FIELD ORNITHOLOGY
Wednesday Nov 26 2003 09:33 AM
Allen Press • DTPro System
GALLEY 67
forn 75_108 Mp_67
File # 08TQ
J. Field Ornithol. 75(1):67–73, 2004
Variability in roost size in an Amazona parrot:
implications for roost monitoring
Stacey Cougill and Stuart J. Marsden1
Applied Ecology Group, Department of Environmental and Geographical Sciences, the Manchester Metropolitan
University, Chester Street, Manchester M1 5GD United Kingdom
Received 3 July 2002; accepted 6 March 2003
ABSTRACT. Roost counts may be a useful method for assessing and monitoring parrot populations as long
as counting regimes can detect real differences in abundance above the noise of daily variability in roost size. We
studied a roost of up to 85 Red-tailed Amazons (Amazona brasiliensis) for 28 consecutive mornings and evenings
from 12 July to 7 August 2001, and recorded bird behavior and associated weather data. The roost declined
significantly over the survey period as the breeding season drew nearer. There was no significant difference between
evening and morning roost counts, but we suggest that as long as misty mornings are avoided, morning roost
counts were more effective as birds left more quickly and predictably. It took longer for birds to arrive on evenings
when the roost was large, but birds left quicker in the morning when there were large numbers in the roost. Weather
influenced both roost size and timing of arrival, with larger than expected numbers in the roost, and birds arriving
later in the afternoons of sunny, warm days. We tested the reliability of four roost counting regimes: counts from
five consecutive nights, five counts, one every fourth night, five nights picked at random, and 10 randomly picked
nights. Counts from every fourth day performed significantly worse than all the other regimes in estimating the
mean numbers in the roost. The 10-d random sampling regime performed significantly better than the 5-d regime
in detecting very large roosts which occurred occasionally through the month.
SINOPSIS. Variabilidad en el tamaño de los dormideros de una Amazona: implicaciones para el
monitoreo de dormideros
El conteo de aves en dormideros puedo ser un método útil para monotorear poblaciones de cotorras, siempre y
cuando el régimen de conteo pueda detectar diferencias reales en abundancia entre la variabilidad diaria del tamaño
del dormidero. Estudiamos por 28 dias consecutivos, en la manana y en la tarde, un dormidero de la cotorra
Amazona brasiliensis. El estudio se llevó a cabo del 12 de julio al 7 de agosto de 2001. Además de contar las aves
se tomaron datos sobre su conducta y las condiciones del tiempo. El dormidero se redujo significativamente según
se fue acercando el periodo reproductivo de las aves. No se encontró diferencia significativa entre los conteos
matutinos y los de la tarde. Sin embargo sugerimos, se eviten las mañanas con niebla. Los conteos de la mañana
resultan más efectivos que los de la tarde, ya que las aves dejan el lugar más rápida y predeciblemente. Le tomó a
las aves más tiempo el llegar en las tardes cuando el dormidero era bien grande, pero bajo estas condiciones las aves
dejaron el lugar más rapidamente en la mañana. Las condiciones del tiempo afectaron tanto el tamaño del dormidero
como el tiempo de llegada, con un mayor número de aves que las esperadas y llegando más trade en dias cálidos
y tardes soleadas. Estudiamos la confiabilidad de conteos con muestras de cinco noches consecutivas, cinco conteos
hechos cada cuatro dias, cinco noches tomadas al azar, y diez noches tomadas al azar. Los conteos hechos cada
cuatro dias fueron significativamente peores en estimar el número promedio de aves en el dormidero que los otros
tipos de muestreos. El muestreo cada 10 dias al azar, arrojó, significativamente, mejores resultados que el régimen
de cada cinco dias para detectar aves en dormideros grandes (que se formaron ocasionalmente a lo largo del mes).
Key words: Amazona brasiliensis, Atlantic forest, Brazil, movements, roost
Counting individuals as they enter/leave
roosts has been used in many assessments of
parrot population sizes (e.g., Gnam and
Burchsted 1991; Martuscelli 1995) and may
have potential for long-term monitoring of
populations of some species (Wermundsen
1998; Snyder et al. 2000). The method may be
especially useful where bird densities during the
1
Corresponding author. Email: s.marsden@mmu.
ac.uk
67
day are very low (Marsden 1999; Pithon and
Dytham 1999) but where roosts are discrete
and stable (Martuscelli 1995; Snyder et al.
2000). Few systematic studies of roosting in
parrots have been published and, recognizing
the potential of the methods, Casagrande and
Beissinger (1997) recommended the further development of roost-survey protocol. To accurately and precisely gauge roost sizes, a number
of factors need to considered, including reliability of individual counts (e.g., observer bias),
time of year, and the intrinsic variability in the
FIELD ORNITHOLOGY
Wednesday Nov 26 2003 09:33 AM
Allen Press • DTPro System
68
GALLEY 68
S. Cougill and S. J. Marsden
numbers of birds that enter the roost each evening (e.g., Gnam and Burchsted 1991; Casagrande and Beissinger 1997; Harms and Eberhard 2003). For effective year-by-year monitoring, the ‘‘unwanted’’ variability in roost numbers caused by all factors other than a real
change in the population needs to be controlled
for.
We studied a roost of the endangered Redtailed Amazon (Amazona brasiliensis) on Ilha do
Cardoso, southeast Brazil, for 28 consecutive
mornings and evenings from 12 July to 7 August 2001, using a standard method. Our aim
was to examine daily variability in numbers recorded entering/leaving the roost, to identify
factors that might affect this variability, and to
assess the performance of different counting regimes in accurately reflecting the true numbers
of birds in the roost.
METHODS
The roost. The study was carried out at
the Parque Estudual da Ilha do Cardoso
(258039S 478539W; 22,500 ha), off the south
coast of São Paulo state, Brazil. The roost is
adjacent to the ecological station in the northeast of the island, in a small clump of trees on
raised ground within a mosaic of sand-plain
forest, coastal dune, and mangrove habitat between the coast and a tidal creek (the roost is
inaccessible by foot). Amazona brasiliensis is the
only parrot known from this roost, which has
been used for several years (M. Galetti, pers.
comm.). The roost, as with other roosts of the
species, seems to be active principally during
the non-breeding season, with pairs splitting
from the main group at the end of August. According to Martuscelli (1995), breeding pairs
usually sleep in the nest hollow, leading to fewer birds visiting the roost as the breeding season
gets underway and then perhaps no birds roosting communally, although where non-breeding
birds roost is not known. On Cardoso, the
roost is inactive in March (M. Galetti, pers.
comm.) and possibly other months, although
no definitive data are available.
Field methods. Surveys were conducted
from a vantage point (a raised bridge) situated
250 m from the roost and allowing a full view
of parrot flight paths to and from the roost. All
surveys were conducted by SC after one week
of practice. Morning observations commenced
forn 75_108 Mp_68
File # 08TQ
J. Field Ornithol.
Winter 2004
just before dawn (around 06:30) and continued
until the last bird had left the roost. Evening
surveys commenced at 15:00 and continued
until just after dusk (around 18:00). A major
flight path for the birds is adjacent to the research station and is lit up at night, and no
parrots were observed to arrive after dark during the week-long pilot study. For each recording of parrots entering or leaving the roost,
their time of detection, the direction of flight,
group size, and whether they were heard calling
were recorded. One problem with roost counts,
especially those from the evenings, is that birds
can move around the roost and often repeatedly
enter and leave the roost (Snyder et al. 1987).
To combat this problem a ‘‘roost zone’’ was delineated around the roost trees. The zone was
a circle of radius equal to approximately 50 m
around the epicenter of the roost. All bird
movements, both into and out of this area, were
recorded. Birds leaving the roost zone were subtracted from the number of birds counted entering the roost zone so as not to double-count
groups. Binoculars (10 3 50) were used to
identify birds, although the vantage point was
close enough to the roost to count the number
of birds accurately without them.
Maximum daily temperature (8C), total daily
incoming solar radiation absorbed (J/m), and
total daily precipitation (mm) were downloaded
from the weather station situated ,100 m from
the observation point. In addition, every two
hours, (between 08:00 and 18:00) on each day
of the survey, SC recorded the presence or absence of mist.
Data analysis. Variables were examined
for normality using Kolmogorov-Smirnov tests.
Where the distribution of values differed significantly from normality (P , 0.05), nonparametric tests were used. Differences between
counts of birds entering the roost in the evening and those of birds leaving the following
morning were tested using a paired t-test. The
higher of the evening or morning count for a
particular night was used as the roost count for
that night in subsequent analyses. Differences
in the frequencies of group sizes between birds
arriving at the roost and those leaving were examined using a chi-square test. Differences in
the time it took for all birds to arrive at the
roost, and to leave the following morning, were
tested using a Wilcoxon signed-ranks test. Relationships between roost parameters were test-
FIELD ORNITHOLOGY
Wednesday Nov 26 2003 09:33 AM
Allen Press • DTPro System
GALLEY 69
Parrot Roost Surveys
Vol. 75, No. 1
ed with Pearson’s product-moment correlation,
except when relating roost parameters to the
weather data where the nonparametric Spearman rank correlation was used.
To examine daily variability in roost numbers
and to test for reliability of roost counting regimes, we first had to control for changes in
roost size through the study period. Overall
roost numbers declined through the month, so
we controlled for this decline by regressing
roost number on day number. We had no apriori assumption that roost number should decline in a linear fashion, so we tested the fit of
a series of curves including linear, quadratic, cubic, and power functions, and picked the model
with best fit. We saved the residuals from this
regression as these indicate whether more (positive residual) or fewer (negative residual) birds
than expected for a given day were actually in
the roost (a residual of zero indicates that the
roost was the size expected for a given day).
We tested the performance of four counting
regimes. The roost counts were again the residual values after the decline in roost count
throughout the study period had been accounted for. The regimes were ‘‘five consecutive
days,’’ a rolling average of counts from five sequential days counts (e.g., days 1–5, 2–6, etc.);
‘‘every fourth day,’’ groups of five counts from
every fourth day (e.g., days 1, 5, 9, 13, 17; 2,
6, 10, 14, 18, etc.); ‘‘random five days,’’ roost
counts from five days selected randomly from
the survey period; and ‘‘random 10 days,’’ roost
counts from ten days selected randomly from
the survey period. This allowed 23 counts for
the ‘‘five consecutive day’’ regime and 11 counts
for the ‘‘every fourth day’’ count regime. We
generated 40 runs for each of the random regimes. Differences in standard errors between
counting regimes were tested with ANOVA
with Bonferroni posthoc tests. Differences in
mean roost count residuals and maximum
counts were tested using Kruskal-Wallis tests
with Dunn’s posthoc tests (e.g., Wheater and
Cook 2000).
RESULTS
Changes in roost size over time. As the
month progressed, fewer birds entered the roost
(Fig. 1). The falloff in bird numbers with day
number best fitted a cubic function (r2 5 0.48,
F3,23 5 7.05, P 5 0.0016).
forn 75_108 Mp_69
File # 08TQ
69
Fig. 1. Changes in Red-tailed Amazon roost count
(higher of the evening or morning counts) over the
survey period.
Differences between evening and morning roost counts. There was no significant
difference between the evening and morning
counts (paired t-test: t26 5 0.28, P 5 0.78).
There was a significant difference in the deviations between the morning and afternoon
counts (regardless of whether the morning or
afternoon count was larger) between the first
and second halves of the month (day 1–14,
mean difference, 23.1 6 17.2 SD; day 15–28,
mean difference, 5.9 6 7.4; t25 5 3.4, P 5
0.003). There was a significant positive relationship between the deviations of the morning
and evening counts and the total roost count (r
5 0.63, P , 0.001), showing that on days
when more birds entered the roost, there were
larger discrepancies between morning and evening counts. Roost counts tended to be lower
than those of the previous afternoon when mist
was present in the morning (mean difference,
24.2), than on clear mornings (mean difference, 113.0), although the difference was not
quite significant (t24 5 1.9, P 5 0.08).
There was a significant difference in the frequencies of group sizes between morning and
afternoon (x26 5 30.2, P , 0.001). The main
differences were that, in the evenings, there
were more pairs and fewer singles and groups
.6 entering the roost than there were leaving
the roost in the mornings (Table 1).
Timing of movements to and away from
the roost. There was considerable betweenday variability in the timing of birds entering/
FIELD ORNITHOLOGY
Wednesday Nov 26 2003 09:33 AM
Allen Press • DTPro System
70
forn 75_108 Mp_70
File # 08TQ
GALLEY 70
J. Field Ornithol.
Winter 2004
S. Cougill and S. J. Marsden
Table 1. Frequency and percentage of encounters of
group sizes of Red-tailed Amazons entering/leaving
the roost.
Group size
1
2
3
4
5
6
.6
Max. group size
Entering roost
55
361
36
15
19
7
15
16
11%
71%
7%
3%
4%
1%
3%
Leaving roost
63
252
25
17
7
8
41
36
15%
61%
6%
4%
2%
2%
10%
leaving the roost (Fig. 2). Birds took longer to
arrive at the roost in the evenings (mean, 65
min 6 26 SD) than they did to leave the roost
the following mornings (mean, 13 min 6 6.1;
Z 5 4.5, P , 0.001).
For the evenings, there was a significant positive correlation between the time it took to
arrive and the total number of parrots in the
roost (r 5 0.52, P 5 0.005), indicating that
the larger the total number in the roost, the
longer it took them to arrive. In the mornings,
however, the total number of parrots in the
roost was negatively correlated with the amount
of time it took birds to arrive (r 5 20.43, P
5 0.02), indicating that when there were a
large number of parrots in the roost, the parrots
left the roost more quickly.
Measures of the timing of arrival of birds in
the evenings were significantly correlated with
the amount of absorbed solar radiation, and to
a lesser extent, maximum temperature, during
that day (Table 2). On sunny, warm days, birds
generally arrived later in the afternoons than on
cooler, sunless days. There were no significant
relationships between time of arrival and precipitation.
Fig. 2. Timing of Red-tailed Amazons entering/
leaving the roost (minutes after dawn/before dusk).
Influence of weather on roost size.
High values of residual roost counts were positively correlated with total radiation absorbed
(rs 5 0.42, P 5 0.03). Roost counts tended to
be lower on days with high, or at least some
precipitation but the relationship was not significant (rs 5 20.32, P 5 0.10). There was no
relationship between roost count and maximum temperature (rs 5 20.08, P 5 0.70).
Test of different counting regimes.
Standard errors for the three 5-d regimes were
similar, but the average SE was significantly
lower in the 10-d sample than the 5-d random
Table 2. Spearman rank correlation coefficients between the timing of parrot arrival at the roost and weather
variables. First in, Last in, and 50% in, are the number of minutes before dusk that the first bird, the last
bird, and 50% of those in the roost had arrived.
First in
Last in
50% in
Max. temp.
Radiation
Last in
50% in
10.41*
10.78**
10.56**
* P , 0.05, ** P , 0.005.
Maximum
temperature
20.46*
20.16
20.47*
Radiation
Precipitation
20.45*
20.52**
20.66**
10.39*
10.33
10.28
10.35
10.16
20.44*
FIELD ORNITHOLOGY
Wednesday Nov 26 2003 09:33 AM
Allen Press • DTPro System
forn 75_108 Mp_71
File # 08TQ
GALLEY 71
Parrot Roost Surveys
Vol. 75, No. 1
71
Table 3. Roost count residuals for the four counting regimes. Values shown are mean deviations from the
expected roost count (where a mean of zero equals the expected mean), standard errors, and mean maximum
roost count (the average of the highest total recorded on any of the 5/10 d). N 5 number of runs for each
regime.
Model
A. Five consecutive days N 5 23
B. Every fourth day N 5 11
C. Random five days N 5 40
D. Random ten days N 5 40
A vs. B vs. C vs. D
Post-hoc tests
a
b
Mean roost
count residual
2.1
6.2
3.1
2.9
H3a 5 15.3, P 5
0.002
B . A, B . C, B
.D
Mean SE
4.9
4.2
4.7
3.3
F3,110b 5 9.4, P ,
0.001
A . D, C . D
Mean of
maximum count
112.2
111.4
111.6
116.3
H3a 5 15.3, P 5
0.002
D.C
Kruskal-Wallis tests with Dunn’s posthoc tests.
ANOVA with Bonferroni posthoc tests.
sample and the sample from every fourth day
(Table 3). In terms of counting accuracy (deviations from the means), counts from every
fourth day were significantly less precise than
the other three models. Counts from five consecutive days were actually more precise than
the 10-d random model, although the difference was not significant. Maximum counts also
differed between models, and this time the 10d random model was significantly better at
picking up large roosts than the 5-d random
model.
DISCUSSION
Despite considerable daily variability in
numbers of birds entering the roost, we were
able to detect a decline in roost size through
the study. Red-tailed Amazons are known to
begin breeding in September (Martuscelli
1995), and our data suggest that some birds
abandoned the central roost as the breeding season drew nearer. Studies of other parrots have
found marked seasonal changes in roost sizes
(e.g., Renton 2002), with perhaps a proportion
of birds roosting in their nest holes prior to
breeding (Martuscelli 1995). In terms of accurate roost counting, we stress that surveys
should take place at the same time of year each
season or across sites, that survey periods should
be carefully selected because breeding seasons
themselves can vary between years or sites (e.g.,
Forshaw 1989), and that the roost may diminish quite gradually over time towards the breeding season.
While we could detect no consistent difference between evening and morning counts, we
suggest that morning roost counts may be more
reliable than evening counts, as long as mornings with poor visibility due to mist are avoided. Birds left the roost more quickly than they
arrived in the evening; the latest that all birds
had left the roost was 55 min after dawn. The
timing of arrival in the evenings was significantly influenced by weather conditions, with
birds arriving up to three hours before dusk on
cloudy days. In the mornings, birds left the
roost more predictably, and there was little of
the movement in and out of the roost seen in
the evenings (Mabb 1997). The stimuli for
most movements around the roost in the evening were unidentified, although perceived predators, such as the Chimango Caracara (Milvago
chimachima), were a major cause of roost disturbance (e.g., Mabb 1997; Pithon and
Dytham 1999). One potential disadvantage of
morning counts at larger roosts can be that
birds leave more quickly. This may make
counting individuals difficult, especially if they
leave in very large groups.
We were able to account for some of the
variability in size of nightly roosts in terms of
weather the previous day. Roost counts were
lower on sunless days (and perhaps also on wet
days), and it may be that a proportion of birds
staying away from the roost spent the night in
their nest cavities (birds at the roost slept on
branches rather than in cavities). There are energetic benefits to birds roosting in cavities
(e.g., du Plessis et al. 1994), and this may be a
FIELD ORNITHOLOGY
Wednesday Nov 26 2003 09:33 AM
Allen Press • DTPro System
72
forn 75_108 Mp_72
File # 08TQ
GALLEY 72
S. Cougill and S. J. Marsden
mechanism by which birds can reduce energy
expenditure during ‘‘winter’’ nights on Cardoso,
which can be cold and windy. Alternatively,
there may be other roosts on the island or in
other areas where birds form temporary roosts,
and it could that there is a high degree of fluidity in roost position and membership (e.g.,
Marzluff et al. 1996; Pithon and Dytham
1999; Berg 2001).
Whatever its causes, the daily variability in
roost numbers recorded during our study
means that caution is needed when interpreting
roost counts made over just one or a few nights.
The average difference between the roost
counts on consecutive nights in this study was
almost 25% (of the higher count), and on one
occasion the roosts on two consecutive nights
differed by 60% (28 vs. 70 individuals). To detect real changes in population size using just
one or two roost counts is clearly unrealistic.
Our test of different counting regimes suggested that a random selection of dates over the
month or counts over successive days performed significantly better at estimating the
mean number of birds in the roost than did
returning to count the roost periodically. Why
periodic counts (counting the roost every four
days) should result in high deviance from expected roost count values is unclear. It could be
that there is some periodicity in roost numbers,
with roosts building up every few days to a
maximum and then reducing. What is clear is
that a sequence of 10 d of counts performed
significantly better than 5 d of counts at detecting the very large numbers of individuals
that entered the roost on just a few dates in the
month. Whether these ‘‘occasional’’ birds are
seen as a target for monitoring may depend on
the aim of the study, but if they are, then a
prolonged survey period is needed to detect
them.
Unless the locations of all roosts, or the
‘‘catchment area’’ for each roost is known,
counts like ours cannot of course yield estimates of total population, only estimates of individual roost size. How appropriate counts
from a single roost might be will depend on the
amount of movement between roosts of individuals from the local population. In our study,
the nearest adjacent roost used by Red-tailed
Amazons was over 8 km away. Consequently,
we assumed relatively low rates of day-to-day
movements between the established roosts in
J. Field Ornithol.
Winter 2004
our study. The same cannot be said for other
parrot species; for example, the Green-rumped
Parrotlet (Forpus passerinus) shows extensive between-day movement among roosts (Casagrande and Beissinger 1997). Ideally, roost monitoring should be done at a time of year when
roosts are stable and birds most sedentary. We
have little data on roosting patterns in parrots
in general, and additional research is needed.
While inapplicable for some groups and
some situations (Gilardi and Munn 1998),
roost counting can be a useful tool in the monitoring of some seriously threatened parrot taxa
such as Amazona and Ara (Pitter and Christiansen 1995). The magnitude of population
change in a roost that we might detect may be
in the region of 20% over 3–5 yrs, a decline
that would qualify a taxon for ‘‘Vulnerable’’ status according to the IUCN Red List classification (BirdLife International 2000). In our
study, series of counts over 5 and 10 nights
deviated on average around four and two individuals from the expected (around 8% and
4% of the population actually present). In
terms of average roost size, 5–10 nights of
counts seem adequate to express the ‘‘average’’
roost size, at least for this roost in this particular
month, with counts over 10 d being consistently more precise. Short study periods will be
unsuccessful at picking up unusually large
roosts, and if a maximum roost count is the
target, then many nights of roost counting are
needed. While daily and seasonal variability in
roost size, and the unpredictability of roost
membership, will confound attempts to accurately or precisely monitor parrot roosts, the repeated counting of a sample of stable roosts
across years may be a useful tool in warning of
possible population declines in rare species.
ACKNOWLEDGMENTS
Permission to conduct research on Ilha do Cardoso,
logistical help, and accommodation was provided by
Marcos Campolin. We are grateful to Mauro Galetti for
hosting the project at UNESP. For support on Cardoso,
we thank Emma Edwards and Sr. Romeu. This project
was funded by the North of England Zoological Society
(NEZS). We thank Roger Wilkinson for various kinds
of help.
LITERATURE CITED
BERG, K. S. 2001. Notes on the natural history of the
Pale-mandibled Aracari. Journal of Field Ornithology 72: 258–266.
FIELD ORNITHOLOGY
Wednesday Nov 26 2003 09:33 AM
Allen Press • DTPro System
Vol. 75, No. 1
GALLEY 73
Parrot Roost Surveys
BIRDLIFE INTERNATIONAL. 2000. Threatened birds of the
world. Lynx Editions and BirdLife International,
Barcelona, Spain.
CASAGRANDE, D. G., AND S. R. BEISSINGER. 1997. Evaluation of four methods for estimating parrot population size. Condor 99: 445–457.
DU PLESSIS, M. A., W. W. WEATHERS, AND W. D. KOENING. 1994. Energetic benefits of communal roosting by Acorn Woodpeckers during the non-breeding season. Condor 96: 631–637.
FORSHAW, J. M. 1989. Parrots of the world. 3rd ed.
Lansdowne Press, Melbourne, Australia.
GILARDI, J. D., AND C. A. MUNN. 1998. Patterns of
activity, flocking, and habitat use in parrots of the
Peruvian Amazon. Condor 100: 641–653.
GNAM, R., AND A. BURCHSTED. 1991. Population estimates for the Bahama Parrot on the Abaco Island,
Bahamas. Journal of Field Ornithology 62: 139–
146.
HARMS, K. E., AND J. R. EBERHARD. 2003. Roosting
behavior of the Brown-throated Parakeet Aratinga
Pertinax and roost locations on four southern Caribbean islands. Ornitologia Neotropical 14: 79–
89.
MABB, K. T. 1997. Roosting behaviour of naturalized
parrots in the San Gabriel Valley, California. Western Birds 28: 202–208.
MARSDEN, S. J. 1999. Estimation of parrot and hornbill
densities using a point count distance sampling
method. Ibis 141: 377–390.
MARZLUFF, J. M., B. HEINRICH, AND C. S. MARZLUFF.
forn 75_108 Mp_73
File # 08TQ
73
1996. Raven roosts are mobile information centres.
Animal Behaviour 51: 89–103.
MARTUSCELLI. P. 1995. Ecology and conservation of the
Red-tailed Amazon Amazona brasiliensis in southeastern Brazil. Bird Conservation International 5:
405–420.
PITHON, J. A., AND C. DYTHAM. 1999. Census of the
British Ring-necked Parakeet Psittacula krameri
population by simultaneous counts of roosts. Bird
Study 46: 112–115.
PITTER, E., AND M. B. CHRISTIANSEN. 1995. Ecology,
status and conservation of the Red-fronted Macaw
Ara rubrogenys. Bird Conservation International 5:
61–78.
RENTON, K. 2002. Seasonal variation in occurrence of
macaws along a rainforest river. Journal of Field Ornithology 73: 15–19.
SNYDER, N., P. MCGOWAN, J. GILARDI, AND A. GRAJAL.
2000. Parrots. Status survey and conservation action plan 2000–2004. IUCN, Gland, Switzerland.
———, J. W. WILEY, AND C. B. KEPLER. 1987. The
parrots of Luquillo: natural history and conservation of the Puerto Rican Parrrot. Western Foundation of Vertebrate Zoology, Los Angeles, CA.
WERMUNDSEN, T. 1998. Colony breeding of the Pacific
Parakeet Aratinga strenua Ridgway 1915 in the Volcán Masaya National Park, Nicaragua. Tropical Zoology 11: 241–248.
WHEATER, C. P., AND P. A. COOK. 2000. Using statistics
to understand the environment. Routledge, London, UK.