated across populations or species. Future studies that aim to characterize cracid populations for conservation purposes should take into account possible intraspecific density variations related to seasonality, local movements, and habitat heterogeneity.

Full text

Volume 118, 2016, pp. 24–32
DOI: 10.1650/CONDOR-15-51.1
COMMENTARY
Population densities of curassows, guans, and chachalacas (Cracidae):
Effects of body size, habitat, season, and hunting
Gustavo H. Kattan,
1
* Marcia C. Mu ˜
noz,
2
and David W. Kikuchi
3
1
Departamento de Ciencias Naturales y Matema
´ticas, Pontificia Universidad Javeriana Seccional Cali, Cali, Colombia
2
Biodiversity and Climate Research Centre (BiK-F) and Senckenberg Gesellschaft f¨
ur Naturforschung, Frankfurt am Main, Germany
3
Department of Biology, Carleton University, Ottawa, Ontario, Canada
* Corresponding author: gustavokattan@gmail.com
Submitted March 31, 2015; Accepted September 8, 2015; Published November 11, 2015
ABSTRACT
Understanding the factors that determine population densities is critical for conserving viable populations of
threatened species. Half of the 50 species in the family Cracidae have experienced population declines. We conducted
a literature review to explore the relations of population densities of cracids with body size, habitat, season, and
hunting. We compiled 103 density data points for 27 species in 37 localities from Mexico to Argentina. There was no
correlation between body mass and density. The larger cracines tended to have lower densities than penelopines, but
densities in both subfamilies spanned a similar range of values. Intraspecific and interspecific densities varied among
sites over 2 orders of magnitude (1–100 birds km
2
). Some cracids exhibited plasticity in habitat use, with variable
densities among habitats. There is evidence that some species performed local movements related to seasonality in
rainfall or resource availability, leading to aggregations around water sources during the dry season or around
seasonally abundant food sources. Hunting had a negative effect on population densities, but in some cases low to
moderate hunting did not cause a decrease in density in comparison to nonhunted sites. Despite having similar
ecologies, densities of cracid species are very variable, and each population seems to respond idiosyncratically to local
factors, which requires care if data are extrapolated across populations or species. Future studies that aim to
characterize cracid populations for conservation purposes should take into account possible intraspecific density
variations related to seasonality, local movements, and habitat heterogeneity.
Keywords: Cracidae, habitat use, hunting, population density, seasonality
Densidades poblacionales de paujiles, pavas y guach aracas: Efectos del tama ˜
no corporal, el ha
´bitat, la
estacionalidad y la cacer´
ıa
RESUMEN
El estudio de los factores que determinan las densidades poblacionales, es cr´
ıtico para la conservaci ´
on de especies
amenazadas. La mitad de las 50 especies de la familia Cracidae esta
´n amenazadas. Hicimos una revisi ´
on de literatura
para evaluar las relaciones entre las densidades poblacionales de Cracidae y el tama ˜
no corporal, el ha
´bitat, la
estacionalidad y la cacer´
ıa. Obtuvimos 103 datos de densidades para 27 especies en 37 localidades entre M´
exico y
Argentina. No encontramos correlaci ´
on entre masa corporal y densidad. Las especies de Cracinae, que son ma
´s
grandes, tienden a tener densidades ma
´s bajas que Penelopinae, pero en ambas subfamilias las densidades abarcan un
intervalo similar de valores. Las densidades intra e interespec´
ıficas var´
ıan geogra
´ficamente en dos ´
ordenes de
magnitud (1 a 100 individuos km
2
). Algunas especies tienen plasticidad en el uso de ha
´bitat y sus densidades var´
ıan
entre ha
´bitats. Hay evidencia de que algunas especies hacen movimientos locales relacionados con la estacionalidad
en la precipitaci ´
on o disponibilidad de recursos; los individuos se agregan alrededor de fuentes de agua durante la
estaci ´
on seca o alrededor de fuentes abundantes de alimento. La cacer´
ıa tiene un efecto negativo sobre las densidades
poblacionales, pero en algunos casos la cacer´
ıa baja a moderada no causa una disminuci ´
on en las densidades, en
comparaci ´
on con sitios sin cacer´
ıa. A pesar de tener ha
´bitos similares, las densidades de las especies de Cracidae son
muy variables y cada poblaci ´
on parece responder de manera idiosincra
´tica a los factores locales. Se requiere
precauci ´
on si se van a extrapolar datos entre poblaciones o especies. Los estudios futuros que busquen caracterizar las
poblaciones de Cracidae con prop ´
ositos de conservaci ´
on, deben tener en cuenta las posibles variaciones relacionadas
con estacionalidad, movimientos locales y heterogeneidad de ha
´bitat.
Palabras clave: Cracidae, uso de ha
´bitat, la caza, la densidad de poblaci ´
on, la estacionalidad
Q2016 Cooper Ornithological Society. ISSN 0004-8038, electronic ISSN 1938-5129
Direct all requests to reproduce journal content to the Central Ornithology Publication Office at aoucospubs@gmail.com

INTRODUCTION
Cracidae is a family of galliform birds endemic to the
Neotropics (del Hoyo et al. 1994). The family contains 50
species, with their center of diversity in Colombia and
Ecuador. Cracids are classified into 2 subfamilies. The
Cracinae (curassows: 14 species) are large, mostly terres-
trial birds, whereas the Penelopinae (guans and chacha-
lacas: 36 species) are smaller and arboreal. Cracids are
largely frugivorous but have broad diets that include
animal matter and other foods (Mu ˜
noz and Kattan 2007).
This is one of the most threatened families of birds, with
24 species listed in the Threatened, Endangered, or
Critically Endangered categories (Brooks 2006). The major
causes of population declines in these birds are habitat loss
and hunting.
Developing spatially explicit conservation plans and
preserving viable populations of cracids requires under-
standing their patterns of distribution and abundance and
the processes that influence those patterns. Density is an
important parameter that influences population dynamics
through density-dependent vital rates. For example, at low
densities, reproductive rates may be reduced as a result of
Allee effects (inverse density dependence of per capita
growth rate at low densities; Courchamp et al. 1999). Local
population densities have been extrapolated to estimate
abundance in a larger area or across the geographic range
of a species, as a basis to estimate threat status (Renjifo et
al. 2014). However, this requires caution because of spatial
heterogeneity in density related to habitat structure and
other local factors (Hansen et al. 1995). If local densities
are highly variable, abundance estimates will be unreliable.
Many factors may influence population density and the
spatial dispersion of individuals. Two of the main factors
are body size and trophic level. There is a general negative
correlation between body size and population density
(Gaston and Blackburn 2000). However, most of the
variation in bird population density that is explained by
body size and trophic level occurs at the family and order
taxonomic hierarchies, which suggests that these traits are
phylogenetically conserved (McGill 2008).
Animal species normally exhibit large variations in
abundance of populations across their ranges, with small
numbers in most localities and a few abundance hotspots
(Brown et al. 1995, Lundberg et al. 2000). One half of the
variance in bird abundance (controlling for other factors,
such as taxonomic affiliation and trophic level) is due to
spatial variation within species (McGill 2008). Part of this
variation is related to a spatial cline of abundance from the
center to the periphery of the geographic range, which may
result from source–sink dynamics (Curnutt et al. 1996).
However, the generality of this clinal pattern has been
challenged, because densities show much more complex
spatial patterns (Sagarin et al. 2006). At local scales,
population densities may vary according to habitat
suitability in heterogeneous landscapes, which, in turn,
may be related to habitat structure or distribution and
abundance of resources (Boyce and McDonald 1999).
Density, however, is not a reliable indicator of habitat
suitability, because numerous ecological factors may lead
birds to settle in poor habitats (Johnson 2007).
Animals may also move in a landscape in response to
temporal changes in resource distribution and abundance
in different habitats, which may be related to seasonal or
aseasonal fluctuations in climate. For example, variations
in the availability of food resources are correlated with the
local abundance of forest birds (Levey 1988, Poulin et al.
1992), and locally abundant resources may lead to
temporary aggregations of individuals (Mu ˜
noz et al.
2007). In tropical mountains, birds may perform seasonal
elevational movements in response to variations in food
availability or climate (Boyle 2010, 2011).
Here, we use a literature review to explore how
population density of cracids is related to body size,
habitat heterogeneity within a locality, season, and
hunting. We expected cracines to exhibit lower population
densities than penelopines because of their larger sizes. In
particular, chachalacas (Ortalis spp.) comprise a group of
small penelopines that tolerate disturbed habitats (del
Hoyo et al. 1994), so we expected them to be the most
abundant. Curassows are considered sensitive to habitat
disturbance and hunting (del Hoyo et al. 1994), and we
expected these birds to be sedentary and restricted to
mature forest. We also expected population densities of
cracids to vary in relation to seasonality in rainfall and
resource availability. Finally, cracids should be strongly
affected by hunting.
METHODS
We searched the scientific literature to build a database on
population densities of cracids. We used the keywords
‘‘cracid’’ and ‘‘bird population density’’ to find references in
Google Scholar, and looked for citations of these papers as
well as papers that they cited. We found 32 studies that
reported a total of 103 density data points. Studies
encompassed 27 species (10 Cracinae, 17 Penelopinae)
and 37 localities distributed from Mexico to Argentina
(Table 1).
The 32 studies used 4 main methods to estimate density.
Sixteen studies used distance sampling. Birds were
detected along transects, and the perpendicular distance
to the transect was estimated. Then, using the program
Distance (Thomas et al. 2009), data were used to generate
detection probability as a function of distance to the
transect and then to estimate density. In strip transects (10
studies), a detection distance determined by the observer
was used to define the area of the sampled strip (width 3
The Condor: Ornithological Applications 118:24–32, Q2016 Cooper Ornithological Society
G. H. Kattan, M. C. Mu ˜
noz, and D. W. Kikuchi Cracid population densities 25

length), and density was calculated as the number of
individuals detected divided by that area. Point counts
were used in 2 studies. A stationary observer detected
birds within a circle and used the maximum detection
distance to calculate the area sampled. Finally, 3 studies
estimated densities by spot mapping birds within a defined
study area.
We analyzed the effect of survey method (distance
sampling, strip transect, point counts, and spot mapping)
on the natural logarithm of population densities by using a
linear mixed model, which included species as a random
effect to account for potential taxonomic differences in the
methods used. We performed our analyses in R version 3.2
(R Development Core Team 2014). We did not find any
significant differences between densities estimated by the
various sampling methods (likelihood ratio test [LRT]; v2¼
1.18, df ¼3, P¼0.75), although our power to detect an
effect of the latter 2 methods was low because of the small
number of cases. In subsequent analyses we ignored survey
method.
To calculate correlations between body mass and
population density, we used only data obtained in the
birds’ main habitat type (i.e. undisturbed, nonfragmented
forest) and in the absence of hunting. This gave us 24
species for analysis. Often, several density values were
available for each species in 1 or more localities. Therefore,
in conducting a linear regression of ln(density) against
ln(mass), we included species as a random effect in the
model. We also used regression analysis with species as a
random effect, to test for differences between cracine and
penelopine densities.
Four studies reported density data of 6 species in
different habitats within a locality. The study designs,
localities, and habitats were very heterogeneous, which
precluded a quantitative analysis of how densities varied
with habitat. Therefore, we present those results in a
descriptive form.
To analyze the effect of hunting on population density,
we first used studies in which hunted and nonhunted
forests were paired together at the same site. Three
TABLE 1. Species in the family Cracidae for which population densities have been reported and countries where they were studied.
Species Country References
Subfamily Cracinae
Crax Alberti Colombia Rodr´
ıguez 2008
C. alector French Guiana Thiollay 1989, 1994
C. daubentoni Venezuela Silva and Strahl 1997, Strahl et al. 1997, Bertsch and Barreto 2008
C. fasciolata Brazil Desbiez and S˜
ao Bernardo 2011
C. globulosa Colombia, Brazil, Bolivia, Peru Alarc ´
on-Nieto and Palacios 2008, Haugaasen and Peres 2008,
Hill et al. 2008, Yahuarcani et al. 2009
C. mitu Peru Terborgh et al. 1990
C. rubra Guatemala, Mexico Mart´
ınez-Morales 1999, Eisermann 2004
Mitu tuberosa Peru, Brazil, Bolivia Torres 1997, Begazo and Bodmer 1998,
Haugaasen and Peres 2008, Hill et al. 2008, Barrio 2011
Nothocrax urumutum Peru Parker 2002
Pauxi pauxi Colombia, Venezuela Silva and Strahl 1997, Setina et al. 2012
Subfamily Penelopinae
Aburria aburri Colombia, Venezuela Nadachowski 1994, Silva and Strahl 1997, Rios et al. 2005
A. pipile Trinidad Hayes et al. 2009
Chamaepetes goudotii Colombia Londo ˜
no et al. 2007
Oreophasis derbianus Mexico Abundis-Santamar´
ıa and Gonza
´lez-Garc´
ıa 2007
Ortalis canicollis Paraguay, Bolivia Brooks 1997, Mamani 2001
O. guttata Peru, Brazil Torres 1997, Begazo and Bodmer 1998, Haugaasen and Peres 2008
O. ruficauda Venezuela Silva and Strahl 1997, Schmitz-Orn´
es 1999
Penelope argyrotis Venezuela Silva and Strahl 1997
P. barbata Ecuador Jacobs and Walker 1999
P. jacquacu Peru, Brazil Terborgh et al. 1990, Torres 1997, Begazo and Bodmer 1998,
Haugaasen and Peres 2008, Barrio 2011
P. marail French Guiana Thiollay 1994
P. montagnii Ecuador, Colombia Nadachowski 1994, Creswell et al. 1999
P. obscura Brazil Guix et al. 1997
P. perspicax Colombia Kattan et al. 2006, 2014
P. purpurascens Venezuela Silva and Strahl 1997
Pipile cumanensis Peru Terborgh et al. 1990, Torres 1997, Begazo and Bodmer 1998,
Barrio 2011
P. jacutinga Brazil Galetti et al. 1997, Guix et al. 1997
The Condor: Ornithological Applications 118:24–32, Q2016 Cooper Ornithological Society
26 Cracid population densities G. H. Kattan, M. C. Mu ˜
noz, and D. W. Kikuchi

studies presented comparative data (Table 2). Begazo and
Bodmer (1998) collected data from hunters at 3 sites
classified as ‘‘protected area,’’ ‘‘moderately hunted,’’ and
‘‘heavily hunted.’’ Thiollay (1989) classified 3 sites as no
‘‘hunting,’’ ‘‘near hunting area,’’ and ‘‘regularly hunted.’’
Mamani (2001) surveyed sites with subsistence hunting
and no hunting. Only Begazo and Bodmer (1998)
presented quantitative data on harvested birds, so we
used qualitative categories for analysis.
In addition to our paired hunting and no-hunting data,
we looked for an effect of hunting across our wider
datasetthatincludedunpairedsites.Todothis,we
modeled the natural logarithm of density as a function of
being in a hunted or nonhunted area, with ln(body mass)
included as a covariate. We included habitat type nested
within study site as a random effect to control for
variance in density across habitats and sites. We tested the
likelihood of this model against a model that did not
include hunting as a predictor, using the likelihood ratio
test.
RESULTS
Body masses of the 27 cracid species included in this
sample varied by an order of magnitude, between 400 and
4,000 g. Cracines were larger than penelopines, and with
the exception of Nothocrax urumutum (Cracinae), whose
body mass (1,250 g) was in the upper range of penelopine
body masses, there was no overlap between the 2
subfamilies.
In populations that had not experienced habitat
disturbance, fragmentation, or hunting, there was no
correlation between ln(mass) and ln(density) ( t
21
¼1.6,
P¼0.12; Figure 1). We found no significant differences
between cracine and penelopine densities (t
22
¼0.94, P¼
0.36). Mean density (6SE) was 8.9 67.4 birds km
2
for
cracines (n¼8 species) and 17.7 69.4 birds km
2
for
penelopines (n¼16 species). However, cracine densities in
general were ,20 birds km
2
, except for Crax daubentoni,
which reached densities of 40 birds km
2
. The smaller
cracine species covered a broad range of densities that
included the lowest values observed in this subfamily
(Figure 2). Penelopine densities varied between 1 and 42
birds km
2
, but Ortalis canicollis reached densities of 170
birds km
2
. Several penelopines had densities of ,10 birds
km
2
(Figure 2).
Intraspecific and interspecific cracid densities varied
geographically over 2 orders of magnitude (1–100 birds
km
2
; Figure 2). For species with .1 density estimate in
what seemed to be adequate habitat with no hunting, there
were large differences in densities among localities. In
particular, densities were highly intraspecifically and
interspecifically variable among guans in the genus
Penelope.DensitiesofPenelope barbata in montane
habitats (unprotected but undisturbed cloud forest) in
Ecuador ranged from 2 to 17 birds km
2
(Jacobs and
Walker 1999). Other montane species reached compara-
tively high densities. For example, densities of P. perspicax
ranged from 10 to 42 birds km
2
in several protected sites
in the Colombian Andes (Kattan et al. 2014). An
Amazonian species, P. jaquacu, had a low density in a
TABLE 2. Studies comparing population densities of cracids among sites with different intensities of hunting.
Species Region No hunting
Low–moderate
hunting
Heavy–regularly
hunted Reference
Crax alector French Guiana 8.37 1.38
a
0.39 Thiollay 1989
Mitu tuberosa Peruvian Amazon 1.65 2.08 0.02 Begazo and Bodmer 1998
Ortalis canicollis Bolivian Chaco
b
44.6 8.7 Mamani 2001
O. canicollis Bolivian Chaco
b
172.1 41.9 Mamani 2001
O. guttata Peruvian Amazon 3.28 3.6 5.95 Begazo and Bodmer 1998
Penelope jacquacu Peruvian Amazon 5.46 5.46 0.22 Begazo and Bodmer 1998
Pipile cumanensis Peruvian Amazon 6.79 9.37 0.44 Begazo and Bodmer 1998
a
Near hunting area (see text).
b
Two different habitats.
FIGURE 1. Logarithmic relationship between mean density and
body mass for 24 species of cracids. Data from undisturbed,
nonfragmented sites. Each distinct shape indicates data from a
unique species.
The Condor: Ornithological Applications 118:24–32, Q2016 Cooper Ornithological Society
G. H. Kattan, M. C. Mu ˜
noz, and D. W. Kikuchi Cracid population densities 27

protected area (Manu National Park, Peru, 2 birds km
2
;
Terborgh et al. 1990), although one study reported
densities of ~20 birds km
2
(Torres 1997). In another
Amazonian locality (Rio Pur´
us), densities of this species in
different habitats were 0.2–4.4 birds km
2
(Haugaasen and
Peres 2008).
We found data for 3 species of chachalacas. Two of them
(O. canicollis and O. ruficauda) exhibited the highest
densities in the family, but the third one (O. guttata) had
low densities (3.3 birds km
2
in a protected area; Begazo
and Bodmer 1998). Densities of chachalacas varied in
different habitats. For example, in the Chaco region of
Bolivia, densities of O. canicollis were 43higher in tall
riverine forest than in drier scrub vegetation (Mamani
2001). In Venezuela, densities of O. ruficauda were higher
in agricultural areas (with fruit plantation fields and
deciduous forest in adjacent hills) than in deciduous and
semideciduous forest in a protected area (Schmitz-Orn´
es
1999).
Density variations and movements among habitat types
have also been reported in other forest-dependent species
in both cracid subfamilies (Table 3). For example, Bertsch
and Barreto (2008) reported that in central Venezuela, C.
daubentoni inhabited heterogeneous landscapes compris-
ing gallery and dry forest, but also used forest borders,
hedges, and open area. Birds reached very high densities
during the dry season in seasonally dry forest and gallery
forest, which suggests aggregation around water sources.
In open savanna, which may be considered a marginal
habitat, densities were low in both seasons.
Another cracine, Mitu salvini,wasstudiedinthe
northwestern Colombian Amazon, where Parra et al.
(2001) followed a family group for 6 mo. The group had
a home range of 72 ha that included riparian, flooded,
open, and mature forest. The birds temporally shifted their
patterns of habitat use in response to changes in food
resources, mainly the availability of fruit in flooded and
mature forest.
Patterns of habitat use at the population level have been
reported for P. perspicax in the Colombian Andes (Kattan
et al. 2014). Densities varied, from 10–18 birds km
2
in
medium-sized (500–700 ha), isolated forest tracts to 42
birds km
2
in a continuous forest of several thousand
hectares. These guans also used secondary forest, early
regeneration, and ribbons of vegetation along streams,
where densities were 10–40 birds km
2
. At one site, guans
congregated at a Chinese ash (Fraxinus chinensis)
plantation, where they reached densities of 100 birds
km
2
(Kattan et al. 2006, Rios et al. 2008). Guans
aggregated in large numbers at the ash plantation and
fed on ash foliage during the period of low fruit availability
in the forest (Mu˜
noz et al. 2007).
Two cracines were surveyed on islands. On Cozumel
Island, Mexico, densities of C. rubra were very low (0.9
birds km
2
), and 60% of records were obtained ,250 m
TABLE 3. Summary of studies reporting population densities of cracids in different habitat types.
Species and
site/conditions Habitat and density (birds km
2
) Country Reference
Crax daubentoni Gallery forest Dry forest Savanna Venezuela Bertsch and Barreto 2008
Dry season 161 44 13
Wet season 40 28 8
Ortalis ruficauda Continuous forest Agricultural–forest Urban–forest Venezuela Schmitz-Orn ´
es 1999
38 56 20
Penelope perspicax Old-growth forest Second-growth forest Riparian forest Colombia Kattan et al. 2014
Barbas 18 11
Bremen 11 42 17
Terra firme forest Va
´rzea Igap´
o Brazil Haugaasen and Peres 2008
P. jacquacu 4 0.2 0.6
O. guttata 1.5 1
Mitu tuberosum 1.6 3 1
FIGURE 2. Relationship between body mass and density for
cracids. This graph includes all data points, so a species may be
represented by .1 point (n¼46 density data points, n¼24
species). Filled circles are penelopines, and open circles are
cracines.
The Condor: Ornithological Applications 118:24–32, Q2016 Cooper Ornithological Society
28 Cracid population densities G. H. Kattan, M. C. Mu ˜
noz, and D. W. Kikuchi

from a water source (Mart´
ınez-Morales 1999). By contrast,
on an island in the Caqueta River, Colombia, densities of C.
globulosa ranged from 11 birds km
2
in forest with a dense
understory to 19 birds km
2
in mature forest and 29 birds
km
2
in disturbed forest (Alarc´
on-Nieto and Palacios
2008). The density reported for this species in riparian
varzea in Bolivia was 3.4 birds km
2
(Hill et al. 2008).
Movements on a larger scale have been documented in P.
purpurascens and Chamaepetes unicolor in the Tilara
´n
mountains of Costa Rica (Chaves-Campos 2003), by
quantifying changes in abundance at different elevations.
Both species breed in lower montane rainforest at 1,400 m
and apparently move downslope to elevations of 800 m
(premontane rainforest), with P. purpurascens going as low as
400 m at the transition of tropical wet forest to premontane
forest. These movements coincided with a general pattern of
altitudinal migration for bird species at this site.
In our analysis of studies with paired data on hunting
(Table 2), we found a significant effect of hunting on
population density (LRT; v2¼11.13, df ¼2, P¼0.004).
Tukey’s HSD revealed that although there was no
difference between areas with no hunting and areas with
low hunting (z¼0.41, P¼0.91), areas with heavy hunting
had significantly lower population densities than areas
with no hunting (z¼4.24, P,0.001). Indeed, populations
in areas with low hunting pressure also had higher
densities than those in areas with heavy hunting pressure
(z¼3.33, P,0.002). In our analysis of the entire dataset
that included both paired and unpaired sites, we found that
hunting continued to have a significant negative effect on
ln(population density) (v
2
¼6.01, P¼0.014). Hunting of
some species may favor other species. In the study of
Begazo and Bodmer (1998), O. guttata was more abundant
in hunted areas, because it is little hunted compared with
the other 3 (larger) species.
DISCUSSION
We found no clear relationship between body size and
population density in Cracidae. Some of the small species
exhibited low densities, and a few of the large species had
relatively high densities. In addition, the smaller penelo-
pines were not necessarily more abundant than cracines.
In analyses that included a broad range of body sizes (7
orders of magnitude) and density data obtained from
multiple localities, mean density of a species scaled to the
3/4 power of body mass (White et al. 2007). Our dataset
includes a body-mass range of only 1 order of magnitude,
which represents a small part of the global range. Thus, in
this context, the lack of correlation in our analysis is due to
regression scale. Cracids are highly frugivorous, but their
diets are very broad and plastic (Mu˜
noz and Kattan 2007).
Therefore, diet is unlikely to explain the observed
variability in population density.
Cracid population densities varied over 2 orders of
magnitude. In some cases, densities were relatively high,
even compared to small passerines. At several Neotropical
forests sites where bird densities have been estimated,
densities of nonpasserine species varied between 1 and 100
birds km
2
(Terborgh et al. 1990, Robinson et al. 2000,
Haugaasen and Peres 2008). Insectivorous passerine
densities also varied within the same range, although
many species had densities of ,20 birds km
2
(Stouffer
2007, Kikuchi 2009). In Manaus, Amazonian Brazil,
median density of 228 bird species was 5 birds km
2
, and
55 species had 2 birds km
2
(Johnson et al. 2011). Thus,
cracid densities in general are not particularly low.
Intraspecific densities of cracids are geographically
variable, although few species have been evaluated at
more than 1 locality. Geographic variability in abundance
is a general phenomenon observed in birds and other
animals, as population densities respond to combinations
of factors that include variation in environmental condi-
tions and species interactions (Lundberg et al. 2000,
Sagarin et al. 2006). The factors that drive geographic
variability in cracid populations have not been investigat-
ed, but one possible factor is productivity related to
latitude, elevation, temperature, and precipitation patterns.
Habitat specialization is a dimension of rarity and an
important factor of vulnerability (Arita et al. 1990, Brooks
1998). Therefore, documenting spatial and temporal
patterns of habitat use is critical for conserving cracid
populations. Many cracids seem to be plastic and use
different habitats in heterogeneous landscapes. Variability
among habitats in the numbers of birds may reflect 1of 3
situations: (1) Different individuals show consistent
preferences for a particular type of habitat, where they
remain most of the time; (2) individuals move among
habitats over short-term periods; or (3) populations move
seasonally among habitats (e.g., Parra et al. 2001, Rios et al.
2006). Habitat shifts and local to regional movements in
response to food availability have been documented in
some avian species (Law and Dickman 1998, Renton 2001,
Holbrook et al. 2002, Haugaasen and Peres 2007).
Plasticity in habitat use promotes population stability
because it provides a range of resources and microclimates
at the landscape scale (Oliver et al. 2010). Thus, habitat
mosaics are important, and the protection of a single
habitat may be insufficient for the conservation of
populations (Law and Dickman 1998). The seasonal
patterns of habitat use in cracids require better documen-
tation.
Hunting is a major threat for cracids, which may
constitute the main hunted item in some ethnic commu-
nities (Begazo and Bodmer 1998). The risk is increased if
the hunted animals are rare (Brooks 1999). Even if
populations are not extirpated, heavy hunting reduces
population densities to the point where they may be
The Condor: Ornithological Applications 118:24–32, Q2016 Cooper Ornithological Society
G. H. Kattan, M. C. Mu ˜
noz, and D. W. Kikuchi Cracid population densities 29

demographically inviable because of Allee effects. The
impact of hunting will depend on harvest rates and the
extent of the area affected (Brooks 1999). For an area of
276 km
2
in Amazonian Peru, Begazo and Bodmer (1998)
estimated that harvest rates of M. tuberosa and P.
cumanensis were unsustainable, but harvest of P. jacquacu
was within sustainable levels. The persistence of hunted
populations also depends on the presence of nonhunted,
adjacent areas that may function as refuges or populations
sources, although the hunted area may be a population
sink (Powell et al. 1996).
Cracids are usually among the largest species in
Neotropical bird assemblages, but they are not necessarily
scarce—the rarest species are not necessarily the largest
ones. Despite differences in body size and terrestrial versus
arboreal habits, cracid species exhibit many ecological
similarities, such as highly frugivorous but opportunistic
and broad diets. Cracid densities are geographically
variable and exhibit temporal fluctuations as they move
among habitats tracking resources. Results from our small,
but geographically and taxonomically broad, sample
suggest that cracid populations respond idiosyncratically
to local factors. Therefore, researchers and managers
should be cautious when extrapolating data across species
or even among populations of the same species. Future
studies that aim to characterize cracid populations should
take into account possible intraspecific density variations
related to seasonality, local movements, and habitat
heterogeneity.
ACKNOWLEDGMENTS
We thank Dan Brooks and an anonymous reviewer for helpful
comments on the manuscript.
Author contributions: G.H.K. and M.C.M. conceived the
idea. G.H.K. and M.C.M. collected data and conducted the
research. D.W.K. and G.H.K. analyzed the data. And G.H.K.
and D.W.K. wrote the paper.
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