camera trap study on inventory and daily activity patterns of large mammals in a mixed forest in...

Mammalia 76 (2012): 43–48 © 2012 by Walter de Gruyter • Berlin • Boston. DOI 10.1515/MAMM.2011.102

Camera trap study on inventory and daily activity patterns of large mammals in a mixed forest in north-western Turkey

Burak Akbaba * and Zafer Aya s

Hacettepe University , Faculty of Science, Department of Biology (Zoology Section), 06800 Beytepe , Ankara, Turkey , e-mail: [email protected]

* Corresponding author

Abstract

This study aimed to detect the presence and the daily activity patterns of large mammals in a mixed forest in north-western Turkey. Field studies were carried out at 21 camera trap sta-tions with a total sampling effort of 1046 camera trap days, covering an area of approximately 70 km 2 between June 2009 and January 2010. Brown bear ( Ursus arctos ), wolf ( Canis lupus ), Eurasian lynx ( Lynx lynx ), red deer ( Cervus elaphus ), wild boar ( Sus scrofa ), red fox ( Vulpes vulpes ), European badger ( Meles meles ) and European hare ( Lepus europaeus ) were not known to be present in the area. European hare was the most captured species among the others and Eurasian lynx was the most captured carnivore. There was a positive relationship between spatial distributions and daily activ-ity patterns of European hare and Eurasian lynx. European hare, Eurasian lynx and red fox were found to have nocturnal activity in the study area. The number of records between the activity classes (nocturnal and diurnal) did not differ for red deer and wolf. This study revealed the ecological importance of the area by determining both the species present in this area and their activity patterns.

Keywords: Eurasian lynx; European hare; red deer; red fox; wolf.

Introduction

Large mammals have prominent roles in most ecosystems. Large herbivores exert considerable effects on modifying pri-mary production, nutrient cycles, soil properties and fi re regimes (Gordon 2006 ) and large carnivores in turn, with their direct and indirect effects on prey, shape their ecosystems (Sinclair et al. 2003 , Dalerum et al. 2008 ). Determining the presence of large carnivores and herbivores in natural systems is essential for understanding the processes they engender and for planning their conservation and management of the habitats. Large mam-mals naturally occur at low densities according to lower trophic level species, and thus the detection of these species in an area is relatively diffi cult (Manley et al. 2006 ). Therefore many direct techniques, like spotlight surveys (Ruette et al. 2003 ),

road mortality counts (Marks and Bloomfi eld 1999 ), drive counts (Gaidet -Drapier et al. 2006 ), aerial counts (Jachmann 2002 ), hunting statistics (Nyenhuis 2000 ) and sighting and questionnaire surveys (Fuller et al. 1992 ), and indirect tech-niques, like scent-station surveys (Wilson and Delahay 2001 ), fecal counts (Tuyttens et al. 2001 ), track counts (Gusset and Burgener 2005 ) and aural surveys (Robbins and McCreery 2003 ), have been developed and implemented to detect the presence of such species in any particular area. Silveira et al. (2003) stated that despite the variety of fi eld techniques that can be used for terrestrial mammal surveys, all of them can-not be effi ciently applied in every ecosystem or for all species. Although being practical and objective, indirect methods are not always very accurate for the elusive species, while direct methods are expensive and diffi cult because they are time con-suming and logistically demanding.

Camera trapping is a useful tool for determining large mammals in various habitats (Kinnaird et al. 2003 , Silveira et al. 2003 , Yasuda 2004 , Tobler et al. 2008 ). It can be imple-mented in a wide variety of ground and climatic conditions and can be used to collect information on elusive species in diffi cult terrains where other fi eld techniques are likely to fail (Rowcliffe et al. 2008 ). It has been used widely in wildlife studies for identifying the species inhabiting a particular area, monitoring relative and absolute abundances of species, and recording animal behavior (Yasuda 2004 , Kay and Slauson 2008 ). In recent years, camera trapping has become increas-ingly popular as camera technology has improved and equip-ment costs have decreased (Tobler et al. 2008 ).

Can and Togan (2009) pointed out that several large mam-mal species, which are ecologically, economically and scien-tifi cally important, live in Turkey. However, information on these species is very limited and reliable systematic fi eld sur-veys do not exist for most of them. In this study, the camera trap-based inventory and daily activity patterns of large mam-mals in a mixed forest in north-western Turkey was investi-gated to provide data for future conservation and management studies related to large mammals in the area.

Materials and methods

Study area

The study was carried out in Ç aml ı dere- Ç amkoru region (40 ° 34 ′ N, 32 ° 30 ′ E, Figure 1 ), which is located in Ankara Province in north-western Turkey. In the region, forest veg-etation is dominant and it comprises the communities of Quercus pubescens , Pinus nigra subsp. pallasiana , Pinus sylvestris and Abies nordmanniana subsp. bornmuelleriana.

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44 B. Akbaba and Z. Ayas: Camera trapping large mammals in NW Turkey

The vegetation in the study area is under the infl uence of an extremely cold type of the Mediterranean climate, with lim-ited rainfall (Akman and Aydogdu 1986 ). A part of the study area (approx. 215,000 m 2 ) was declared as a “ Nature Park ” in 2008. The altitude of the study area varied between 1200 m and 1850 m.

Camera trap survey

Camera trap surveys were carried out from June 2009 to January 2010 to determine the large mammal fauna using a total number of ten passive infrared cameras (Recon Outdoors, Huntsville, AL, USA). All terrestrial large mammals (weigh-ing over 1 kg) of the orders Carnivora, Artiodactyla and Lagomorpha, which were expected to occur in the area of interest according to the interviews previously conducted with local people, were targeted: brown bear ( Ursus arctos ), wolf ( Canis lupus ), Eurasian lynx ( Lynx lynx ), golden jackal ( Canis aureus ), red deer ( Cervus elaphus ), wild boar ( Sus scrofa ), red fox ( Vulpes vulpes ), European badger ( Meles meles ), European pine marten and/or beech marten ( Martes martes and/or M. foina ) and European hare ( Lepus europaeus ).

Camera traps were placed at game trails and dirt roads where signs of large mammals like tracks or feces were identi-fi ed 1 month before the sampling efforts had begun. The cam-eras were set at an average height of 50 cm above the ground with a focal range (the distance between the camera and the middle of the trail) of 3 – 5 m. Each sensor and camera were housed in a weather-resistant casing, which was mounted on a tree or a hard bush. We checked camera traps every 4 weeks to download the captured pictures and to replace batteries if necessary. We recorded the geographic positions of all the selected camera trap sampling locations by Garmin GPSMAP 60 CSX (Garmin International, Inc., Olathe, KS, USA) and plotted them on the map (Figure 1 ).

The cameras were triggered by sensors detecting heat and motion within a range of a conical infrared beam. The time lag between the animal detection by the infrared sensor and the triggering of the camera was approximately 1 s. The delay between pictures was set to 1 min.

Tobler et al. (2008) reported that the same number of spe-cies was obtained with either 1 or 2 km spacing between sta-tions. For inventories, maximizing potential photographs of all species is paramount and it is likely that camera spacing has little bearing on successful documentation of species present in an area (Kelly 2008 ). Therefore, we placed camera traps approximately 1.5 – 2 km apart to maximize the area that was covered. The distance between the camera traps were kept to < 2 km to prevent missing the species with small home-range size (e.g., fox). During the study, each camera trap was kept for a minimum of 1 month at each station and then moved to a new station for exhaustive inventory (Moruzzi et al. 2002 ). We carried out surveys at 21 camera trap stations with a total sampling effort of 1046 camera trap days, covering an area of approximately 70 km 2 .

Data analysis

We sorted the photographs of the target species based on the assumption that multiple photographs of a species taken at a single camera location within short time intervals (up to 10 min) represented a single individual. We considered such multiple photographs as a single independent “ record ” . This may be explained by the fact that some species (e.g., hare) spend a long period of time in front of a camera. Also, in cases where a photograph contains a group of individuals of the same species (e.g., hares) captured, we defi ned the photo as a single record for that species.

We calculated capture rate for a given species as the num-ber of camera trap records/100 camera trap days (CTD) and

Figure 1 Location of the study area ( Ç aml ı dere- Ç amkoru region, Ankara Province, Turkey) and camera trap stations.


B. Akbaba and Z. Ayas: Camera trapping large mammals in NW Turkey 45

called this the relative capture frequency (RCF). For inter-species comparisons, we separately calculated RCF of cap-tured species in each camera trap station. RCFs of the species were not generally normally distributed (Shapiro-Wilk test), so we used the non-parametric Kruskal-Wallis test to inves-tigate whether RCF signifi cantly differed among species across the area. Then we used linear regressions to compare spatial distributions of prey animals (deer and hare) with car-nivores which have adequate data (wolf, lynx and fox). The same analysis was applied to compare carnivores ’ spatial dis-tributions with other carnivores to determine the avoidance between each other across the area.

We assumed that the number of camera trap records taken at various times was correlated to the daily activity patterns of large mammals. We used the hours printed on the records to describe the daily activity patterns of the species. To analyze the daily activity patterns, the records of target species were tabulated in 2-h intervals. This analysis was performed only for the species with at least ten records for the results to be signifi cantly evaluated (Sanderson 2004 ). The records were classifi ed into two activity classes as either diurnal or noc-turnal depending on the capturing period (06:00 – 17:59 and 18:00 – 05:59, respectively). We performed a χ2 test to deter-mine the signifi cant differences of number of records between the activity classes for chosen species. We used an α value of 0.05 as our signifi cance level. For interspecies comparisons, we calculated only RCFs of spatially correlated species in all intervals separately and we used linear regression analysis to compare daily activity patterns of these species.

We used software STATISTICA (v. 8.0; StatSoft, Inc., Tulsa, OK, USA) for all statistical analysis.

Results

A total of 182 camera trap photographs were evaluated after eliminating the photographs with human or domestic animal presence and empty ones. Among these, 90.66 % of camera trap photographs (165 out of 182) were found to belong to target species and 9.34 % of camera trap photographs (17 out of 182) to belong to unidentifi able and non-target species.

In the study area, photographs of eight terrestrial large mammal species were found to be captured. Of these species, hare was the most frequently captured (78 times; 47.27 % of all target species photographs), followed by fox (23 times; 13.94 % ), deer (22 times; 13.33 % ), lynx (19 times; 11.52 % ), wolf (14 times; 8.48 % ), boar (fi ve times; 3.03 % ), bear (three times; 1.82 % ) and badger (once; 0.61 % ).

The total sampling effort of 1046 camera trap days yielded 114 independent records for further analysis (69.1 % of all tar-get species photographs), resulting in an RCF of 0.11 per 100 CTD (Table 1 ).

The RCF did not vary signifi cantly among species (K-W: H = 11.23; df = 7; p > 0.05). There were no signifi cant relation-ships between spatial distributions of deer and carnivores (p > 0.05 for all binary comparisons). Hare were captured at seven camera trap stations, and there was a signifi cant (but weak) positive relationship between spatial distributions

Table 1 Number of camera trap records of captured large mammal species in Ç aml ı dere- Ç amkoru region, Ankara Province, Turkey.

Species Number of camera trap records

Brown bear 3Wolf 13Eurasian lynx 17Red deer 14Wild boar 5Red fox 11European badger 1European hare 50Grand Total 114

Total number of camera trap days 1046Total capture frequency(camera trap records/camera trap days×100)

0.11

of hare and lynx (n = 21; p = 0.001; y = 1.2612x + 1.6136; r 2 = 0.4450). There was no signifi cant relationship between spatial distributions of carnivores (p > 0.05 for all binary comparisons).

In the daily activity patterns for carnivore species which were recorded at least 10 times, it was observed that wolf was active during the period 20:00 – 08:00, frequently from 00:00 to 08:00. Lynx was active during the period 18:00 – 06:00 and fox was active during the day randomly and frequently from 20:00 to 02:00 (Figure 2 ).

In the daily activity patterns for herbivore species which were recorded at least 10 times, it was observed that deer had a homogeneous distribution in time, presenting at all activity classes and hare was active during the period 16:00 – 08:00, frequently from 20:00 to 24:00 and 04:00 to 08:00 (Figure 3 ).

The number of records between the activity classes was statistically different for hare, lynx and fox ( χ 2 = 20.48; df = 1; p < 0.001, χ 2 = 17.00; df = 1; p < 0.001, χ 2 = 4.45; df = 1; p < 0.05, respectively), indicating that the three species had nocturnal activity. On the other hand, the number of records between the activity classes was the same for deer and it was not sta-tistically different for wolf ( χ 2 = 3.77; df = 1; p > 0.05). There was a signifi cant (but weak) positive relationship between daily activity patterns of hare and lynx (n = 12; p = 0.05; y = 1.4439x + 0.2051; r 2 = 0.3316).

Discussion

Evaluation of the camera trapping data revealed that the study area had a suitable habitat structure for large mammals. The presence of bear, wolf, lynx, deer, boar, fox, badger and hare in Ç aml ı dere- Ç amkoru region was recorded for the fi rst time. We could not capture any marten species and jackal which were also among the target species, although a dead European pine marten was observed in the vicinity of the study area. Recent studies reported that the animal size could have an impact on photograph rates (Kelly 2008 ). In this study, cam-era traps were placed at a height of approximately 50 cm from



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Figure 2 Daily activity patterns of carnivore species with at least ten records: wolf (A), Eurasian lynx (B) and red fox (C). The bars indicate mean relative capture frequency (RCF) of 21 camera trap stations at each time period of the day and the whiskers above the bars indicate standard deviation of the mean.

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Figure 3 Daily activity patterns of herbivore species with at least ten records: red deer (A), European hare (B). The bars indicate mean relative capture frequency (RCF) of 21 camera trap stations at each time period of the day and the whiskers above the bars indicate stan-dard deviation of the mean.

While the RCF of a species may be positively correlated with its abundance, as previously suggested by Tobler et al. (2008) , this relationship may not be used in interspecies rela-tive abundance comparisons for several reasons such as the positive correlation between the body mass of a species and its probability of being recorded by a camera trap, the behav-ioral differences between species and the home range size differences between species. So we could not deduce from the RCF in a total sampling period that a species was less or more abundant than another in the study area. Nevertheless, we considered camera trap stations as independent sampling units and it showed us that RCF did not vary signifi cantly among species.

We obtained similar or higher values of RCF for bear, wolf, badger and hare in comparisons with surveys from areas with a higher protection status (Yaylac ı k Research Forest; Can and Togan 2009 , Dat ç a-Bozburun Special Environmental Protection Area; I lemin and G ü rkan 2010 ). Also Ambarl ı et al. (2010) recently reported that they had obtained one of the fi rst camera trap records for lynx in Turkey from an area

the ground to capture the large-size species. This might have prevented capturing relatively rare and small species like marten in the study area. We found no evidence (tracks, feces etc.) indicating the presence of jackal during the study.


B. Akbaba and Z. Ayas: Camera trapping large mammals in NW Turkey 47

close to Ç aml ı dere- Ç amkoru region and our study proved that this forest and the surrounding area which is rarely used by humans and has limited settlements might provide high vegetation cover and abundant food sources for this cryptic species. All these indicated the ecological importance of the study area.

Unexpectedly, RCFs of boar and fox, which can be observed in all parts of Turkey (Demirsoy 1996 , Aulagnier et al. 2008 ), were found to be much lower in frequency in the area when compared to other studies conducted in Yaylac ı k Research Forest (Can and Togan 2009 ) and Dat ç a-Bozburun Special Environmental Protection Area ( Ilemin and G ü rkan 2010 ). Lynx kills fox (Jobin et al. 2000 ), even though it does not always eat it (Aulagnier et al. 2008 ). The generalist nature of fox makes it exploit effi ciently in very different habitats and it can change its habitat to avoid possible encounters with relatively large predators (Fedriani et al. 1999 ). Due to the presence of lynx, fox was thought to disperse to the areas closer to human settlements located outside the study area. However, wolf predation was the best possible reason for the lower RCF of boar. Jedrzejewska et al. (2000) reported wolves not to respond to growing densities of prey species, other than red deer. Their consumption of other ungulates, particularly the boar, was shaped by densities of deer. Deer was reintroduced to the region in 2007 by The Ministry of Environment and Forestry (Turkey). According to the inter-views with local people, nearly half of the deer were predated by wolves in the previous 2 years and, interestingly, after 2009 wild boar counts had a dramatic decline. Difference in climate (accordingly in food availability), hunting exploita-tion (even though hunting was forbidden in most parts of the area) or a disease might be another reason affecting the RCF of boar.

Activity periods for lynx, fox and hare were found to be similar to those reported previously in the literature. Lynx was strictly nocturnal without any captures during daytime. Lynx activity is often unequivocally related to the hunting behavior (Jedrzejewski et al. 1993 ). The results of our lin-ear regression models indicated that there was a signifi cant positive relationship between the spatial distributions and the daily activity patterns of hare and lynx. Therefore, hare was thought to be one of the main food sources of lynx. As a result, lynx ’ s activity period was related to the nocturnal habits of its main prey. Fox is known to be primarily noctur-nal, becoming active at twilight and foraging until sunset; although it may occasionally be active during the daytime when undisturbed (Macdonald and Reynolds 2004 ). In the study area, its frequent activity near sunset and daytime seemed to be related to the night activities of relatively large predators, especially lynx, to reduce the risk of being killed.

Wolf is thought to have adopted a nocturnal lifestyle to avoid human confrontation (Theuerkauf et al. 2003 , Aulagnier et al. 2008 ). However, we found that the num-ber of records did not statistically differ between activity classes. Deer is known to be one of the main preys of wolf (Jedrzejewska et al. 2000 ). Meng ü ll ü o g lu and Bilgin (2010) also conducted a study in Ankara Province and reported

no signifi cant relationship between wolf and deer activ-ity, which was in accordance with our linear regression models. It is known that wolf can be active in daytime in winter months despite human activity (Ciucci et al. 1997 ). However, as a result of observed daytime activity of wolf in summer months, wolf activity during both day and night may be due to the lack of human disturbance. Deer is report-edly active mainly at near sunrise and sunset (Aulagnier et al. 2008 ). In our study area, deer had a homogeneous dis-tribution in time, presenting activity in all activity classes. Because of the reintroduction mentioned above, we thought that it had not fully adapted to the region. Therefore, fi nd-ings from previous studies on this species were thought not be applicable in the study area.

Our study provided data for future conservation and man-agement studies for large mammals in Ç aml ı dere- Ç amkoru region. Noteworthy records of mammals found in the study area demonstrated the importance of the study itself and the need for better protection planning of the area.

Acknowledgements

Camera traps and legal permission required for the study were provided by The Ministry of Environment and Forestry, General Directorate of Nature Protection and National Parks (Turkey). The authors would like to thank Cemal Akcan, Burak Tatar and Fehmi Ar ı kan from General Directorate of Nature Protection and National Parks (Ministry of Environment and Forestry) for providing the necessary support to make this study possible and the colleagues Duygu Y ü ce, Baran Yogurt ç uoglu, Seyma Bilgen, Yasin Ilemin and Okan Ü rker for their assistance in the fi eld. This study was part of the MSc thesis of Burak Akbaba submitted to Hacettepe University.

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Received April 27, 2011; accepted November 10, 2011


camera trap study on inventory and daily activity patterns of large mammals in a mixed forest in...

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