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Article

The Distribution and Activity of the Invasive Raccoon Dog in Lithuania as Found with Country-Wide Camera Trapping

by
Marius Jasiulionis
*,
Vitalijus Stirkė
and
Linas Balčiauskas
Nature Research Centre, Akademijos 2, 08412 Vilnius, Lithuania
*
Author to whom correspondence should be addressed.
Forests 2023, 14(7), 1328; https://doi.org/10.3390/f14071328
Submission received: 10 May 2023 / Revised: 20 June 2023 / Accepted: 26 June 2023 / Published: 28 June 2023
(This article belongs to the Special Issue Conservation and Management of Forest Wildlife)
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Abstract

:
The raccoon dog (Nyctereutes procyonoides Gray, 1834) is an invasive mammal widespread in northern, eastern, and central Europe, where it damages biodiversity and carries a wide range of pathogens. Surveys of this species in Lithuania ceased before 2000, so there is a lack of scientific information on its distribution and relative abundance. In 2019–2022, we carried out a nationwide recording of raccoon dogs using camera traps (101 sites, sampling effort of 15,563 trapping days). The species was found at 64 sites (63.4% of the sites surveyed), with an average relative shooting frequency of 4.30 photographs per 100 days. The frequency of raccoon dogs was higher at camera sites where lynx (Lynx lynx Linnaeus, 1758) or wolves (Canis lupus Linnaeus, 1758) were recorded compared to sites where predators were absent (7.95 vs. 3.21 photos/100 days, p < 0.05). The highest raccoon dog activity (69.5% of records) was observed at night and at temperatures between −3 and +5 °C. Below −15 °C, animals were not active, while above 25 °C, there was very little activity. Diurnal activity (36.1% of daytime records in April–June) increased during estrus, gestation, and rearing of pups. We conclude that wide-scale camera trapping is a suitable method for raccoon dog surveys.

1. Introduction

The introduction of invasive alien species has become one of the most important causes of biodiversity change and loss [1]. Invasive species are increasing every year and are expected to increase in the future [2]. Invasions are usually driven by the intensification of transport flows and the spread into new areas [3,4], by land use change [5], or by ill-considered human activities, in particular through the transport of alien species [6], of cultivated species of plants [7], or by the movement of escaped pets or domestic animals [8].
Global climate change is allowing invasive species to adapt to alien conditions [9]. The economic costs of invasions are rising at an enormous rate. For example, in Germany alone, the figure was around USD 1 million in 1960, and by 2020, the economic cost will already reach USD 1 billion per year. In Europe, invasions cost EUR 140 billion annually [10].
The natural range of the raccoon dog (Nyctereutes procyonoides Gray, 1834) covers Eastern Asia [11]. In Lithuania, they spread from the neighbouring countries of Belarus, where they were acclimatised in 1936, and Latvia, which introduced the species in 1948. By 1960, they had already invaded Lithuania [12] and later spread to other parts of Europe [11]. Surveys on this species in Lithuania ceased before 2000 but based on the number roadkilled and hunted raccoon dogs, the current population in Lithuania is at least 10,000 [13].
Raccoon dogs have a significant negative impact on birds and amphibians [14] being the most detrimental to ground-nesting birds [15]. The species is characterised by ecological plasticity, adaptability to survive in urbanised areas, and transmits many diseases [16]. This species is characterised by passive hibernation, but the duration and weather conditions of hibernation are not well known [17]. As the climate warms and winters become milder, the negative impacts of these invasive animals on other species may increase [18].
In eastern Finland, raccoon dogs have a total of 50 hibernation days in winter, with an average of seven hibernation days in one period. The longest hibernation periods were 31 days [19]. In winter, the activity score of a raccoon dog had a significant negative covariance with snow depth but had no significant covariance between activity and depth of the soft snow [19]. Raccoon dogs lose their appetite at temperatures of −5 °C degrees or below and can go without food for 11 weeks without any adverse effects on their health or reproduction [20]. After the hibernation season, female raccoons weighing between 5 and 7 kg produce younger than those weighing more. This indicates that the dogs are well adapted to hibernation and are able to lose body weight. There was a significant negative correlation between the number of pups produced and the average body weight of females at the beginning of the mating season [21]. Individuals with insufficient fat cover are more active in winter [20,22]. They choose wintering habitats where they can find food even in winter if needed. Underweighted animals prefer gardens, the banks of water bodies, marshes, and forests [22].
Estimating the population size of the raccoon dog is not easy due to the shortage of survey methods. It is not possible to record tracks in the snow, as activity decreases in winter. Their excrements are left in one place, so it is not possible to count animals by excrement. Camera traps have, therefore, been used that allow not only the relative abundance to be estimated but also changes in daily activity and seasonal activity. Obtaining data could help to manage the abundance of these invasive animals and the damage they cause. Norway and Sweden have an early warning system based on camera traps baited at potential immigration routes. This allows for a rapid awareness of the spread of these invasive animals and timely control measures. In addition, camera traps are used to estimate population size by identifying the proportion of individuals already recorded [23]. In this way, cameras are simulating the traditional mark-recapture method. In Lithuania, raccoon dog surveys have not been carried out for the last three decades, and it is, therefore, proposed to assess the status of the population and population trends based on the use of hunting bags and the roadkill index. Strong and significant correlations have been found at the national level, both between the number of animals surveyed and the number of animals hunted, and between the number of animals hunted and the number of roadkill. Therefore, the number of raccoon dog who are roadkill on stable predefined routes was tested as a survey proxy [13].
Camera trapping is a widely used method, ranging from rare and discreet species, such as big cats [24,25,26,27] and bears [28], to common species such as ungulates [29], foxes [30,31], and pine martens [32]. It is a globally applied method to answer complex ecological questions: seasonal and daily activity analysis [33]; density and abundance estimation [25,34]; species richness and site occupancy [35,36]. This method is relatively cheap, saves researchers’ time and resources, and allows the collection of large amounts of data on multiple species with minimal disturbance [37,38].
Cameras are increasingly being used to detect spatiotemporal movement patterns, habitat selection [39], daily activity patterns [40], burrow use and their sharing with other mammals [41], reproductive success [42], and the monitoring of raccoon dogs or other invasive animals [43]. Early warning systems are being developed using camera traps to prevent raccoon dogs from spreading into new territories [23].
Although wildlife cameras have been increasingly used in Lithuania in recent years, they have not been used to study raccoon dogs, at least not with published results. The aim of this nationwide camera-trapping-based study was, therefore, to determine the distribution and relative abundance of raccoon dogs in Lithuania using relative shooting frequency as a proxy, as well as to investigate seasonal and diurnal activity of these invasive animals.

2. Materials and Methods

2.1. Study Site

The survey was carried out throughout Lithuania. The study area was divided into three parts according to landscape, agricultural intensity, and microclimate (Figure 1). The Coastal Highlands area is characterised by the transport of maritime air to the mainland, coastal breeze circulation, high water tables, marshy soils, and the rise of moist air masses on the western and south-western slopes of the highlands. The Middle Lowland region is characterised by adiabatic dispersion of air from the neighbouring highlands, poor conditions for water runoff on a flat surface, and over-irrigation of the soil. The region has the most fertile soils and, therefore, the most intensive agriculture. The South-Eastern Highlands are characterised by more intense turbulent air circulation and thermal convection in the hilly terrain, the effect of local altitude, sandy soils, and the generation of powerful temperature inversions in the wind [44].

2.2. Camera Trapping

From September 2019 to August 2022, we installed camera traps on Lithuanian territory. We intended to have a similar survey coverage in all months, however, it is slightly lower in August and September due to the higher number of people visiting the forests during the mushroom picking season. A total of 101 camera sites were surveyed, with 1–4 (average 1.74) cameras were used per site. The cameras were located in forests on animal paths, in forest clearings, and in drainage canals, where animal movements are likely to be highest. A total sampling effort was 15,563 camera trap days (TD), that is, 154 trap days per site on average.
We used black LED Ltl Acorn-6210 cameras (https://www.ltlacorn.com/product-category/ltl-6210-series/, accessed on 10 April 2023) with autonomous triggering and sensors set to maximum sensitivity (effective range of use 13 m). The trigger interval was set to 0 s. The cameras were programmed to record 1 photo and a 10 s videos during each trigger. No attractants were used. The data, time, and temperature were automatically recorded in each photo.
We compared temperature readings from both the thermometer and the camera on all possible occasions. In a few cases, the differences observed were within 2 degrees, but in most cases, differences were less, suggesting the reliability of camera data. However, it is important to note that temperatures in Lithuania can vary significantly throughout the day and across different locations, which may introduce some errors.
Photographs taken at an interval of at least 1 h were considered as independent observations (trap events). Each day was divided into three periods: daytime, nighttime, and twilight. Twilight was defined as the one-hour period before and after sunrise and sunset, so each day had four hours of twilight. A daytime period was defined as the period from one hour after sunrise to one hour before sunset, and, correspondingly, nighttime was defined as the period from one hour after sunset to one hour before sunrise. Sunset and sunrise times were obtained from http://www.timeadate.eu/pages/lt/sunrise-calc-lt.html (accessed on 14 March 2023).
Seasons were defined as 3-month sequences: March, April, and May (spring), June, July, and August (summer), September, October, and November (autumn), while December, January, and February stood for winter. These months are used by default in our latitude.

2.3. Data Analysis

The relative shooting frequency (RSF, expressed as photos/100 days) was calculated (for each site, year, month, etc.) using the formula RSF = (TE/TD) × 100, where TE (trapping events) is a number of independent photos and TD (trapping days) is a number of days the cameras were working. We calculated 95% confidence intervals (CI) and standard errors (SE) for RSF values [45]. Differences between sites with or without large predators and RSF differences between years (using monthly means for 2020 and 2021) were compared using the Mann–Whitney test.
For the analysis of daily and seasonal activity, we compared the proportions and CI of the number of photos taken at the respective times. Differences in proportions were assessed by G-test, using an online calculator (https://elem.com/~btilly/effective-ab-testing/g-test-calculator.html, accessed on 2 April 2023). However, changes in activity throughout the year are largely due to variations in daylight hours. Direct comparison of activity by comparing the proportions of the photos taken is biased because at our latitudes the length of daylight and darkness varies considerably throughout the year. Therefore, the probability of capturing an animal at different times of the day varies seasonally.
Bias was mitigated using the selection ratio (w) parameter. Selection ratios for each concerned period were calculated according to the formula of Manly [46]: w = PEi/PTi, where PE is the proportion of trapping events in period i, and PT is the ratio of the duration of period i to the duration of all periods. w > 1 indicates that period selectivity is higher than availability; w < 1 indicates period avoidance.
Calculations were performed in Statistica for Windows, version 6.0 (StatSoft, Inc., Tulsa, OK, USA) and Microsoft® Excel®.

3. Results

3.1. Distribution and Relative Shooting Frequency of Raccoon Dogs

During the three-year study period, 971 trap events with raccoon dogs were obtained in 101 locations (Figure 1). The average relative shooting frequency of raccoon dogs was 4.30 (CI = 2.88–5.72) photos/100 days. Raccoon dogs were detected in 64 sites (63.4% of all sites surveyed). The relative shooting frequency varied across the sites, ranging from 0.01 to 4.99 photos per 100 days in 38 sites, from 5.00 to 9.99 photos per 100 days in 14 sites, from 10.00 to 19.99 photos per 100 days in six sites, and exceeding 20 photos per 100 days in six sites (Figure 1).
The South-Eastern Highlands region was characterised by the highest percentage of survey points where raccoon dogs were recorded, 71.4% (CI = 53.7%–85.4%). In the Middle Lowlands and Coastal Highlands regions, the respective proportions were 61.2% (CI = 46.2%–74.8%) and 52.9% (CI = 27.8%–77.0%) of the survey points. Differences between the South-Eastern Highlands and the Middle Lowlands (G = 0.55, df = 1, p = 0.46), as well as between the South-Eastern Highlands and the Coastal Highlands (G = 0.99, df = 1, p = 0.32) were not significant.
The highest relative shooting frequency of raccoon dogs was 6.76 (CI = 3.55–9.97) photos/100 days in the South-Eastern Highlands (Figure 2a) was significantly higher (G = 148.8, df = 1, p < 0.001) than that in the Middle Lowlands, being 3.24 (CI = 1.64–4.84) photos/100 days. The lowest relative shooting frequency of raccoon dogs was found in the Coastal Highlands region at 2.33 (CI = 0.52–4.14) photos/100 days, but the difference from Middle Lowlands is not significant (G = 0.22, df = 1, p = 0.36). A significant difference was observed in the relative shooting frequency of raccoon dogs between the Coastal Highlands (lowest frequency) and the South-Eastern Highlands (highest frequency) (G = 102.6, df = 1, p < 0.001).

3.2. Relative Abundance of Raccoon Dogs in Relation to the Presence of Large Carnivores

We assessed one of the factors that can influence the relative abundance of raccoon dogs, i.e., the presence of large predators, such as lynx (Lynx lynx) or wolf (Canis lupus), in the area. In study areas where lynxes or wolves were recorded with tracking cameras, the relative shooting frequency of raccoon dogs was 7.95 (CI = 4.20–11.70) photos/100 days. At sites where large predators were not recorded, it was 3.21 (CI = 2.17–4.20) photos/100 days. The difference in relative abundance is significant (Mann–Whitney, z = −2.06, p < 0.05).

3.3. Seasonal and Daily Activity of Raccoon Dogs

The lowest seasonal activity of the raccoon dog was observed in winter (Figure 2b), with 4.19 (CI = 2.65–5.73) photos/100 days. Activity indices in the other seasons are similar and higher than that in winter (G = 31.0, df = 1, p < 0.001).
The relative shooting frequencies of raccoon dogs significantly differed between 2020 and 2021 (z = −2.62, p < 0.001). A sharp increase in the frequency was observed in 2021, the average being 15.14 (CI = 8.99–12.30) photos/100 days. In 2022, the number of observations had declined, the average being 2.22 (CI = 0.49–3.95) photos/100 days to a level similar to 2020, 3.36 (CI = 1.69–5.03) photos/100 days (Figure 3).
Overall, 69.5% (CI = 66.5%–72.4%) of the photographs were recorded at night, 17.6% (CI = 15.2%–20.1%) during the daytime, and 12.8% (CI = 10.8%–15.1%) during twilight hours.
However, diurnal activity varied (G = 139.6, df = 3, p < 0.001) between seasons (Figure 4). In winter, almost all raccoon dog sightings took place at night (97.6%, CI = 94.5%–99.2%), similar to autumn (83.4%, CI = 77.5%–88.3%). During the warm season, raccoon dog activity during the day and in the twilight time increased. In spring, 59% (CI = 54.1%–64.5%) of sightings were still recorded at night, but this was statistically significantly lower than in winter (G = 121.3, df = 1, p < 0.001) or autumn (G = 34.9, df = 1, p < 0.001). In summer, only 45.4% (CI = 38.5%–52.5%) of observations were recorded at night. This is reliably lower than in winter (G = 159.3, df = 1, p < 0.001), autumn (G = 64.6, df = 1, p < 0.001), or spring (G = 9.7, df = 1, p < 0.05).
The daytime activity of the raccoon dog increased significantly during the estrus, gestation, and pup rearing period, with 36.1% (CI = 30.9%–41.5%) of the recordings occurring during daylight hours in April–June. In other months, however, only 7% (CI = 5.9%–10.2%) of raccoon dogs were active during the day. This difference is reliable (G = 113.5, df = 1, p < 0.001).
The most avoided time for raccoon dog activity was daytime (w = 0) and twilight (w = 0.14) in winter and daytime in autumn (w = 0.18). Although raccoon dogs are not very active during the day at all times of the year, daytime is the least avoided in summer (w = 0.64). The time of twilight is favoured differently throughout the year, ranging from avoidance in winter (w = 0.14) or autumn (w = 0.60) to an active time in spring (w = 1.11). Night is the time when raccoon dogs are most active in all seasons from winter (w = 1.71) to summer (w = 1.91). During the rut and pup-rearing period, the raccoon dog activity increased during the day (w = 0.70) compared to other months (w = 0.15).

3.4. Activity of Raccoon Dogs Depending on Temperature

No raccoon dog activity was recorded below −15 °C, while activity below −4 °C and above 25 °C was very low (Figure 5). The highest activity of raccoon dogs was recorded at temperatures ranging from −3 °C to 5 °C. From +1 °C onwards, raccoon dog activity decreased steadily as the temperature increased.

4. Discussion

Our nationwide raccoon dog survey, conducted using camera traps, revealed the following findings: (i) unequal distribution and relative abundance across geographical areas, (ii) temporal variations in relative abundance, and (iii) a positive correlation between raccoon dog abundance and the presence of large predators such as wolves and lynx in the area. Additionally, we collected data on the seasonal and diurnal activity patterns of raccoon dogs and their dependence on ambient temperature. These findings are crucial for assessing the invasive species status of raccoon dogs in Lithuania and can also be applicable in neighbouring countries. Moreover, our data enable us to anticipate changes in raccoon dog ecology and their impact on ecosystems due to climate change, including the potential increase in mongoose impact as the winter hibernation period shortens or disappears. We will discuss the results in the context of findings from other countries.
Raccoon dogs exhibit high adaptive plasticity, enabling them to inhabit diverse habitats including farmland, deciduous forests, sparsely vegetated areas, fields, gardens, mixed forests, grasslands, and open forests with tall and abundant undergrowth [19,47,48,49]. In Japan, raccoon dogs can be classified into two types: mountain and village. The mountain type prefers grassy habitats and is more likely to settle in forests, while the village type favours farmland and gardens [50]. Similarly, in Germany, raccoon dogs can be categorised as agrarian and forest types. The agrarian type operates in agricultural environments, with forests comprising less than 5% of their home range size, while the forest type primarily inhabits forests, which make up nearly 70% of their home range size [51].
In some areas, raccoon dogs are one of the most abundant species among medium-sized predators [51]. There is a common perception that these invasive animals are ubiquitous. However, we did not find these animals in 1/3 of the sites surveyed. The highest relative abundance was found in the South-Eastern Highlands region with hilly terrain, mosaic landscapes, and abounding lakes. The relative abundance decreased towards the north-west (see Figure 1). In the Coastal Highlands area, we did not detect raccoon dogs in about half of the surveyed areas. These results were surprising as the area closer to the sea is characterised by milder winters, lower snow cover, and fewer days with snow.
It is important to know the raccoon dog diet so that we can assess which groups of organisms are most affected, and which groups will be under more pressure if raccoon dogs are active during the cold season.
Compared to foxes and badgers, raccoon dogs exhibit the broadest food niche [52,53,54], with their diet varying considerably based on location and the availability of food sources [55], in different biotopes [56] and seasonally [56,57]. In Finland, frogs were more frequently consumed by adult raccoon dogs and the main food item was insects [52]. In Germany, the proportions of amphibians, small mammals, and insects in their diet were smaller [57]. Belarus, the diet of raccoon dogs consisted mainly of birds and eggs, fruits, mammals, and carrion [56]. However, the presence of eggs in their diet is challenging to determine [55]. During the cold season, carcasses of ungulates and cattle were the most important food items in Estonia and Lithuania [53,58], but during the warm season amphibians, plants (raspberries, blueberries), and rodents were dominating [53].
Large carnivores are one of the factors that can regulate the number of invasive animals. In the Bialowieza Forest, 7% of recorded raccoon dog mortalities were caused by wolves [51]. In Finland, camera trap surveys have shown a negative correlation between predators (lynx and wolves) and the distribution of the raccoon dog [58].
In our study, the opposite trend was found. In areas where wolves or lynx were recorded, the relative abundance of raccoon dogs was twice as high as in study areas with no large carnivores. T.A. Diserens and his colleagues found a similar trend: raccoon dogs were more frequent in study areas of Bialowieza Forest, where wolves were more likely to be encountered [59].
Raccoon dogs are not skilled hunters, but their diet is plastic, and they take every opportunity to feed if they find food left by other predators [60]. The risk of being killed by larger predators is, therefore, balanced against the availability of additional food such as carcasses [61]. Depending on population density and food availability, the impact of the risk of large predators on mesopredators may be outweighed by mitigating effects [59]. We hypothesise that it is the remains of wolf and lynx prey that cause raccoon dogs preference to use the same habitat as large predators.
The camera method allowed us to assess both seasonal and daily activity of raccoon dogs. In this study, high nocturnal activity was observed in 69.5% of all recordings. The similar nocturnal activity was also observed in the Valdai Upland (Russia), with 64.0% of all recordings [40]. In East Germany, nocturnal and twilight activity was even more expressed, averaging 86.8% of recordings, with daytime activity changing from 15.0% in winter to 56.6% during the pupping and pup-rearing time [62]. A similar trend was found in our study: 36.1% of activity was recorded in the daytime during the pupping season in contrast to 7% at other times of the year. In Japan, raccoon dogs are recorded almost two times less frequently during the day than at twilight and almost four times less frequently than at night [63].
Similar selection ratios were also observed in different periods in similar latitudes in Russia [40] to our study: daytime selection ratio was w = 0.57 in Russia versus w = 0.41 in the present study, twilight selection ratio was w = 0.68 versus w = 0.77, and nighttime—w = 1.59 versus w = 1.72. In some areas, raccoon dogs may remain active during the day, either where vegetation is very dense [64] or in certain areas (e.g., cormorant colonies) where food resources are more readily available during the day [65].
Raccoon dogs cause the most damage to other groups of animals when these invasive animals are present in large numbers and at their most active periods. In countries where raccoon dogs are abundant, amphibian populations can be severely affected [14]. In Lithuania, the damage to amphibians depends on their (both raccoon dogs and amphibians) presence in the agricultural landscape and on their use of specific habitats such as beaver lodges and ponds [66]. Amphibians that hibernate in the beaver lodges become easily accessible prey.
It was believed that raccoon dogs hibernate in our latitudes during the winter [12], so amphibians are not severely affected. Our study showed that they remain quite active even in winter, with statistically significant differences compared to activity in other seasons. In our study, the highest activity of raccoon dogs was observed at +1 °C. We also recorded activity at temperatures below 0 °C, and in two cases, raccoon dogs were active at temperatures of −13 °C and −15 °C.
In the study period, the average temperature in December was −1.8 °C (0.2 °C above the long-term average), in January −0.3 °C (2.7 °C above the long-term average) and in February −0.7 °C (2.0 °C above the long-term average). So, it might be concluded that the impact of raccoon dogs on potential prey in winter may further increase in the future as the climate warms. Amphibians wintering in underground passages, drainage systems, and other similar habitats become affected.
Disease, food resource abundance, and climatic conditions can influence year-to-year fluctuations in the abundance of these invasive animals [67,68]. However, snow cover is one of the most important factors determining the survival of raccoon dogs and their need to hibernate. These animals do not survive when snow cover exceeds 80 cm [11]. When snow cover reaches 20 cm, they spend most of their time in caves, and when snow cover reaches 35 cm, hibernation begins [11,64]. Sleeping in caves also carries a number of risks: fur parasites and diseases are more easily spread, hibernating animals die if they do not accumulate enough fat, cubs are killed by foxes or badgers living in the same cave [64].
The highest relative shooting frequency of raccoon dogs was recorded in 2021, several times higher than in other survey years (see Figure 3). Does this mean that we had the highest abundance of raccoon dogs in 2021? The winter of 2019–2020 and 2020–2021 was characterised by the absence of permanent snow cover in Lithuania. This explains, at least in part, the peak in raccoon dog records in 2021. The number of days with snow cover is predicted to decrease in the future due to climate change. We can, therefore, predict that there will be more years when the activity of raccoon dogs in the cold period will be high and their environmental impact will increase.

5. Conclusions

Nationwide camera trap recording, carried out in 2019–2022 in Lithuania, yielded data on the relative abundance, expressed as camera shooting frequency, and also allowed analysis of daily and seasonal activity including hibernating regime depending on the weather temperatures. The positive influence of the co-presence with large carnivores, such as wolves and lynx, was shown. Therefore, we conclude that wide-scale camera trapping is a suitable method for raccoon dog surveys.

Author Contributions

Conceptualisation, L.B.; methodology, all authors; investigation, M.J. and V.S.; formal analysis, M.J. and L.B.; data curation, M.J. and L.B.; writing—original draft preparation M.J.; writing—review and editing, M.J. and L.B. All authors have read and agreed to the published version of the manuscript.

Funding

Surveys were funded by the project “Investigations of the Status of Invasive and Alien Species in Lithuania” (Contract No. 05.5.1-APVA-V-018-01-0012), co-financed by the European Union Structural Funds according to the 5th Priority of the European Union Funds Investment Operational Program for 2014–2020 “Environment, Sustainable Use of Natural Resources and Adaptation to Climate Change” under the measure “Biodiversity protection” (05.5.1-APVA-V-018).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Due to ongoing investigation, data of this study are available from the corresponding author upon personal request.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Locations of camera sites in Lithuania (CH—Coastal Highlands, ML—Middle Lowlands, SH—South-Eastern Highlands) and relative shooting frequency of raccoon dogs.
Figure 1. Locations of camera sites in Lithuania (CH—Coastal Highlands, ML—Middle Lowlands, SH—South-Eastern Highlands) and relative shooting frequency of raccoon dogs.
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Figure 2. Relative shooting frequency of raccoon dogs in three regions of Lithuania (a) and in different seasons (b): SH—South-Eastern Highlands, ML—Middle Lowlands; CH—Coastal Highlands.
Figure 2. Relative shooting frequency of raccoon dogs in three regions of Lithuania (a) and in different seasons (b): SH—South-Eastern Highlands, ML—Middle Lowlands; CH—Coastal Highlands.
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Figure 3. Dynamics of relative shooting frequencies of raccoon dogs in 2019–2022.
Figure 3. Dynamics of relative shooting frequencies of raccoon dogs in 2019–2022.
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Figure 4. The daily activity of raccoon dogs in different seasons (nighttime—dark grey area, twilight—light grey area, daytime—white area, defined as an average time for each season).
Figure 4. The daily activity of raccoon dogs in different seasons (nighttime—dark grey area, twilight—light grey area, daytime—white area, defined as an average time for each season).
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Figure 5. The activity of raccoon dogs at different air temperatures (camera readings were used).
Figure 5. The activity of raccoon dogs at different air temperatures (camera readings were used).
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Jasiulionis, M.; Stirkė, V.; Balčiauskas, L. The Distribution and Activity of the Invasive Raccoon Dog in Lithuania as Found with Country-Wide Camera Trapping. Forests 2023, 14, 1328. https://doi.org/10.3390/f14071328

AMA Style

Jasiulionis M, Stirkė V, Balčiauskas L. The Distribution and Activity of the Invasive Raccoon Dog in Lithuania as Found with Country-Wide Camera Trapping. Forests. 2023; 14(7):1328. https://doi.org/10.3390/f14071328

Chicago/Turabian Style

Jasiulionis, Marius, Vitalijus Stirkė, and Linas Balčiauskas. 2023. "The Distribution and Activity of the Invasive Raccoon Dog in Lithuania as Found with Country-Wide Camera Trapping" Forests 14, no. 7: 1328. https://doi.org/10.3390/f14071328

APA Style

Jasiulionis, M., Stirkė, V., & Balčiauskas, L. (2023). The Distribution and Activity of the Invasive Raccoon Dog in Lithuania as Found with Country-Wide Camera Trapping. Forests, 14(7), 1328. https://doi.org/10.3390/f14071328

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