howling behaviour exhibited by canids is proposed to function as a deterrent to conspecifics in order to maintain territories (Jaeger et al. 1996). The howling ...
The impact of anthropogenic disturbance on the behaviour and ecology of the golden jackal (Canis aureus) Lisa Bulmer
MSc Ecology and Environmental Management, 2015
Department of Biology at the University of York
Acknowledgements Many thanks to Archipelagos Institute of Marine Conservation for enabling me to conduct this research. I would like to thank Kelly Redeker and Anna Gardner for their guidance and support during the project. In addition, I would like to thank Emma Rand and Ruth Cox for their statistical analysis assistance.
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Abstract How anthropogenic disturbance impacts animal behaviour has become recognised as a critical issue, due to global increase in development and diversification of human activities. Urbanisation poses a major threat to the golden jackal (Canis aureus) in Greece by creating disturbances and possible habitat reduction. Additionally, increased road traffic due to anthropogenic developments and tourism increases the risk of jackal-vehicle collisions, which is of great concern to human safety and to the protection of the jackal population. There is a lack of research investigating the trade-off between animals exhibiting behaviours to avoid anthropogenic threats and other fitness-enhancing behaviours. Here, the impact of such anthropogenic pressures on the foraging behaviour and distribution of jackals was examined through the use of bioacoustic surveys and camera trap surveys. Linear mixed effects models and general linear models were used to document associations between variables related to the ecosystem (altitude and temperature), human disturbances (proximity to towns, proximity to main roads, and road traffic frequency), and the presence, distribution, and space use of jackals. Proximity to towns and main roads was found to significantly influence the number of jackals in an area, with an increase observed in jackal group size closer to towns and main roads. Jackals were found to adapt to anthropogenic disturbances by accessing urban areas as a group, as opposed to individually. Therefore urban areas were not avoided by jackals and instead were incorporated into their territories. Jackal foraging behaviour was not significantly influenced by proximity to main roads; this indicates that the increased mortality risk and disturbance posed by high traffic roads did not disrupt jackal foraging activity. This study demonstrates how jackals spatially utilise their environment at night, providing information that can be used by conservation enforcement groups to identify areas for protection to benefit the jackal population.
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Contents 1. Introduction…................................................................................................4 1.1 Anthropogenic disturbance…………………………………………………………...4 1.2 Current threats…………………………………………………………………………5 1.3 The golden jackal in Greece………………………………………………………….6 1.4 Surveying techniques………………………………………………………………….8 1.5 Study objectives………………………………………………………………………..9
2. Material and Methods……………………………………………………………9 2.1 Acoustic surveys…………………………………………………………………….....9 2.1.1 Study sites……………………………………………………………………………9 2.1.2 Data collection……………………………………………………………………...11
2.2 Camera trap surveys…………………………………………………………………12 2.2.1 Study sites…………………………………………………………………………..12 2.2.2 Data collection……………………………………………………………………...12
2.3 Data Analyses………………………………………………………………..............13 2.3.1 Acoustic survey data analysis…………………………………………………….13 2.3.2 Camera trap survey data analysis………………………………………………..14
3. Results…………………………………………………………………………….15 4. Discussion………………………………………………………………………..23 4.1 Conclusion…………………………………………………………………………….26
References……………………………………………………………………………27 Website References……………………………………………………………………...33
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1. Introduction Human activity is globally recognised to have negative environmental impacts. These impacts range from altering climate and habitat structures, to changing ecosystem functions and species distributions (Levinsky et al. 2007). Mediterranean ecosystems are rich in wildlife species and habitats; however they are influenced by increasing anthropogenic pressures, particularly in lowland and coastal areas (Sokos et al. 2013). Furthermore, increasing effects of climate change are predicted to increase the vulnerability of the Mediterranean basin by further ecosystem loss (Metzger et al. 2008). Due to the development and diversification of human activities, the impact of disturbance on animal behaviour has become recognised as a critical issue in need of research (Marchand et al. 2014).
1.1 Anthropogenic disturbance Augmentation of human populations has led to increases in human presence in many areas that are important for conservation (Gill and Sutherland 2000). In the past decade, the impact of human presence on wildlife has gained interest, with a major concern being potential fitnessreducing animal responses (Gill and Sutherland 2000). For example, there is potential for the impacts of habitat loss or degradation to be similar to those of human disturbance, through animals avoiding or under-using such areas. Therefore, the impacts from each pressure may produce analogous responses. One of the primary studies investigating animal responses to human disturbances proposed that human disturbance and predation risk are perceived similarly by animals, thus animals respond in a similar manner to both threats (Frid and Dill 2002). This theory was developed from an experiment in which Thomson’s gazelles (Gazella thomsoni) were approached by a car to test the factors that influence the distance of flight initiation (Walther 1969). This experiment was then repeated with wild dogs (Lycaon pictus) and showed that the factors influencing responses to a car were similar to those influencing responses to an actual predator stimulus (Walther 1969). This hypothesis is developed from the principle that antipredator responses in prey have evolved to be triggered by generalised threatening stimuli, such as rapidly approaching objects and loud noises (Dill 1974a; Dill 1974b). Further studies found that human disturbance and predators produce the response of time and energy being diverted from other fitness-enhancing activities such as mating displays, foraging, or parental care (Frid and Dill 2002). Therefore animals experiencing disturbances ranging from high levels (a passing motorcycle) to low levels (a mountain hiker) should follow the same economic principle used when encountering a predator (Berger et al.1983). A trade-off occurs between the risk of encountering humans and the benefit of carrying out fitnessenhancing behaviour (Lima 1998; Marchand et al. 2014). Pink-footed geese (Anser brachyrhynchus) demonstrate this trade-off by moving to forage in fields far from roads that
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frequently disturb the geese, which results in up to 64% of the food source going uneaten (Gill and Sutherland 2000). Researching such trade-offs can be used to determine the extent to which anthropogenic disturbance influences animal ecology (Gill and Sutherland 2000). Previous studies have proposed that areas associated with greater danger and richer resources are less frequently visited by animals than areas with reduced danger (Frid and Dill 2002). This theory is consistent for a wide range of taxa including fish, ungulates, and small mammals (Edwards 1983; Gilliam and Fraser 1987; Berger 1991). These studies follow the principle that habituation to disturbance stimuli is often partial (Burger and Gochfeld 1990; Steidl and Anthony 2000) or negligible (Berger et al. 1983; Bleich et al. 1994), due to the cost of underestimating danger having a much greater fitness consequence than the cost of diverting time and energy from other fitness-enhancing activities (Bouskila and Blumstein 1992). The time and energy diverted from fitness-enhancing activities can lead to increases in energetic costs. For example, killer whales (Orcinus orca) have been found to alter their provision of energy when disturbed by boat presence, leading to reduced time spent feeding (Williams et al. 2006). This can have negative consequences on an individual’s health or reproductive success. For example, Amo et al. (2006) found that the presence of increased tourism resulted in reduced body condition of common wall lizards (Podarcis muralis) and increased host-parasite relationships. Also, lower reproductive rates in California sea lions (Zalophus californianus) due to increased human presence were reported by French et al. (2011). Developing an understanding of the impact of human activities on animal behaviour would enable researchers to predict habitat shifts and changes in population dynamics (Gill et al. 1996; Gill et al. 2001); this is crucial information for species management decisions to be made in order to conserve vulnerable species (French et al. 2011).
1.2 Current threats A globally increasing threat to wildlife is urbanisation that can attract individuals by providing resource benefits, though individuals may not perceive the associated risks (Delibes et al. 2001). In human-altered environments, such maladaptive behaviour may be prevalent due to the risks being different from those experienced in an animal’s evolutionary history (Delibes et al. 2001). Urbanisation involving land-use changes and developments often requires the construction and extension of road networks, as well as increased traffic in areas that were previously wild. Roads can act as barriers to animal movement and can lead to fragmentation and edge effects being observed across a landscape (Jensen et al. 2014). Nocturnal animals are at increased risk of animal-vehicle collisions, due to motorists’ ability to detect animals being impaired at night (Mastro et al. 2010). Animal-vehicle collisions are a serious problem that can result in injury and death to humans and animals, as well as property damage (Foster and Humphrey 1995). Developing an
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understanding of animal movements and their use of roads can be useful for forming habitat management strategies (Litvaitis and Tash 2008). Recent research documented that areas of high anthropogenic activity discouraged wolves (Canis lupus) and cougars (Puma concolor) from ranging in close proximity to such activity during the day and instead move closer at night (Hebblewhite and Merrill 2008; Knopff et al. 2014). Crooks (2002) found that large-bodied carnivores in coastal California with specialist habitat requirements were negatively impacted by habitat fragmentation, whereas generalist urban mesopredators were more abundant in small fragments and were proposed to benefit from the anthropogenic resource subsidies available. Alternatively, studies have shown that roads can facilitate animal movement and be incorporated into predator hunting grounds by improving access to habitats that are structurally complex (Červinka et al. 2013). Benson et al. (2015) proposed that canids can exploit the beneficial attributes of roads while mitigating the anthropogenic mortality risk. Developing an understanding of how animals utilise their habitat and interact with high-traffic roads would provide insight into the trade-off between the risk of animal-vehicle collisions and the benefit that accessing such areas provides.
1.3 The golden jackal in Greece Anthropogenic pressures and environmental changes, including land-use changes, urbanisation, barriers and forest fires, have been associated with a significant decline in the golden jackal (Canis aureus) population across Greece (Figure 1) (Krystufek et al. 1997; Giannatos et al. 2005; Ćirović et al. 2014). Such land altering processes and disturbances can negatively impact fauna through changing vegetation structure, resulting in reduced food and shelter resources and reduced habitat connectivity (Robinson et al. 2013; Bar-Massada et al. 2014). In addition, interand intra-specific competition may increase, leading to reduced population sizes (Hagen et al. 2012). This can ultimately impact community ecosystems by altering their composition and processes, as well as species’ ability to adapt to environmental changes and disturbances (Reyers 2004).
A)
B)
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The jackal has become the most rare canid species in Greece and is listed as “vulnerable” in the Red Data book for Greek vertebrates (Giannatos et al. 2005). Golden jackals in Europe show a preference for agricultural land and wetlands that have adequate cover and low elevations (Deinet et al. 2013); however, increasing urbanisation and tourism is reducing the availability of such habitats (Fuller et al. 2015). The jackal is an elusive species that is timid around humans, thus the species is primarily nocturnal and under high risk of vehicle collisions at night (Tóth et al. 2009). Other threats include persecution of jackals through the use of poison and hunting of wild boars (Sus scrofa) in which jackals are often mistakenly shot (Giannatos 2004; Debnath and Choudhury 2013). Understanding the influence of anthropogenic pressures on species and communities through the use of behavioural experiments can enable predictions of animal responses to disturbances to be made with greater confidence than in the case of higher-level processes (Sutherland and Gosling 2000; Creel et al. 2001). This can also allow thresholds of changes that may lead to degradation or irreversible transitions to be set, providing useful information for monitoring population status. The golden jackal is a top-predator in Samos and regulates ecosystem trophic structures, thus is of ecological importance (Doherty et al. 2015). Over the past 200 years range and population declines have been experienced by most top-predators across the globe, due to anthropogenic drivers (Ripple et al. 2014). Studies have shown that in areas where dingoes (Canis dingo) are poisoned, cat (Felis catus) and fox activity is increased due to a lack of invasive mesopredator regulation by the dingo (Brawata and Neeman 2011). Declines in the jackal populations on Samos may lead to increases in mesopredator and herbivore populations due to their release from top-predator suppression (Johnson et al. 2007). Invasive rat populations can be
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supported by resource subsidies found in urban areas (Ruffino et al. 2012); however such rodent populations can be controlled by the presence of jackals that act as a ‘cleaner’ of nature by preying on rodents and reducing organic waste. The jackal prevents disease transmission by removing garbage and dead animals, and benefits humans by feeding on animals that damage crops. The benefits that the presence of jackals provides demonstrate the importance of establishing longterm coexistence between jackals and humans.
1.4 Surveying techniques The ecology of canid species has been previously examined through bioacoustic research. This utilises the vocalisation behaviour of canids to locate groups, estimate group and range sizes, and determine the factors that influence behavioural responses (Robbins and McCreery 2003). Studies have included the use of playbacks to survey wolves (Joslin 1967), African wild dogs (Lycaon pictus; Robbins and McCreery 2003), spotted hyenas (Crocuta crocuta; Mills 2001), arctic foxes (Alopex lagopus; Frommolt et al. 2003), and lions (Panthera leo; Smuts et al. 1977). Group howling behaviour exhibited by canids is proposed to function as a deterrent to conspecifics in order to maintain territories (Jaeger et al. 1996). The howling covers sufficiently long distances and advertises the groups’ location as an area to be avoided (Joslin 1967). There is a lack of research investigating the long-ranging vocal behaviour of small canids and where such species prefer to establish territories (Darden and Dabelsteen 2008). Obtaining reliable and accurate information regarding the status of the jackal is vital for the conservation of populations through their recovery, reintroductions, or management (Gese 2004). Furthermore, wildlife surveys using camera traps have been used extensively to conduct population estimations and monitoring, though recent studies have used this method to investigate behaviours of elusive animals (King 2013; Krishnappa and Turner 2014). Studies have included the use of camera traps to survey red foxes (Vulpes vulpes; Sarmento et al. 2009), wildcats (Felis silvestris; Can et al. 2009), and elk (Cervus elaphus; VerCauteren et al. 2007). Camera trapping techniques have great potential for improving understanding of how jackals utilise and behave within their habitat at night. Behavioural studies can provide essential new insight into conservation problems (Sutherland and Gosling 2000), enabling conservation strategies to be amended and improved.
1.5 Study objectives The impact of anthropogenic disturbance and urbanisation on the behaviour and ecology of jackals on Samos, Greece, will be examined. Field experiments will be conducted using a widely accepted acoustic method of census to test the study predictions, along with observational data of foraging behaviour and space use collected using camera traps. The first hypothesis is that jackal
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presence and distribution will be influenced by proximity to towns and main roads. It is predicted that increasing distance from towns and main roads will result in an increase in jackal presence and an increase in the number of individuals; this is due to their timid nature and avoidance of human disturbance (Tóth et al. 2009), as well as the increased available habitat in rural areas. The second hypothesis is that road traffic frequency will influence jackal presence and distribution. It is predicted that temporal variation will be observed in both road traffic frequency and jackal foraging activity, with a peak in traffic frequency expected to be observed in the middle of July to August, due to this period being the prime tourism season. A trend is expected in which a decrease in the time spent and number of jackals observed in close proximity to main roads will be associated with an increase in traffic frequency due to the increased mortality risk and disturbance, thus disrupting jackal foraging activity. Therefore, it is predicted that jackals will exhibit behavioural plasticity to adapt to anthropogenic disturbances and maintain fitness.
2. Material and Methods 2.1 Acoustic Surveys 2.1.1 Study sites Areas that had adequate vegetation cover and low elevations were selected for acoustic survey sites. Seven sites had been surveyed in 2011 and 2013 respectively by Archipelagos Institute of Marine Conservation that were selected by analysing habitat suitability and through discussions with a golden jackal expert (Giannatos, personal communication). This study used these seven sites in addition to six other sites (Figure 2) that were selected by analysing habitat suitability to increase the sample size for the calling surveys. Habitat suitability was assessed by examining land altitudes, vegetation coverage, and the countrywide jackal acoustic survey sites that have been used by WWF Greece for a 25 year period (Giannatos 2004). The sites were selected with vantage points that had limited obstructions to maximise sound dispersal and all sites had similar vegetation structure to mitigate differences in sound penetration distances (Plate 1). The acoustic ranges of the selected sites did not overlap with one another (>1.6 km apart) to increase the land surveyed in order to maximise jackal group detection. Also, the sites were an appropriate distance away from the camera trap sites (>1.7 km) to ensure that the two experiments would not interfere with each other. Sites were visited on a biweekly basis to reduce jackal familiarisation with the playback. Altitude, road connections and proximity to urbanisation varied between sites, providing diversity among sites for comparison during statistical analyses.
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9 10
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Plate 1.Two of the sites selected for acoustic surveying in Samos, Greece. The landscape in each site includes similar vegetation structure to mitigate differences in sound dispersal across all sites and limited obstructions to maximise sound dispersal. The sites also included sloping hills that shape sound projection (Pijanowski et al. 2011).
2.1.2 Protocol and data collection Jackal howls were recorded using a portable, battery-operated, Olympus digital voice recorder WS-750M with a directional audio amplifier with windshield. The recording was used as a playback during experimental trials to simulate the intrusion of an unknown jackal group into a pair’s home range (Darden and Dabelsteen 2008; Krofel 2008). Experimental trials began one hour after sunset. At each site an initial background noise reading was recorded using a sound level meter SL-5868P with windshield. The jackal howl recording was then broadcasted for 30 seconds using a megaphone, rotating slowly at 360o to allow the sound to cover the entire site area,
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followed by three minutes of silence during which observers listened for responding jackal howls. The broadcast and silence was repeated three times at each site. Previous studies investigating social and vocal carnivores have used similar methods extensively (McCarley 1975; Harrington and Mech 1982; Jaeger et al. 1996; Mills et al. 2001; Giannatos 2004; Krofel 2008). During each survey the start time, presence or absence of jackal response, time taken for response, direction of response, an estimation of the distance to responding jackal group, and the number of individuals and groups responding were recorded. A single response consisted of a jackal making one or more howls from the same location (Darden and Dabelsteen 2008) and individuals were identified by differences observed in call intonation. At every site the altitude, estimated distance and direction of nearest town, and estimated distance to nearest main road were recorded. Surveyor’s hearing capacity was determined as having a threshold of up to 2 km on windless nights through trials that involved broadcasting the recorded playback and traveling away from the playback origin, across land with similar vegetation coverage to that of the survey sites. At the point that the playback was no longer heard, the average distance reached was calculated. The maximum distance for attracting jackals has been previously determined as 1.5 km and an audible response from jackals is estimated to cover an area of up to 12.5 km (Gese 2004; Giannatos et al. 2005). Nights that had poor weather conditions (very windy or raining) were avoided as this would severely limit the observers’ hearing capacity and may disturb animal responsiveness. Each week calling surveys were conducted for two nights, with a maximum of four sites being surveyed in one night. To ensure sampling was consistent and standardised the method employed was the same at each site throughout the study period, which increased the reliability of the data and enabled comparisons between sites to be conducted. The acoustic surveys were conducted in May, June, July and August 2015 for 12 weeks, with between 3 and 7 sites surveyed each week (65 surveys in total).
2.2 Camera Trap Surveys 2.2.1 Study sites Areas with adequate vegetation coverage and low elevations were selected for camera trap survey sites. Three transects were selected by observing for signs of jackal presence through finding tracks and/or scat. In addition, areas that had a fresh water source and/or fruit plants were likely to be incorporated in jackal ranges and were considered as a possible transect. Each transect ran perpendicularly through a main road. Three points on each transect were used to set up a camera trap: approximately 30 m, 100 m, and 300 m distance from the road.
2.2.2 Protocol and data collection 11
Two infrared motion triggered cameras were used: a RECONYX HyperFire HC 500 camera that was set to capture five consecutive photographs when triggered, and a Bushnell HD trophy Max 119476 camera that was set to record one minute of video footage when triggered. The cameras were programmed to record the date and time for every image/video taken. Each camera was placed approximately 5 m away from a lure of raw meat (~200 g of chicken, beef, or pork) that was placed on a tree or rocks at an accessible height to jackals (1 km from main roads and > 1 km from towns (Figure 3). Surveys conducted in the south and east of Samos observed jackal responses from a further distance than in other study sites.
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Figure 3. The observations of all jackal responses during acoustic surveys across south-east Samos, Greece, and the estimated locations of jackals in relation to main roads and settlements.
T he
minimum adequate binomial general linear model examining the impact of main roads on jackal presence did not include any other explanatory variables, whereas the model examining the impact of towns also included study week and time of survey as explanatory variables (Table 3). Proximity to main roads did not have a significant effect on the probability of jackal presence (x2 = 0.60; d.f. = 78; p =0.60) (Figure 4; Table 4). The odds of jackal presence increased by a factor of 0.90 every kilometre increase in distance from main roads, but this was not significant. In contrast, proximity to towns had a significant effect on the probability of jackal presence (x2 = 0.90; d.f. = 78; p=0.03) (Table 4), with the odds of jackal presence increasing by a factor of 5.25e+31 every kilometre increase in distance from town. A significant interaction was observed between proximity to towns, study week, and time of survey (x2 = 0.01; d.f. = 72; p=0.01) (Figure 4; Table 4).
Table 3. The binomial general linear models of the acoustic survey data. * indicates the minimum adequate model. Explanatory
Model
AIC
variables
Full model p value
1
A+B+C+D+E
114.18
0.13
2
A*C*D*E
115.58
0.08
3
A+C+D+E
112.29
0.14
4
A+C
111.14
0.84
5
A
110.54*
0.06
6
B*C*D*E
113.39
0.28
7
B*C+D+E
109.37
0.05
8
B*C*D
104.68*
0.09
9
B*C
108.81
0.11
*The explanatory variables are: A = proximity to main road, B = proximity to town, C = study week, D = time of survey, E = altitude. Where + indicates association between explanatory and response variables and * indicates the interaction between variables.
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A)
B)
Figure 4. A) The probability of jackal presence in relation to proximity to main roads (Table 3, Model 5). B) The probability of jackal presence in relation to the interaction between proximity to towns, study week, and time of survey (Table 3, Model 8).
Table 4. The minimum adequate binomial general linear models that explain the response variable jackal presence. Explanatory variables A
B*C*D
Variable effect
Odds ratio
P value
A = negative
0.90
0.60
B = positive
5.25e+31
0.03
C = positive
8.73e+09
0.03
D = positive
2.54e+62
0.09
B*C = negative
1.16e-05
0.02
C*D = negative
8.39e-12
0.03
B*D = negative
2.33e-36
0.03
B*C*D = positive
3.32e+05
0.01
*The explanatory variables are: A = proximity to main road, B = proximity to town, C = study week, D = time of survey. Where * indicates the interaction between variables. Odds ratio indicates the factor by which the expected probability of presence increases when the value of the covariate increases by one unit.
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The minimum adequate linear mixed effects model examining the impact of main roads on jackal density did not include other explanatory variables (Table 5). Similarly, the model examining proximity to towns did not include other explanatory variables (Table 5). Proximity to main roads had a significant effect on the density of jackals (x2 = 6.29; d.f. = 1; p = 0.01) (Figure 5; Table 5). The number of jackals was approximately 0.11 ± 0.14 less for every kilometre decrease in proximity to main roads. Proximity to towns had a significant effect on the density of jackals (x2 = 6.10; d.f. = 1; p=0.01) (Figure 5; Table 5). The number of jackals was approximately 0.09 ± 0.23 less for every kilometre decrease in proximity to towns.
Table 5. The linear mixed effects models of the acoustic survey data. * indicates the minimum adequate model. Model 1
Fixed effects A, B, C, D, E
269.5
AIC
Full model p value 2.96
2
A, B, D, E
267.5
0.94
3
B, D, E
266.6
0.29
4
B, D
264.8
0.71
5
B, E
270.8
0.01
6
B
268.9
0.01*
7
A, D, E
265.8
0.62
8
A, D
264.3
0.47
9
A, E
270.4
0.01
10
A
268.6
0.01*
*Where the fixed effects are: A = proximity to main road, B = proximity to town, C = study week, D = time of survey, E = altitude. The random effects in all models are average traffic frequency and study site.
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A)
B)
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Figure 5. The relationship between the number of jackals and A) proximity to main roads (Table 5, Model 10) and B) proximity to towns (Table 5, Model 6) in Samos, Greece.
Investigating the foraging behaviour of jackals in relation to road proximity enabled any significant influence of road presence and road traffic frequency on jackal behaviour to be determined. Camera traps were deployed at each distance (30, 100, 300 m) a total of 27 times (n=81). The minimum adequate linear mixed effects model for both response variables (number of jackals and accumulative time jackals spent in the camera trap area) included time jackal was initially detected and proximity to main road as fixed effects (Table 6). Table 6. The linear mixed effects models of the camera trap survey data. * indicates the minimum adequate model.
Fixed effects A, B, C, D
When response is number of jackals Full model p AIC value 200.9 0.17
When response is the accumulative time jackals spent in the area Full model p AIC value 387.1 0.09
2
A, B, D
200.9
0.16
386.0
0.35
3
A, B
226.9
0.07
423.4
0.58
4
A, D
200.6*
0.20
386.0*
0.16
Model 1
*Where the fixed effects are: A = proximity to main road, B = study week, C = temperature, D = time jackal was initially detected. The random effects in all models are average traffic frequency and study site.
As the study weeks progressed, the average road traffic frequency increased gradually from 84 ± 4.00 to 148 ± 2.00 vehicles passing in a half hour period at the onset of jackal foraging activity. Proximity to main roads did not have a significant effect on the density of jackals (x2 = 1.63; d.f. = 1; p = 0.20). The number of jackals was approximately 0.21 ± 0.24 greater at 30 m than at 100 m, and approximately 0.45 ± 0.24 greater at 30 m than at 300 m, but this was not significant. Also, proximity to main roads did not have a significant effect on the accumulative time jackals spent in the area (x2 = 1.96; d.f. = 1; p = 0.16). The accumulative time jackals spent in the
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area was approximately 0.17 ± 0.86 greater at 30 m than at 300 m, and approximately 0.88 ± 0.85 less at 30 m than at 100 m, but this was not significant. No significant trend was observed between the number of jackals and proximity to road with fluctuations notable across the study period (Figure 6A). At 30 m and 300 m distance from the main road, an increase in the number of jackals detected was observed between week four and six, and within this period the number of jackals detected at the sites 100 m from the road also displayed an increase (Figure 6A). Also, no significant trend was observed between the accumulative time jackals spent in the study area and proximity to road, showing fluctuations as the study progressed (Figure 6B). Sites at 100 m distance from the main road showed the greatest fluctuations, with the accumulative time spent in the area varying from two to twelve minutes. All sites at the three tested distances showed an increase at week four followed by a decrease at week five in the accumulative time jackals spent in each area (Figure 6B).
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A)
Distance / m
B)
Distance / m
Figure 6. A) The relationship between the number of jackals observed and study week and tested distance from a main road. B) The relationship between the accumulative time jackals spent in the camera trap area and the study week and tested distance (Table 3, Model 6) (Wickham 2009; Fox and Weisberg 2011).
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4. Discussion Here I show that anthropogenic disturbance impacts the behaviour and ecology of the golden jackal. The acoustic survey observations showed that towns significantly influence the probability of jackal presence and that both towns and main roads significantly influence the number of jackals utilising the area. Larger jackal groups were observed with increasing proximity to towns and main roads; however, in accordance with the study predictions, the probability of jackal presence decreased with increasing proximity to towns. These results may be due to the timid nature of jackals, thus jackals were found to approach towns as part of a group rather than as an individual, therefore increasing safety (Tóth et al. 2009; Bijleveld et al. 2015). Additionally, group living may be promoted by spatiotemporal variation in resource availability in close proximity to towns and main roads (Baker et al. 1998). The clustered observations of jackals in north-east Samos are proposed to be related to the increased availability of resources in close proximity to towns, in comparison to the south and south-east where resources may be more available in rural environments. Jackals have been found to exhibit tolerance to human and road disturbances in Central Africa, which is in agreement with this study’s results (Vanthomme et al. 2013). Further studies examining the interaction between jackals and environmental features and resources are needed to investigate jackal spatial movements across a landscape. A limitation to this study was that the acoustic survey technique can underestimate the number of jackals in study areas. An absence of jackal response during acoustic surveys may not translate to an absence of jackals, but may indicate an absence of established territorial groups (Giannatos 2004). Additionally, exhibiting territoriality can have a cost to individuals through exposing their location (Darden and Dabelsteen 2008). For example, during the denning season jackals risk advertising the location of their dens to rival conspecifics, which increases the vulnerability of their young (Jaeger et al. 1996). Variation is likely to be exhibited within populations and between sexes, which will depend on the benefits of holding a territory in particular seasons and on the encounter type experienced (Darden and Dabelsteen 2008). This trade-off is exhibited by male Tungara frogs (Physalaemus pustulosus) that chorus to attract potential mates, but this also attracts predatory bats (Trachops cirrhosis) (Frid and Dill 2002); thus reducing chorusing behaviour for safety has the cost of postponed access to mates (Ryan 1985). In addition, this technique involves human error when estimating responding jackal location and is labour intensive, which limits the number of surveys that could be conducted each night. Although, the high number of jackal responses (approximately 75% of surveys) observed in this study and the significant interaction between time of survey with other variables in relation to jackal presence suggests that the time period that the surveys were conducted and the duration of each survey influenced the chances of jackal responses. This contrasts with a similar study that observed wolves responding approximately 13% of the occasions a howl playback was broadcasted (Joslin 1967). This
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difference in survey effectiveness may be due to disparities in study areas, the species tested and the population sizes. Furthermore, the presence of noise pollution at sites in close proximity to main roads and settlements can reduce surveyor hearing capacity, thus limiting the ability to detect distant jackal responses. However, in this study the sites with the highest sound level reading recorded jackal responses up to 1 km away, thus background noise was unlikely to be a limiting factor here. Nevertheless, the acoustic surveying technique has many advantages, such as being quick, simple, and inexpensive, and is proposed to be an effective tool for canid conservation research (Robbins and McCreery 2003; Giannatos et al. 2005). An area for future research is to examine jackal responses to different recorded jackal call playbacks, which may provide greater understanding of social interactions. Similar studies have been conducted with swift foxes (Vulpes velox) (Darden and Dabelsteen 2008) and arctic foxes (Frommolt et al. 2003). This study also reported that jackal foraging behaviour was not significantly influenced by proximity to main roads or road traffic frequency, which contrasts with the study expectation. A previous study found that jackal foraging activity was influenced by proximity to urbanisation due to the increased predictability and availability of resources (Rotem et al. 2011), though this study did not test the impact of roads on jackal behaviour. The consistent increase in road traffic frequency from June to August corresponds with the prediction that traffic frequency will peak in the middle of July to August. However a trend was not observed between this traffic increase and the time spent and number of jackals observed at study sites, which indicates that jackals were not influenced by traffic frequency. In accordance with these results, other studies have found that the density or presence of the side-striped jackal (Canis adustus) was not found to be significantly associated with road variables including road type and traffic level (Vanthomme et al. 2013). Traffic volume has also been shown to have no association with the location of deer-vehicle collisions (Bissonette and Kassar 2008). Conversely, a study examining animal collision rates found that traffic volume had the highest influence on collision rates; however this study only examined Blanding’s turtles (Emydoidea blandingii), bobcats (Lynx rufus) and moose (Alces alces), which does not represent every taxa (Litvaitis and Tash 2008). The camera trap survey was limited by the availability of cameras, which resulted in a reduced sample size to that proposed in the study objectives. Also the cameras lacked reliability, for example on several occasions the cameras did not capture the removal of the meat lure and these could not be included in the data set. Additionally, the non-significant influence of road traffic frequency on jackal behaviour may be due to the limited number of jackal territories the study incorporated, which reduces the reliability of this data. Therefore, future studies should use more sites and set up more than one camera at each site where possible. This would increase the reliability of the data collected and enable more areas to be surveyed to increase sample size.
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The fluctuations observed in jackal foraging activity across the study period may be related to the reproductive cycle, for example pups were only observed at sites 100 m from the main road and at this distance increases in time spent and number of jackals were documented from week six to eight. It is likely that dens were present in close proximity to these sites, however further research is needed to determine whether or not road presence and traffic frequency influence the location of dens. Another area for future research is to investigate the impact of anthropogenic disturbance throughout the year, as the scale of impact may alter across the breeding and nonbreeding seasons (Gill and Sutherland 2000). Here, the surveys were conducted during the period when mating pairs are rearing cubs and, as the study progressed, more responses were observed during acoustic surveys, which may be due to the maturation of the cubs reducing their vulnerability and the need for increased group communication during night activity (Moehlman 1987; Giannatos 2004). Previous studies have reported seasonal fluctuations in the number of black-backed jackals (Canis mesomelas) with increases in abundance observed in winter (Kaunda 2000). Identifing individual jackals was important because demographic processes, such as density dependence, can be explained by variation in the behaviour of individuals (Sutherland and Gosling 2000; Hopkins and Kennedy 2004). For example, density can potentially affect fitnessenhancing processes due to differences in individuals, such as their competitive ability and foraging efficiency. In human-altered landscapes, natural selection should favour individuals that respond to anthropogenic disturbances in a way that maximises fitness, through resource selection while avoiding mortality risks (Bolnick et al. 2003; McLoughlin et al. 2008). Natural selection acts on individual behavioural traits, such as shyness and boldness, or behavioural plasticity in which individuals adjust their behaviour to adapt to environmental changes (West-Eberhard 1989; Thompson 1991; West-Eberhard 2003). The results reported here show that individuals avoid main roads and towns, instead access these areas as part of a group, which increases their chances of survival and increases individual fitness (Bijleveld et al. 2015). This is in accordance with this study’s prediction that jackals will exhibit behavioural plasticity in order to maintain fitness through adapting to anthropogenic disturbances. Risk-averse behaviour is likely to be taught by parents of canids raised in areas including high traffic roads and human disturbances, thus it is proposed that such individuals are more adept at balancing the trade-off between the risks posed by roads and humans, and the benefits of obtaining resources in these areas (Lima 1998; Marchand et al. 2014). Roads can provide ease of access to food sources and are not proposed to act as barriers for the movement of jackal populations. Previous studies have reported that roads have facilitated animal movement and that predator hunting grounds can incorporate such features (Červinka et al. 2013). How canids utilise their habitat and select resources is influenced by the need to travel efficiently, acquire sufficient food resources, and avoid areas of high-level mortality risk from humans (Mech and Boitani 2003; Whittington et al. 2005; Hebblewhite and Merrill 2008). Wolves,
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coyotes (Canis latrans) and other canids have been shown to benefit from the resources provided by urbanisation, such as human food sources and greater travel efficiency along roads (Fedriani et al. 2001; Whittington et al. 2005; Bateman and Fleming 2011; Newsome et al. 2013). Here I suggest that jackals in Samos are also able to exploit the resources and ease of movement provided by urbanisation during night activities. The results documented here demonstrate that jackals adjust their behaviour to adapt to urbanisation and the resulting anthropogenic pressure. This has also been observed in India, where jackals have been found to inhabit areas in close proximity to urbanisation and human presence (Debnath and Choudhury 2013; Gupta et al. 2014; Negi 2014). Urbanisation is known to provide benefits to animals, such as resource subsidies, as well as associated risks (Delibes et al. 2001). In order to mitigate the risk of jackal-vehicle collisions that are likely to increase during the summer tourist season, fencing and wildlife underpasses are proposed to be incorporated into road network plans and upgrades in areas with known jackal presence (Foster and Humphrey 1995; Litvaitis and Tash 2008). Such underpasses have been documented to effectively facilitate the movement of multiple species, such as grey wolves and coyotes, when placed in convenient locations (Foster and Humphrey 1995). This study has shown that road networks in Samos overlap with jackal territories, such as in the north-east. Further research is necessary to determine convenient locations for similar road management developments. The canid population decline across Greece has been partly attributed to legal persecution of species including jackals, foxes and wolves in the 1970s and 1980s when the species were perceived as pests (Giannatos et al. 2005). Persecution has continued in Greece through the use of poison and other means. To help reduce persecution of this vulnerable species, community members must be educated about the ecosystem services jackals provide as a top predator in Samos and as ‘cleaners’ of nature (Giannatos 2004; Dar et al. 2009; Doherty et al. 2015). This action is necessary to achieve coexistence between jackals and humans and to protect the species from further population declines.
4.1 Conclusion The results reported here indicate that jackal foraging activity was not disrupted by the increased mortality risk and disturbance posed by high traffic roads, which indicates an area for necessary protection of the species from vehicle collisions. Jackals were found to adapt to anthropogenic disturbances by accessing urban areas as a group. Therefore urban areas were not avoided by jackals and instead were incorporated into their territories. A similar result was documented in wolves and cougars that adjusted their behaviour temporally by moving closer to human activity at night due to increased road availability, while avoiding such areas during the day (Knopff et al. 2014; Benson et al. 2015). This study demonstrates how jackals spatially utilise their environment at night. Such information can be used by conservation enforcement groups to
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identify areas for protection to benefit the jackal population. The importance of adaptive behavioural responses to anthropogenic disturbances by persecuted species is highlighted here through the changes to animal distribution that a human-dominated landscape generates. Developing an understanding of the ecology of any taxon that exhibits adaptation to human disturbed ecosystems can help to generate suitable conservation measures for such species.
References Akaike, E. (1973) Information Theory and an Extension of the Maximum Likelihood Principle. In: Petrov, B. N. and Csáki, F. F. eds. Second International Symposium on Information Theory. Budapest: IEEE pp 267-281. Amo, L., López, P. and Martìn, J. (2006) Nature-based tourism as a form of predation risk affects body condition and health state of Podarcis muralis lizards. Biological Conservation 131: 402-409. Baker, P. J, Robertson, C. P. J., Funk, S. M. and Harris, S. (1998) Potential fitness benefits of group living in the red fox, Vulpes vulpes. Animal Behaviour 56: 1411-1424. Bar-Massada, A., Radeloff, V. C. and Stewart, S. I. (2014) Biotic and abiotic effects of human settlements in the wildlife-urban interface. BioScience 64:429-437. Barrull, J., Mate, I., Ruiz-Olmo, J., Casanovas, J. G., Gosàlbez, J. and Salicrú, M. (2014) Factors and mechanisms that explain coexistence in a Mediterranean carnivore assemblage: An integrated study based on camera trapping and diet. Mammalian Biology 79: 123-131. Bateman, P. W. and Fleming, P. A. (2011) Big city life: Carnivores in urban environments. Journal of Zoology 287: 1-23. Benson, J. F., Mahoney, P. J. and Patterson, B. R. (2015) Spatiotemporal variation in selection of roads influences mortality risk for canids in an unprotected landscape. Oikos 0: 1-10. Berger, J. (1991) Pregnancy incentives, predation constraints and habitat shifts: Experimental and field evidence for wild bighorn sheep. Animal Behaviour 41: 61-77. Berger, J., Daneke, D., Johnson, J. and Berwick, S. H. (1983) Pronghorn foraging economy and predator avoidance in a desert ecosystem: Implications for the conservation of large mammalian herbivores. Biological Conservation 25: 193-208. Bijleveld, A. I., Gills, J. A., Jouta, J. and Piersma, T. (2015) Benefits of foraging in small groups: An experimental study on public information use in red knots Calidris canutus. Behavioural Processes 117: 74-81. Bissonette, J. A. and Kassar, C. A. (2008) Locations of deer-vehicle collisions are unrelated to traffic volume or posted speed limit. Human-Wildlife Conflicts 2: 122-130.
27
Bleich, V. C., Bowyer, R. T., Pauli, A. M., Nicholson, M. C. and Anthes, R. W. (1994) Mountain sheep (Ovis Canadensis) and helicopter surveys: ramifications for the conservation of large mammals. Biological Conservation 70: 1-7. Bolnick, D. I. Svanbäck, R., Fordyce, J. A., Yang, L. H., Davis, J. M., Hulsey, C. D. and Forister, M. L. (2003) The ecology of individuals: Incidence and implications of individual specialization. American Naturalist 161: 1-28. Bouskila, A. and Blumstein, D. T. (1992) Rules of thumb for predation hazard assessment: Predictions from a dynamic model. American Naturalist 139: 161-176. Brawata, R. L. and Neeman, T. (2011) Is water the key? Dingo management, intraguild interactions and predator distribution around water points in arid Australia. Wildlife Research 38: 426-436. Burger, J. and Gochfeld, M. (1990) Risk discrimination of direct versus tangential approach by basking black iguanas (Ctenosaura similis): Variation as a function of human exposure. Journal of Comparative Psychology 104: 388-394. Can, Ö. E., Kandemír, Í. and Togan, Í. (2009) The wildcat Felissilvestris in northern Turkey: Assessment of status using camera trapping. Oryx 45: 112-118. Červinka, J., Šálek, M., Padyšáková, E. and Šmilauer, P. (2013) The effects of local and landscape-scale habitat characteristics and prey availability on corridor use by carnivores: A comparison of two contrasting farmlands. Journal of Nature Conservation 21: 105-113. Ćirović, D., Penezić, A., Milenković, M. and Paunović, M. (2014) Winter diet composition of the golden jackal (Canis aureus L., 1758) in Serbia. Mammalian Biology 79: 132-137. Creel, S., Spong, G. and Creel, N. (2001) Interspecific Competition and the Population Biology of Extinction-prone Carnivores. In: Gittleman, J. L., Funk, S. M., Macdonald, D. and Wayne, R. K. eds. Carnivore Conservation. Cambridge: Cambridge University Press pp 35-60. Crooks, K. R. (2002) Relative sensitivities of mammalian carnivores to habitat fragmentation. Conservation Biology 16: 488-502. Dar, N. I., Minhas, R. A., Zaman, Q. and Linkie, M. (2009) Predicting the patterns, perceptions and causes of human-carnivore conflict in and around Machiara national park, Pakistan. Biological Conservation 142: 2076-2082. Darden, S. K. and Dabelsteen, T. (2008) Acoustic territorial signalling in a small, socially monogamous canid. Animal Behaviour 75: 905-912. Debnath, D. and Choudhury, P. (2013) Population estimation of golden jackal (Canis aureus) using different methods in various habitats of Cachar district, southern Assam. Indian Forester 139: 888894. Delibes, M., Gaona, P. and Ferreras, P. (2001) Effects of an attractive sink leading into maladaptive habitat selection. The American Naturalist 158: 1-9.
28
Dill, L. M. (1974a) The escape response of the zebra danio (Brachydanio rerio). I. The stimulus for escape. Animal Behaviour 22: 711-722. Dill, L. M. (1974b) The escape response of the zebra danio (Brachydanio rerio). I. The effect of experience. Animal Behaviour 22: 723-730. Doherty, T. S., Dickman, C. R., Nimmo, D. G. and Ritchie, E. G. (2015) Multiple threats or multiplying the threats? Interactions between invasive predators and other ecological disturbances. Biological Conservation 190: 60-68. Edwards, J. (1983) Diet shifts in moose due to predator avoidance. Oecologia 60: 185-189. Fedriani, J. M., Fuller, T. K. and Sauvajot, R. M. (2001) Does availability of anthropogenic food enhance densities of omnivorous mammals? An example with coyotes in southern California. Ecography 24: 325-331. Foster, M. L. and Humphrey, S. R. (1995) Use of highway underpasses by Florida panthers and other wildlife. Wildlife Society Bulletin 23: 95-100. Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, 2nd Edition. California: Sage Publications. French, S. S., González- Suárez, M., Young, J. K., Durham, S. and Gerber, L. R. (2011) Human disturbance influences reproductive success and growth rate in California sea lions (Zalophus californianus). PLoS ONE 6: e17686. Frid, A. and Dill, L. (2002) Human-caused disturbance stimuli as a form of predation risk. Conservation Ecology 6: 11-26. Frommolt, K. H., Goltsman, M. E. and Macdonald, D. W. (2003) Barking foxes, Alopex lagopus: Field experiments in individual recognition in a territorial mammal. Animal Behaviour 65: 509-518. Fuller, S., Axel, A. C., Tucker, D. and Gage, S. H. (2015) Connecting soundscape to landscape: Which acoustic index best describes landscape configuration? Ecological Indicators 58: 207-215. Gese, E. M. (2004) Survey and census techniques for canids. USDA National Wildlife Research Centre – Staff Publications 337: 273-279. Giannatos, G., Marinos, Y., Maragou, P. and Catsadorkis, G. (2005) The status of the golden jackal (Canis aureus L.) in Greece. Belgian Journal of Zoology 135: 145-149. Gill, J. A. and Sutherland, W. J. (2000) Predicting the Consequences of Human Disturbance from Behavioural Decisions. In: Gosling, L. M. and Sutherland, W. J. eds. Behaviour and Conservation. Cambridge: Cambridge University Press pp 51-64. Gill, J. A., Sutherland, W. J. and Watkinson, A. R. (1996) A method to quantify the effects of human disturbance on animal populations.Journal of Applied Ecology 33: 786-792. Gill, J. A., Norris, K. and Sutherland, W. J. (2001) Why behavioural responses may not reflect the population consequences of human disturbance. Biological Conservation 97: 265-268.
29
Gilliam, J. F. and Fraser, D. F. (1987) Habitat selection under predation hazard: Test of a model with foraging minows.Ecology 68: 1856-1862. Hagen, M., Kissling, W. D., Rasmussen, C., De Aguiar, M. A. M., Brown, L. E., Carstensen, D. W., Alves-Dos-Santos, I., Dupont, Y. L., Edwards, F. K., Genini, J., Guimaraes, P. R., Jenkins, G. B., Jordano, P., Kaiser-Bunbury, C. N., Ledger, M. E., Maia, K. P., Marquitti, F. M. D., McLaughlin, O., Morellato, L. P. C., O’Gorman, E. J., Trojelsgaard, K., Tylianakis, J. M., Vidal, M. M., Woodward, G. and Olesen, J. M. (2012) Biodiversity, species interactions and ecological networks in a fragmented world. Advances in Ecological Research 46: 89-210. Harrington, H. F. and Mech, L. D. (1982) An analysis of howling response parameters useful for wolf pack censuring. Journal of Wildlife Management 46: 686-693. Hebblewhite, M. and Merrill, E. (2008) Modelling human-wildlife relationships for social species with mixed-effects resource selection. Journal of Applied Ecology 45: 834-844. Hopkins, H. L. and Kennedy, M. L. (2004) An assessment of indices of relative and absolute abundance for monitoring populations of small mammals. Wildlife Society Bulletin 32: 1289-1296. Jaeger, M. M., Pandit, R. K. and Haque, E. (1996) Seasonal differences in territorial behaviour by golden jackals in Bangladesh: Howling versus confrontation. Journal of Mammalogy 77: 768-775. Jensen, R. R., Gonser, R. A. and Joyner, C. (2014) Landscape factors that contribute to animalvehicle collisions in two northern Utah canyons. Applied Geography 50: 74-79. Johnson, C. N., Isaac, J. L. and Fisher, D. O. (2007) Rarity of a top predator triggers continentwide collapse of mammal-prey: Dingoes and marsupials in Australia. Proceedings of the Royal Society of London Series B: Biological Sciences 274: 341-346. Joslin, P. W. B. (1967) Movements and homesites of timber wolves in Algonquin Park. American Zoologist 7: 279-288. Kaunda, S. K. K. (2000) Activity patterns of black-backed jackals at Mokolodi nature reserve, Botswana. South African Journal of Wildlife Research 30: 157-162. Kays, R. W. and Slauson, K. M. (2008) Remote Cameras. In: Long, R. A., MacKay, P., Zielinski, W. J. and Ray, J. C. eds. Noninvasive Survey Methods for Carnivores. Washington: Island Press pp 110-140. King, S. R. B. (2013) Prezewalski’s Horses and Red Wolves. Importance of Behavioural Research for Species Brought Back from the Brink of Extinction. In: Bekoff, M. ed. Ignoring Nature No More. Chicago: The University of Chicago Press pp 153-158. Knopff, A. A., Knopff, A. H., Boyce, M. S. and Clair, C. C. (2014) Flexible habitat selection by cougars in response to anthropogenic development. Biological Conservation 178: 136-145. Krishnappa, K. S. and Turner, W. C. (2014) Software for minimalistic data management in large camera trap studies. Ecological Informatics 24: 11-16.
30
Krofel, M. (2008) Survey of golden jackals (Canis aureus L.) in northern Dalmatia, Croatia: Preliminary results. Natura Croatica 17: 259-264. Krystufek, B., Murariou, D. and Kurtonur, C. (1997) Present distribution of the golden jackal Canis aureus in Balkans and adjacent regions. Mammal Review 27: 109-114. Levinsky, I., Skov, F., Svenning, J. C. and Rahbek, C. (2007) Potential impacts of climate change on the distributions and diversity patterns of European mammals. Biodiversity Conservation 16: 3803-3816. Lima, S. L. (1998) Stress and decision making under the risk of predation: Recent developments from behavioral, reproductive, and ecological perspectives. Advances in the Study of Behavior 27: 215-290. Litvaitis, J. A. and Tash, J. P. (2008) An approach towards understanding wildlife-vehicle collisions. Environmental Management 42: 688-697. Lucherini, M., Reppucci, J. I., Walter, R. S., Villalba, M. L., Wurstten, A., Gallardo, G., Iriate, A., Villalobos, R. and Perovic, P. (2009) Activity pattern segregation of carnivores in High Andes. Journal of Mammalogy 90: 1404-1409. Marchand, P., Garel, M., Bourgoin, G., Dubray, D., Maillard, D. and Loison, A. (2014) Impacts of tourism and hunting on a large herbivore’s spatio-temporal behavior in and around a French protected area. Biological Conservation 177: 1-11. Mastro, L. L., Conover, M. R. and Frey, S. N. (2010) Factors influencing a motorist’s ability to detect deer at night. Landscape and Urban Planning 94: 250-254. McCarley, H. (1975) Long-distance vocalization of coyotes. Journal of Mammalogy 56: 847-856. McLoughlin, P. D., Coulson, T. and Clutton-Brock, T. (2008) Cross-generational effects of habitat and density on life history in red deer. Ecology 89: 3317-3326. Mech. L. D. and Boitani, L. (2003) Wolf Social Ecology. In: Mech, L. D. and Boitani, L. eds. Wolves: Ecology, Behaviour, and Conservation. Chicago: University of Chicago Press pp 1-34. Metzger, M. J., Schroter, D., Leemans, R. and Cramer, W. (2008) A spatially explicit quantitative vulnerability assessment of ecosystem service change in Europe. Regional Environmental Change 8: 91-107. Mills, M. G. L., Juritz, J. M. and Zucchini, W. (2001) Estimating the size of spotted hyena (Crocutacrocuta) populations through playback recordings allowing for non-response. Animal Conservation 4: 335-343. Moehlman, P. D. (1987) Social organization in jackals: The complex social system of jackals allows the successful rearing of very dependent young. American Scientist 75: 366-375. Negi, T. (2014) Review of current worldwide status, distribution, ecology and dietary habitats of golden jackal, Canis aureus. Octa Journal of Environmental Research 2: 338-359.
31
Pijanowski, B. C., Villanueva-Rivera, L. J., Dumyahn, S. L., Farina, A., Krause, B. L., Napoletano, B. M., Gage, S. H. and Pieretti, N. (2011) Soundscape ecology: The science of sound in the landscape. BioScience 61: 203-216. Reyers, B. (2004) Incorporating anthropogenic threats into evaluations of regional biodiversity and prioritisation of conservation areas in the Limpopo Province, South Africa. Biological Conservation 118: 521-531. Ripple, W. J., Estes, J. A., Beschta, R. L., Wilmers, C. C., Ritchie, E. G., Hebblewhite, M., Berger, J., Elmhagen, B., Letnic, M., Nelson, M. P., Schmitz, O. J., Smith, D. W., Wallach, A. D. and Wirsing, A. J. (2014) Status and ecological effects of the world’s largest carnivores. Science 343: 151-163. Robbins, R. L. and McCreery, E. K. (2003) Acoustic stimulation as a tool in African wild dog conservation. Biological Conservation 111: 263-267. Robinson, N. M., Leonard, S. W. J., Ritchie, E. G., Bassett, M., Chia, E. K., Buckingham, S., Gibb, H., Bennett, A. F. and Clarke, M. F. (2013) Refuges for fauna in fire-prone landscapes: Their ecological function and importance. Journal of Applied Ecology 50: 1321-1329. Rotem, G., Berger, H., King, R., Bar, P. and Saltz, D. (2011) The effect of anthropogenic resources on the space-use patterns the golden jackals. Journal of Wildlife Management 75: 132-136. Ruffino, L., Russell, J. and Vidal, E. (2012) Anthropogenic subsidies mitigate environmental variability for insular rodents. Oecologia 172: 737-749. Ryan, M. J. (1985) The Tungara Frog: A Study in Sexual Selection and Communication. Illinois: University of Chicago Press. Sarmento, P., Cruz, J., Eira, C. and Fonseca, C. (2009) Evaluation of camera trapping for estimating red fox abundance. Journal of Wildlife Management 73: 1207-1212. Smuts, G. L., Whyte, I. J. and Dearlove, T. W. (1977) A mass capture technique for lions. East African Wildlife Journal 15: 81-87. Sokos, C. K., Mamolos, A. P., Kalburtji, K. L. and Birtsas, P. K. (2013) Farming and wildlife in Mediterranean agroecosystems. Journal for Nature Conservation 21: 81-92. Steidl, R. J. and Anthony, R. G. (2000) Experimental effects of human activity on breeding bald eagles. Ecological Applications 10: 258-268. Sutherland, W. J. and Gosling, L. M. (2000) Advances in the Study of Behaviour and their Role in Conservation. In: Gosling, L. M. and Sutherland, W. J. eds. Behaviour and Conservation. Cambridge: Cambridge University Press pp 3-12. Thompson, J. D. (1991) Phenotypic plasticity as a component of evolutionary change. Trends in Ecology and Evolution 6: 246-249.
32
Tóth, T., Krecsák, L., Szűcs, E., Heltai, M. and Huszár, G. (2009) Records of the golden jackal (Canis aureus Linnaeus, 1758) in Hungary from 1800th until 2007, based on a literature survey. North-Western Journal for Zoology 5: 386-405. Vanthomme, H., Kolowski, J., Korte, L. and Alonso, A. (2013) Distribution of a community of mammals in relation to roads and other human disturbances in Gabon, Central Africa. Conservation Biology 27: 281-291. VerCauteren, K. C., Burke, P. W., Philips, G. E., Fischer, J. W., Seward, N. W., Wunder, B. A. and Lavelle, M. J. (2007) Elk use of wallows and potential chronic wasting disease transmission. Journal of Wildlife Diseases 43: 784-788. Walther, F. R. (1969) Flight behaviour and avoidance of predators in Thomson’s gazelle (Gazelle thomsoni: Guenther 1884). Behaviour 34: 184-221. West-Eberhard, M. J. (1989) Phenotypic plasticity and the origins of diversity. Annual Review of Ecology 20: 249-278. West-Eberhard, M. J. (2003) Developmental Plasticity and Evolution. Oxford: Oxford University Press. Whittington, J., St Clair, C. C. and Mercer, G. (2005) Spatial responses of wolves to roads and trails in mountain valleys. Ecological Applications 15: 543-553. Wickham, H. (2009) ggplot2: Elegant Graphics for Data Analysis. New York: Springer. Williams, R., Lusseau, D. and Hammond, P. S. (2006) Estimating relative energetic costs of human disturbance to killer whales (Orcinus orca). Biological Conservation 133: 301-311.
Website References Bates, D., Maechler, M., Bolker, B. M. and Walker, S. (2015) Fitting linear mixed-effects models using lme4. Journal of Statistical Software www.arxiv.org/abs/1406.5823 (Accessed 5th August 2015). Deinet, S., Ieronymidou, C., McRae, L., Burfield, I. J., Froppen, R. P., Collen, B. and Böem, M. (2013) Wildlife comeback in Europe: The recovery of selected mammal and bird species. ZSL, Birdlife International and the European Bird Census Council www.static.zsl.org/files/wildlifecomeback-in-europe-the-recovery-of-selected-mammal-and-bird-species-2576.pdf (Accessed 16th June 2015). Giannatos, G. (2004) Population status and conservation action plan for the golden jackal (Canis aureus) in Greece. WWF Greece www1.nina.no/lcie_new/pdf/634986392590857891_Greece%20Golden%20Jackal%20Action% 20Plan%202004.pdf (Accessed 19th May 2015). Gupta, S., Sanyal, A., Saha, G. K. and Ghosh, A. K. (2014) Diurnal activity pattern of golden jackal (Canis aureus Linn.) in an urban landscape of Kolkata, India. Proceedings of the Zoological Society of London www.download.springer.com/static/pdf/437/art%253A10.1007%252Fs12595-014-0119-
33
2.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs12595-01401192&token2=exp=1439293516~acl=%2Fstatic%2Fpdf%2F437%2Fart%25253A10.1007%25252Fs 12595-014-01192.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1007 %252Fs12595-014-01192*~hmac=f17c184857f9d537ce4e18365f5f60ba3c60a86a2153dc0885fb81037698e28d (Accessed 11th August 2015). R Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing www.R-project.org/ (Accessed 5th August 2015).
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