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Turkish Journal of Forestry | Türkiye Ormancılık Dergisi
2018, 19(1): 57-62 | Research article (Araştırma makalesi)
a Süleyman Demirel University, Faculty of Forestry, Isparta
@ * Corresponding author (İletişim yazarı): yasinunal@sdu.edu.tr
Received (Geliş tarihi): 20.09.2017, Accepted (Kabul tarihi): 20.12.2017
Citation (Atıf): Ünal, Y., Çulhacı, H., 2018.
Investigation of fallow deer (Cervus dama L.)
population densities by camera trap method in
Antalya Düzlerçamı Eşenadası Breeding Station.
Turkish Journal of Forestry, 19(1): 57-62.
DOI: 10.18182/tjf.339042
Investigation of fallow deer (Cervus dama L.) population densities by camera
trap method in Antalya Düzlerçamı Eşenadası Breeding Station
Yasin Ünala,*, Hasan Çulhacıa
Abstract: In Turkey, it has been aimed to take a number of measures to protect and breed fallow deer, which is under danger of
reduction of population, even extinction. One of these measures is Antalya Düzlerçamı Eşenadası Fallow Deer Breeding Station
(EFDBS). Fallow deer is protected in this area, where measures and improvements are taken to the maximum for breeding fallow
deer in its natural environment. 55 out of 170 mammal species are critically endangered in Turkey, and one of these is fallow
deer (Cervus dama L.). This study aims to investigate the population densities of individuals spread in the EFDBS at Antalya
Düzlerçamı Wildlife Development Area with 521 ha of land using the method of camera traps. Density calculations were made
using the method of individual identification based on spot distribution and antler structure of individuals. The information
provided by the Jackknife Model was used to determine population densities. “CAPTURE” software was used for the analysis of
the data. Based on the obtained results, maximum of 120, minimum of 96 and average of 105 fallow deer individuals were found.
According to these results, fallow deer population density was 20.1/km2 in the study area.
Keyword: Fallow deer (Cervus dama), Camera trap, Capture-recapture, Wildlife inventory
Antalya Düzlerçamı Eşenadası Alageyik Üretim İstasyonu’nda fotokapan
yöntemiyle alageyik (Cervus dama L.) popülasyon yoğunluklarının araştırılması
Özet: Ülkemizde, nesli bu denli azalma hatta yok olma seviyesine gerileyen alageyik için bir takım koruma ve üretme tedbirleri
alınmak istenmiştir. Bunlardan bir tanesi, Antalya Düzlerçamı Yaban Hayatı Geliştirme Sahasında kurulan Eşenadası Alageyik
Üretme İstasyonu’dur. Alageyikler bu alanda koruma altında olup, doğal ortamında üremesine yönelik maksimum önlemlerin ve
iyileştirmelerin yapıldığı bir alandır. Ülkemizde yaşadığı saptanan 170 memeli türden 55’inin nesli önemli ölçüde tükenme
tehdidi altında olup, bunların en önemlilerinden bir tanesi alageyik (Cervus dama L.)’dir. Bu araştırmada, fotokapan yöntemi ile
521 ha alana sahip Antalya Düzlerçamı Yaban Hayatı Geliştirme Sahasında bulunan Eşenadası Alageyik Üretme İstasyonu
içerisinde yayılış gösteren bireylerin popülasyon yoğunluklarının araştırılması hedeflenmiştir. Yoğunluk hesaplamaları, bireylerin
benek dizilişinden ve boynuz yapısından birey tespiti yöntemi kullanılarak yapılmıştır. Verilerin analizi için “Capture” bilgisayar
programından faydalanılmıştır. Populasyon yoğunluğunun belirlenmesi için Jackknife Model verileri dikkate alınmıştır. Elde
edilen sonuçlara göre maksimum 120 birey, minimum 96 ve ortalama 105 Alageyik tespit edilmiştir. Elde edilen bu sonuçlara
göre çalışma alanında alageyik populasyon yoğunluğu 20,1/km2 dir.
Anahtar kelimeler: Alageyik (Cervus dama), Fotokapan, Capture-recapture, Yaban hayati envanteri
1. Introduction
It is known that fallow deer population is 8.000 in
Germany, 62.000 in the United Kingdom, 18.000 in
Hungary, 12.500 in Romany, 11.600 in France and 250,000
in total in Europe, between 15,000 and 35,000 in New
Zealand and 28,350 in Canada, while it is about 450,000 in
the world (Heidemann, 1976; Ueckermann and Hansen,
1994; Kaçar, 2002). Despite the fact that the native land is
Turkey, the last natural fallow deer population in the world
is known to be Antalya-Düzlerçami. The fallow deer is
categorized as LC (Least Concern) in the world, as it is
spread around the world, and the species is not under the
threat of extinction in the near future (IUCN, 2016).
However, in Turkey in the last century, it has been seen that
fallow deer populations are increasingly in danger of
reduction or even extinction especially due to illegal
hunting, increase in urbanization parallel to the human
population, dense forestry, and agriculture activities, grazing
of domestic animals such as goats and sheep, and
deterioration of endangered environments of human
pressures in fallow deer fields (Heidemann, 1976; Saribaşak
et al., 2005; Chapman and Chapman, 1997). Although it is
not categorized in any way in terms of our country, taking
into account that the species is the most endangered
mammal species, it would be a correct approach to treat it as
a CR (Critically Endangered) status (Sevgi et al., 2013).
In the scientific research, inventory method with
camera-trap gives more positive results in speckled species
such as fallow deer. Trolle and Kerry (2003), Connolly
(2007), Meek et al. (2012) and Keuling et al. (2012)
reported that camera-traps were produced primarily to
monitor wildlife populations and Mengüloğlu (2010)
reported that camera-trapping is particularly useful for
Turkish Journal of Forestry 2018, 19(1): 57-62
58
identifying striped or spotted species on an individual basis.
The method of camera trapping is especially beneficial in
identifying wild mammals, as well as determining activity
patterns (Soyumert, 2010; Foster and Harmsen, 2012; Can,
2008; Griffiths and Schaik, 1993). Both random-opportunist
and systematic methods are used in wildlife studies to
collect information regarding wild animal populations with
camera trap method. Method of systematic is the work done
by establishing certain distance between each camera trap
(Harmsen et al., 2011).
The capture-recapture method is a frequently used
method in determining population sizes and densities by
using biological parameters of populations (Chao et al.,
2001; Karanth and Nichols, 1998; Marker et al., 2008;
Wang and Macdonald, 2009). This method provides reliable
scientific and comprehensive results in studies on enclosed
wild animal populations (Chao, 2001). The software
Capture is frequently used to estimate the maximum,
minimum and average population sizes of fallow deer
(Rexstad and Burnham, 1991; Silver et al., 2004). This
program is often used in predicting the population size,
starting from the frequency of capture and recapture of
camera traps in study areas. This method reveals the
minimum, maximum and average sizes of the population by
allowing comparison of different statistical methods and
their combinations (Silver et al., 2004).
2. Material and method
2.1. Material
Antalya Düzlerçamı Wildlife Development Area is the
only area in Turkey where the fallow deer live naturally
(Anonymous, 2013). Düzlerçamı WDA was declared as a
land of 28,972 ha area in 2005. The area is divided by the
road between Antalya and Korkuteli. It was determined that
the fallow deer lived in numerous regions in Turkey, based
on drawings and remains from the period of Hittites, as well
as fossils found in various places such as Van, south of the
Salt Lake, and the Marmara Region (Ducos, 1988). The
fallow deer, known to had lived in the Marmara, Aegean
and Mediterranean Regions naturally in the 19th century,
remained only in the Antalya-Düzlerçamı region today in
small numbers due to illegal hunting and disruption of their
habitat (Figure 1). Turan (1966) determined that fallow deer
were living in Antalya-Düzlerçamı and Manavgat Regions
and led to the departure of Düzlerçamı region as Wildlife
Conservation Area and establishment of a fallow deer
breeding stations in it. In 1974, the first station in operation
was inadequate in terms of the number of animals it hosted,
fallow deer were transported to the EFDBS in 2003 in the
natural environment and in wider and more favorable
conditions (Figure 2).
The study area is located 25 km west of Antalya, within
the borders of Antalya Regional Directorate of Forestry,
Antalya Central Administration, Düzlerçamı Forest
Administration Management. It is surrounded by the Güver
Cliff Canyon, Yukarı Karaman residential area and
Korkuteli Road in the east; Termessos National Park
following Korkuteli Road, Yeşilkayrak and Akkaya in the
north, Gürkavak, Mecene Canyon and Kozdağ in the west;
and residential areas of Doyran, Aşağı Karaman and
Antalya in the south. The area provides to fallow deer for
suitable habitat with its rich flora, water resources and
geographical structure.
Figure 1. Düzlerçamı Wildlife Development Area and
Eşenadası Fallow Deer Breeding Station
Figure 2. Distribution of the fallow deer in Turkey in the past (Red) and today (Yellow)
Turkish Journal of Forestry 2018, 19(1): 57-62
59
In the study, we used 16 Cuddeback Attack Model: 1149
camera traps to determine for deer number, Canon EOS
600D to take photographs for fallow deer habitat and
Magellan Trioton 400D to measure for each plot’s altitude,
coordinates of sampling plots.
2.2. Method
Preliminary studies were carried out to determine tracks
and sings of the fallow deer in the region before the camera
traps were set in the area. As a result of these studies, fallow
deer footprints and feces were observed. During the camera
trap study, 16 Cuddeback Attack IR 5MP passive camera
trap were used. Field studies were carried out in two periods
between 2014 and 2015 in pre-determined camera trap
stations set in intervals of 400 m (Figure 3). The data
obtained from the camera traps that were set across each
other were transferred to the electronic center, stored and
the office work was done to calculate the density (Figure 4).
Population density was determined by dividing the
estimated population size by the effectively sampled area,
and variance was calculated as described by Karanth and
Nichols (1998). The information collected by camera traps
set across each other was transferred to electronic
environment, stored, and used to calculate density. Total 80
camera trap stations were distributed in the region in a
certain systematic and across each other.
2.3. Identification of individuals
Microsoft Paint was used as an alternative method for
individuals’ identification. The images obtained from
camera traps were analyzed in detail, image data in each
plot suitable for identification were divided into plots and
years, and stored. The most important characteristics
distinguishing fallow deer from other deer are the white
spots on their bodies and their prong-shaped antlers. Except
for the winter months, all fallow deer have spots.
Considering these morphological features of fallow deer,
female individuals were identified using the distributions of
their spots, while male individuals were identified in the
same way except for the winter months and using their
antler structure in winter months. In the following stage,
with these data, individuals were identified starting with the
first two plot areas, considering antler structure and spot
distribution. Against the possibility of different individuals
having similar spot distributions and antler structures, the
images were transferred to the Microsoft Paint software.
Here, spot distributions and antler structures were compared
by drawing in the software and different individuals were
numbered (Figure 5a, 5b, 6a, 6b).
Individual identification of fallow deer in the area was
achieved using the capture-recapture method based on the
morphological characteristics of the deer. Our analyses were
carried out based on the data obtained by camera traps. The
data obtained from the camera traps that were set across
each other were transferred to the electronic center and
stored and the office work was done to calculate the density
(Table 1).
Figure 3. Camera trap stations
Figure 4. Opposing camera traps (plot 4-8)
Figure 5a. Male individual No: 9
Table 1. Capture-Recapture calculation
𝒙
𝒚 ≅ 𝑿
𝑻Ṫ ≅ 𝒚
𝒙 . 𝐗
X number of individuals captured and marked in the first sampling
y number of individuals independently captured in the second
sampling
x number of previously marked and recaptured individuals
T total size of population (total number of individuals)
Ṫ Estimated population size
Turkish Journal of Forestry 2018, 19(1): 57-62
60
Figure 5b. Male individual No: 50
Figure 6a. Female individual No: 2
Figure 6b. Female individual No: 31
“The Capture” population size estimation software was
used to determine the maximum, minimum and average
population size, as well as population density (Rexstad and
Burnham 1991; Soria-Diaz and Monroy-Vilchis, 2015;
González-Pérez, 2003; Ortega et al., 2011). In order to
estimate population size, capture-recapture information was
entered (Silver et al., 2004), and the data obtained from
population estimation methods of Jackknife-M(h) (Silver et
al., 2004) and Removal-M(bh) were utilized. While the
resulting values ended up very close to each other,
*Jackknife Population Density Values*, recommended by
Orekici-Temel et al. (2012) and reported to have better
results, were used.
3. Results
A total of 8,120 camera trap days was reached in 80 plot
areas for 203 days. Totally 1232 images and videos were
obtained in 2014 and 2105. Respectively 527 and 464 wild
animals’ images and videos were determined in these
stations (Table 2).
As a result of the study, 19 females and 33 males in
2014, 14 females and 14 males in 2015 totally 80 fallow
deer were determined and identified. 15 fallow deer were
recaptured in the study (Table 3).
Confidence interval in Jackknife-M(h) population size
and density detection was found as 95%, and SE was found
as 6.25. Table 4 shows the minimum, maximum and
average population size values and density values.
Based on the obtained results, a maximum of 120,
minimum of 96 and average of 105 fallow deer individuals
were identified. Additionally, the number of individuals
found in our studies in 2014 and 2015 were based only on
adult individuals and fawns were not taken into account.
About 20 fawns were found in the data obtained using
camera traps and Capture-Recapture method provided us
with the total number of adults and fawns as 105 + 20 =
125. According to these results, fallow deer population
density was 20.1 / km2 in the study area.
Table 2. Analysis of camera trap images
Year
Total camera
trap station
Number of
images
Number of empty
camera trap images
Total number of wild animal images
obtained from camera traps
Number of fallow
deer images (=D)
A
B
B*100/A
(A-B)= C
C*100/A
D
D*100/C
2014
40
654
127
19.4%
527
80.5%
500
94.8 %
2015
40
578
114
19.7%
464
80.3%
408
87.9 %
Total
80
1232
241
19.5%
991
80.4%
908
90.8 %
Table 3. Fallow deer captures and recaptures by study site, with estimated capture probability (average p-hat) per sampling
occasion under the jackknife model of variable probability of capture (M(h)).
Year
(2014-
2015)
Total Capture
- Recapture
Individuals /
year
Individuals
recaptured
Individual fallow deer census
Average
p-hat
2014
2015
Male
Male Rate
%
Female
Female
rate %
Population
size
Total
80
52
28
15
33
58.75
19
41.25
97 (± 22)
0.51
Turkish Journal of Forestry 2018, 19(1): 57-62
61
Table 4 Results of fallow deer density estimates using the Jackknife and Removal population model M(h) and variable
probability removal estimator in which capture probabilities vary
Jackknife-M(h) Model
Density average
(km2)
Removal-M(bh) model
Density (km2)
SE
Min.
Max.
Average
SE
Min.
Max
Average
6.25
96
120
105
20.1
7.48
97
126
108
20.7
Population Density (95% confidence interval)
4. Discussion
This study was conducted in the EFDBS, Antalya
Düzlerçamı WDA by the department of Wildlife Ecology
and Management at the Faculty of Forestry, Süleyman
Demirel University. In this context, this study will provide
sufficient resources on literature and methodology to the
other similar studies. It was carried out to determine the
population size and density of the fallow deer populations in
the study area. Some similar studies (Arslangündoğdu, et
al., 2010; Saribaşak, et. al., 2005) had been carried out to
determine the population size and density of the fallow deer
population in the study area, but this is the first study in
Turkey which used the camera trap method to determine the
population of fallow deer. The camera trap study and set up
of the stations were achieved after finding the general
distribution of the fallow deer in the area.
A field study of 203 days, including 82 in 2014 and 121
in 2015, was carried out in the area. In these studies, camera
trap station was established and in a certain period of time,
it has been left fixed. In studies carried out in two periods, it
was obtained 3,280 camera trap days in the year 2014 and
4,840 days in the year 2015. In a similar study by Soyumert
(2010), again in Turkey to determine wild animal species by
camera traps, daily camera trap value of 4,142 was achieved
by 55 camera trap stations. Considering the obtained data,
80 different individuals (47 male, 33 female) were identified
in the field. In one of the similar studies, Mcshea et al.
(2011) used camera traps to estimate deer population
densities in Catoktin National Park (24.2 km2) and Antietam
National Park (13.5 km2). Mcshea et al. (2011) placed 20
camera traps in each area with 200 m intervals and collected
data in intervals of 2-5 days. As in various wild animal
species such as lynxes and tigers, fallow deer also have
natural signs. The most obvious of these natural signs are
the spots and antlers. Since the deer are spotted species, the
spot arrangements and the antler structures of each
individual are different from each other, allowing these
individual identification studies to be carried out easily. In
their study, Carbone et al. (2001) also reported that this
method is effective in determining the existence of the wild
species and individuals that are shy or hard to see. In this
way, the method of identification of individuals by means of
the natural signs and morphological features used in the
thesis study has been made easily. As stated by Mengüloğlu
(2010) in his studies, individuals can be identified from its
pattern or spot and suggested that this method could be
effective in individual detection studies in many types of
cats. In the light of the results of this method we used in this
thesis work and considering the previous studies and
projections, it was found that camera traps may be used in
identification of individuals and they may provide easiness
in other methods.
Based on the obtained results, a maximum of 120,
minimum of 96 and average of 105 fallow deer individuals
were found. Additionally, the number of individuals found
in our studies in 2014 and 2015 were based only on adult
individuals and fawns were not taken into account. About
20 fawns were found in the data obtained using camera traps
and Capture-Recapture method provided us with the total
number of adults and fawns as 105 + 20 = 125. According
to these results, fallow deer population density was 20.1 /
km2 in the study area. Kasper et al. (2015), in their study on
leopards in an area of 17,500 ha using the capture-recapture
method with camera traps, identified 21 individuals from
113 records based on the data collected in 2005, and
concluded a population density of 0.26 leopards per 1 km2.
If we compare the results of their study to those of our
study, it may be seen that our results are better and more
reliable.
The most frequently seen problems for camera traps
studies is the failing of some devices. Although batteries
and memory cards were suitable for usage, some camera
traps did not work in any condition. This may have been
caused by the sensor. Considering the image quality in the
camera traps, it is considered that the spots of fallow deer
passing by in close range especially in the dark reflect a lot
of light and this may have decreased image quality. It is
additionally thought that the water resources in the area are
limited and individuals experience scarcity of water in
summer months. Therefore, wet areas such as flowing ponds
should be established to satisfy the water needs of the fallow
deer.
It is not believed that the wire fences around the area can
form a protection element for the entire area. In our walks, it
was seen that the area may be entered from various points
easily and illegal hunting activities may be seen. Necessary
precautions should be taken.
Acknowledgements
The Directorate of Scientific Research Projects
Management Unit at Suleyman Demirel University, which
funded my thesis with the project no. 4122-YL1-14.
References
Anonymous, 2013. T.C. Ministry of Forestry and Water
Affairs, VI. Regional Directorate Antalya Branch
Directorate Archive Records. 2013, Antalya.
Arslangündoğdu, Z., Kasparek, M., Sarıbaşak, H., Kaçar, M.S.,
Yöntem, S., Şahin, M.T., 2010. Development of the
population of the European Fallow Deer, Dama dama dama
(Linnaeus, 1758), in Turkey (Mammalia: Cervidae).
Zoology in the Middle East, 49: 3-12.
Can, Ö.E., 2008. Camera trapping large mammals in Yenice
Forest Habitats: A feasibility study for camera trapping
large mammals in Yenice Forests. PhD Thesis, Middle East
Technical University, 118p., Ankara, Turkey.
Turkish Journal of Forestry 2018, 19(1): 57-62
62
Carbone, C., Christie, S., Confori, K., Coulson, T., Franklin, N.,
Ginsberg, J.R., Griffiths, M., Holden, J., Kawanishi, K.,
Kinnaird, M., Laidlaw, R., Lynam, A., Macdonald, D.W.,
Martyr, D., Mcdougal, C., Nath, L., O’brien, T.,
Sidensticker, J., Smith, D.J.L., Sunquist, M., Tilson, R.,
Wan Shahruddin, W.N., 2001. The use of photographic
rates to estimate densities of tigers and other cryptic
mammals. Animal Conservation, 4: 75–79.
Chao, A., 2001. An overview of closed capture-recapture
models. Journal of Agricultural, Biological and
Environmental Statistics, 6(2): 158-175.
Chao, A., Tsay, P.K., Lin, S.H., Shau, W.Y., Chao, D.Y., 2001.
The applications of capture‐recapture models to
epidemiological data. Statistics in Medicine, 20(20): 3123-
3157.
Chapman N.G., Chapman D.I., 1997. Fallow Deer’s. Their
History, Distribution and Biology. Coch-Y-Bonddu Books,
Machynlleth, Powys, SY20 8DJ. 271 pp.
Connolly, C., 2007. Wildlife Spotting Robots. Volume 27
Number 4 pp. 282-287, Stalactite Technologies Ltd,
Wakefield, UK.
Ducos, P., 1988. Archéozoologie Quantitative. Les Valeurs
Numériques Immédiates à Çatal Hüyük. Les Cahiers du
Quaternaire 12. Éditions du CNRS, Paris.
Foster, R.J., Harmsen, B.J., 2012. A critique of density
estimation from camera‐trap data. The Journal of Wildlife
Management, 76(2): 224-236.
Griffiths M., Schaik, V., 1993. The impact of human traffic on
the abundance and activity periods of Sumatran Rain Forest
Wildlife, Mike Griffiths and Carel P. Van Schaik
Conservation Biology, Vol. 7, No. 3 (Sep., 1993), pp. 623-
626.
González-Pérez, G.E., 2003. Uso del hábitat y área de actividad
del venado cola blanca (Odocoileus virginianus sinaloae J.
Allen) en la Estación Científica Las Joyas, Reserva de la
Biosfera de Manantlán, Jalisco. MS thesis, Universidad
Autónoma de México. México, D.F.
Harmsen, B.J., Foster, R.J., Silver, S.C., Ostro, L.E., Doncaster,
C.P., 2011. Jaguar and puma activity patterns in relation to
their main prey. Mammalian Biology-Zeitschriftfür
Säugetierkunde, 76(3): 320-324.
Heidemann, G., 1976. Damwild, Cervus dama Linné,
1758. Kleinasien. Bestand un Schutz–Säugetierk. Mitt, 24:
124-132.
IUCN (International Union for Conservation of Nature and
Natural Resources) Standards and Petitions Subcommittee,
2016. Guidelines for Using the IUCN Red List Categories
and Criteria, Version 12. Accessed December 10, 2016.
http://www.iucnredlist.org/documents/RedListGuidelines.p
df
Kaçar, M.S., 2002. Fallow Deer population and begüming of
vanish process in Antalya-Düzlerçamı. Journal of South-
West Anatolia Forest Research Institute, 4:1-14.
Kasper, C.B., Mazım, F.D., Soares, J.B.G., Oliveira, T.G.D.,
2015. Density estimates and conservation of Leopardus
pardalis southernmost population of the Atlantic Forest,
Iheringia. Série Zoologia, 105(3):367-371.
Karanth, K.U., Nichols, J.D., 1998. Estimation of tiger densities
in India using photographic captures and recaptures.
Ecology, 79: 2852–2862.
Keuling, O., Neubauer, D., Gräber, R., Brün, J., 2012.
Estimating Wild Boar (Sus scrofa) density using
cameratraps and distance sampling. In Book of abstracts,
9th International Symposium on Wild Boar and Other
Suids, pp. 2-6.
Marker, L.L., Fabiano, E., Nghikembua, M., 2008. The Use of
Remote Camera Traps to Estimate Density of Free ranging
Cheetahs in North-Central Namibia.
Mcshea, W.J., Stewart, C.M., Kearns, L., Bates, S., 2011. Road
bias for deer density estimates at 2 N. P. in Maryland.
Wildlife Society Bulletin, 35(3): 177–184.
Meek, P., Ballard, G., Fleming, P., 2012. An Introduction to
Camera Trapping For Wildlife Surveys in Australia.
Canberra, Australia: Invasive Animals Cooperative
Research Centre.
Mengüllüoğlu, D., 2010. An inventory of medium and large
mammal fauna in Pineforests of Beypazarı through camera
trapping. Graduate Thesis, Middle East Technical
University, Ankara, Turkey.
Orekici-Temel, G., Erdoğan, S., Ankaralı, H., 2012. Usage of
Re-sampling methods to evaluate the performance of the
classification model. Journal of Informatics Technologies,
5(3): 7.
Ortega, J.A., Mandujano, S.S., Villareal, J., Mare M.I.D.,
López-Arevalo, H., Molina, M., Correa-Viana,. 2011. In:
(D. Hewitt, ed.) Biology and management of white-tailed
deer. CRC Press, Taylor and Francis Group. USA. pp. 565–
597.
Rexstad, E., Burnham, K.P., 1991. User’s Guide for Interactive
Program CAPTURE. Abundance Estimation of Closed
Populations. Colorado State University, Fort Collins,
Colorado, USA.
Sarıbaşak, H., Kaçar, M.S., Başaran, M.A., Cengiz Y., Köker,
A., Sert, A., 2005. Fallow Deer (Dama dama L. 1758),
production and placement techniques. Ministry of
Environment and Forestry Publication, No: 267, Directorate
Publication No: 027 Technical Bulletin No: 23, 80 p.
Antalya.
Sevgi, O., Sert, H., Sarıbaşak, H., Karacan, V.A., Mert, A.,
2013. Fallow Deer Species Protection Action Plan. T.C.
Ministry of Forestry and Water Affairs General Directorate
of Nature Conservation and National Parks VI. Regional
Directorate Antalya Branch Directorate, Antalya, 81 p.
Silver, S.C., Ostro, L.E., Marsh, L.K., Maffei, L., Noss, A.J.,
Kelly, M.J., Ayala, G., 2004. The use of camera traps for
estimating Jaguar Panthera onca abundance and density
using capture/recapture Analysis. Oryx, 38(02): 148-154.
Sorıa-Díaz, L., Monroy-Vılchis, O., 2015. Monitoring
population density and activity pattern Of White-Tailed
Deer (Odocoileus virginianus) in Central Mexico, using
camera trapping. Mammalia, 79(1): 43–50.
Soyumert, 2010. Detection and determination of ecological
characteristics of large mammal species by camera-trapping
method in Northwest Anatolia forests. Ph.D. Thesis,
Hacettepe University, Ankara, Turkey.
Trolle, M., Kery, M., 2003. Estimation of ocelotdensity in the
pantanal using capture-recapture analysis of camera
trapping data. Journal of Mammaology, 84(2): 607-614.
Turan, N., 1966. Antalya Forestry Directorate, Düzlercamı
Example Forest Management, Report İnstead Of Fallow
Deer Breeding with the Protection Area.
Ueckermann, E., Hansen, P., 1994. Das Damwild. 3rd
ed. Hamburg: Parey.
Wang, S.W., Macdonald, D.W., 2009. The use of cameratraps
for estimating tiger and leopard populations in the high
altitude mountains of Bhutan. Biological Conservation,
142: 606-613.
