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Article

Available Forage and the Conditions for Avoiding Predation of the Siberian Roe Deer (Capreolus pygargus) in the Lesser Xing’an Mountains

by
Yueyuan Li
1,2,
Yuehui Li
1,*,
Yuanman Hu
1,3,
Yue Li
4,
Jia Guo
2,5,
Xuefeng Shao
1,2 and
Huifang Gao
1,2
1
CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
2
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
3
E’erguna Wetland Ecosystem National Research Station, Hulunbuir 022250, China
4
School of Environment, Liaoning University, Shenyang 110036, China
5
Erguna Forest-Steppe Ecotone Research Station, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
*
Author to whom correspondence should be addressed.
Forests 2023, 14(10), 2072; https://doi.org/10.3390/f14102072
Submission received: 6 September 2023 / Revised: 7 October 2023 / Accepted: 10 October 2023 / Published: 17 October 2023
(This article belongs to the Section Forest Ecology and Management)
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Abstract

:
Our study focused on quantifying available forage and the conditions for avoiding predation provided within the home ranges of Siberian roe deer (Capreolus pygargus). We conducted transect surveys in both winter and summer–autumn home ranges of the Siberian roe deer in the Tieli Forestry Bureau of the Lesser Xing’an Mountains. Our results revealed significant differences: (1) In terms of the quantity and quality of available forage, the summer–autumn home range had substantially more available forage than the winter home range, with meadows and cornfields showing the highest edible biomass in each, respectively. In terms of forage quality, there were differences in hemicellulose, cellulose, and lignin content between the two ranges. (2) In terms of the conditions for avoiding predation, the winter home range had lower vegetation coverage and greater visibility, making escape strategies more viable. In contrast, the summer–autumn home range had denser vegetation and limited visibility, making hiding strategies more viable. Our study offers comprehensive insights into the available forage and the conditions for avoiding predation, which is crucial for wildlife conservation strategies and habitat management in the region, as it directly informs strategies that address the seasonal forage requirements and predation avoidance of these deer, ultimately enhancing their prospects for survival in the area.

1. Introduction

The selection of habitat by animals has been a fundamental and central focus in both behavioral ecology and landscape ecology [1,2,3,4,5], as it is essential for effective wildlife management and conservation efforts [6,7,8,9]. Habitat selection is a complex process that involves the assessment of various factors, including the availability of forage, risk of predation, water/snow, reproductive states, human disturbance, competitor effects, etc. [10,11,12,13,14]. Among these factors, available forage and the conditions for avoiding predation are particularly important [15]. The quantity and quality of available forage directly impact individual growth and reproductive success, and the overall abundance of the population [16,17,18]. Animals often select habitats that provide optimal forage resources, allowing them to meet their nutritional needs and maintain healthy physiological conditions. Additionally, the conditions for avoiding predation significantly influence prey species’ survival and reproductive success [19,20,21]. By selecting habitats with suitable options for concealment and escape, prey species can enhance their chances of survival, reduce the risk of predation, and ultimately contribute to the population’s stability and persistence.
Many studies have examined the available forage provided by the surrounding environment for herbivorous animals. For example, the mature forests in the central east slopes of the Rocky Mountains in Alberta, Canada, provide an estimated herbaceous biomass of 43.02 g/m2 for elk (Cervus elaphus) [22]. The forestry bureaus of Genhe, Jinhe, Alongshan, and Mangui in Genhe City, Inner Mongolia, China, provide lichen plants with an average biomass of 40.33 kg/hm2, 49.91 kg/hm2, 103.56 kg/hm2, and 132.36 kg/hm2, respectively, for reindeer (Rangifer tarandus) [23]. However, most studies focus on assessing the overall available forage within larger areas, rather than specifically examining the supply within animals’ home ranges where they typically forage. Estimating the available forage within animals’ home ranges provides valuable insights into the actual dietary choices of animals during their daily foraging activities, which allows a more accurate and detailed understanding of the factors influencing habitat selection [24,25]. Meanwhile, many studies have only estimated aboveground or above-snow standing withered plants as a forage resource [26], neglecting the litterfall in winter. Actually, during winter when forage is scarce, cervids scrape away snow to seek forage in the litterfall on the ground, indicating that litterfall is an important source of forage for herbivorous animals in winter [27,28,29,30]. For example, the Yakushima sika deer (Cervus nippon yakushimae) in Japan consumes litterfall, which accounts for 45.6% of its diet in winter [31]. Therefore, research on animals’ available forage within their home ranges considering litterfall in winter is needed.
The conditions for avoiding predation have also been a subject of considerable attention, which contribute to an understanding of the mechanisms underlying the relationship between the habitat’s structure and the risk of predation of animals, especially for those herbivores who adopt strategies of escaping from predators instead of attacking [32,33,34]. Avoiding predation is a complex process that is influenced by various factors, including the preys’ ability to remain concealed, detect approaching predators, seek refuge or protection from them, etc. [32,35,36]. Among these factors, the conditions of concealment [37,38,39] and escape [40,41] are particularly important. Generally, the conditions of concealment refer to the features that hide the preys from predators, providing protection and reducing the likelihood of detection [42]. The availability of dense vegetation, such as thickets and dense forests, or intricate structural features, such as rocks and burrows, can provide concealment and shelter. For example, in the Northern Great Plains of the United States, newborn white-tailed deer (Odocoileus virginianus) select bed sites with understory vegetation with a greater height, which provides better visual concealment than the surrounding areas [43]. Research has indicated that the European rabbit (Oryctolagus cuniculus) can also use gaps between rocks as shelters [44]. However, few studies have used vegetation coverage, which is assessed visually within different height strata, to represent the conditions of concealment provided by vegetation. Usually, the conditions of escape (primarily visibility) refer to the features that provide sightlines for preys, enabling them to visually detect potential predators in their surroundings [42]. By choosing habitats that provide greater visibility, the preys can detect their predators earlier and flee from them quickly. For example, white-tailed deer and Alaskan moose (Alces alces gigas) select parturition sites at high elevations or with lower vegetation height to improve their visibility and increase their ability to escape approaching predators [45,46]. Currently, several indicators are used to describe these conditions, including “concealment”, “hiding cover”, “visibility”, etc., but these indicators are not standardized, which poses a challenge in obtaining a comprehensive and accurate understanding of the conditions for avoiding predation. Therefore, there is a need for research that makes a clear distinction between concealment conditions and escape conditions, and simultaneously considers the former with stratified coverage, and the latter with clear definitions.
The Siberian roe deer (Capreolus pygargus) is a common cervid species in the Lesser Xing’an Mountains, an important national forest area in China. In our study area, the predator of the Siberian roe deer is the lynx (Lynx lynx) [47,48,49,50]. In this study, we aimed to accurately measure the quantity and quality of available forage provided within the home ranges of the Siberian roe deer. Specifically, we considered both litterfall and standing withered plants as winter forage sources. We also aimed to measure the conditions for avoiding predation in terms of the conditions of both concealment and escape provided within the home ranges of the Siberian roe deer, and identified the measurement indicators based on clear definitions.

2. Materials and Methods

2.1. Study Area

The study was conducted in the Tieli Forestry Bureau (47°07′–47°12′ N, 128°15′–128°20′ E, an area of about 2039 km2) located in the Yijimi River Basin on the southern slope of the Lesser Xing’an Mountains of northeast China (Figure 1). The study area belongs to the cold temperate continental monsoon climate. The annual average temperature is 1.4 °C, with an average temperature of −23.1 °C in January and 21.4 °C in July. The annual average precipitation is 630 mm, which is mainly concentrated during June and August. The study area is characterized by low mountains and hills, with the main soil type being mountain dark brown soil. The zonal vegetation in this area belongs to the Changbai Mountain plant region, characterized by temperate coniferous and broadleaf mixed forests. Korean pine (Pinus koraiensis) is the dominant species, accompanied by various temperate broadleaf tree species [51]. Due to long-term human activities, the current forests are mostly secondary and agricultural fields have become one kind of landscape type [52]. Ungulates including the Siberian roe deer and the elk inhabit the study area, with the former being observed more frequently than the latter. Other major mammal species include the black bear (Ursus thibetanus) and the wild boar (Sus scrofa) [51,53].

2.2. Landscape Map

Referring to the forest vegetation map (1:100,000) and field survey data, we visually interpreted the Google satellite images (dated 11 September 2018) and obtained a landscape map of the study area. The study area consists of approximately 65% broadleaf forests, 16% coniferous forests, 8% mixed forests, 1% meadows, and 9% agricultural fields (including soybean fields, cornfields, and rice fields). The remaining 1% is composed of residential areas, industrial and mining areas, water, and roads.

2.3. Transect Design

We utilized the data retrieved from GPS collars (HQAN40S, Hunan Global Messenger Technology Co., Ltd., Changsha, China) fitted to the Siberian roe deer to estimate the home range. The data, which had an interval of 2 h, were retrieved from December 2018 to September 2019. We removed the data from Grades C (an accuracy of 20 m), D (an accuracy of 100 m), and E (an accuracy of 2000 m), and retained the data from Grades A (an accuracy of 5 m) and B (an accuracy of 10 m) [54].
In mid-December 2018, based on the GPS data available at the time and the preliminary activity ranges, we conducted surveys during the non-vegetation period in four different landscape types: forests, meadows, soybean fields, and cornfields. Specifically, we placed transects using a stratified sampling method and surveyed 13 transects in forests, 3 transects in meadows, 6 transects in soybean fields, and 3 transects in cornfields, totaling 25 transects with a length of 60 m each. Along each transect, we established 6 25 cm × 25 cm sampling plots [37,55] at 10 m intervals (Figure 1), obtaining a total of 151 sampling plots. Subsequently, using the data retrieved from 1 December 2018 to 31 March 2019, we calculated the winter home range using the 95% kernel density estimation (KDE) method [56]. The results indicated that all surveyed transects fell within this calculated range, demonstrating that the data from the transects could reflect the environmental conditions of the winter home range (Figure 1).
In early September 2019, based on the GPS data available at the time and the preliminary activity ranges, we conducted surveys during the vegetation period in seven different landscape types: broadleaf forests, coniferous forests, mixed forests, meadows, soybean fields, cornfields, and rice fields. Specifically, we placed transects using a stratified sampling method and surveyed 10 transects in broadleaf forests, 9 transects in coniferous forests, 1 transect in mixed forests, 10 transects in meadows, 5 transects in soybean fields, 4 transects in cornfields, and 3 transects in rice fields, totaling 42 transects with a length of 60 m each. Along each transect, we established 6 25 cm × 25 cm sampling plots at 10 m intervals (Figure 1), obtaining a total of 222 sampling plots. Subsequently, using the data retrieved from 1 July to 15 September 2019, we calculated the summer–autumn home range using the 95% KDE method. The results indicated that all surveyed transects fell within this calculated range, demonstrating that the data from the transects could reflect the environmental conditions of the summer–autumn home range (Figure 1).
We found evidence to show that this home range was inhabited by more than one Siberian roe deer. We surveyed the footprints discovered within the winter home range, which enabled us to roughly identify at least 3 to 5 roe deer. Similarly, we placed 24 camera traps using a grid method within the summer–autumn home range (Figure 1), successfully capturing images of other roe deer individuals.
Then, we conducted a field survey to investigate the available forage and the conditions for avoiding predation provided within the home ranges of the Siberian roe deer.

2.4. Field Survey

We investigated the latitude and longitude, elevation, slope, and aspect of each transect. We also recorded the conditions of concealment and escape provided by the vegetation in each 25 cm × 25 cm sampling plot.
Conditions of concealment: We used “vegetation coverage” to represent the conditions of concealment, that is, the extent to which animals can find concealment. Generally, higher vegetation coverage is linked to greater concealment. Vegetation coverage was determined by calculating the projection of the vegetation on the ground within a circular area with a radius of 2 m centered on the sampling plot [37]. For the Siberian roe deer, the shoulder height is typically between 0.67 and 0.78 m [57]. We investigated the vegetation coverage within a height range from the ground to 200 cm above the ground, where the deer can reach and forage, specifically within the height layers of 0–20 cm, 20–50 cm, 50–120 cm, and 120–200 cm [37]. In the forest landscape types, the vegetation coverage at 0–20 cm included fallen branches and leaves.
Conditions of escape: We used “visibility from the center to the surroundings”, referred to as “visibility” hereafter, to represent the conditions of escape. Usually, a higher visibility value indicates that preys are more likely to observe or perceive the presence of predators and have a better chance of escaping successfully [33]. Visibility was measured as the maximum distance visible from the center of the sampling plot [52]. One person stood at the center of the sampling plot with one end of a measuring tape, while another person walked in the four directions (east, south, west, and north) with the other end of the measuring tape. We recorded the measurement on the tape when the person at the center could no longer see the walking person. The average of the recorded measurements from the four directions was calculated as the visibility value.

2.5. Sampling Design

During the winter sampling period, we collected all plants, including litterfall, from ground level to 120 cm in each 25 cm × 25 cm sampling plot [58]. In the forests, some plants appeared withered and standing, while others had fallen to the ground surface as litterfall. The only distinguishable plant species in these areas was horsetails (Equisetum hyemale). Horsetails have green, hollow stems that can store water, making them an important source of forage for roe deer during winter. Therefore, we divided the samples in the forests into horsetails and other plant species, and also divided them into standing horsetails, standing other plants, fallen horsetails, and fallen other plants according to the plants’ status. In the soybean fields and cornfields, it is common to find some soybean (Glycine max) and corn (Zea mays) plants remaining on the ground surface as litterfall after mechanical harvesting. If residual soybean and corn plants were present in the sampling plot, we collected them; otherwise, we recorded the sample of that sampling plot as 0.
During the summer–autumn sampling period, we collected all green plants from ground level to 120 cm in each 25 cm × 25 cm sampling plot. These plants were then divided into woody plants, herbaceous plants, and crops, and were kept for further analysis.

2.6. Plant Sample Classification

The roe deer is a herbivore that consumes leaves, tender branches, stems, and sometimes crops in farmlands, as well as dried grass and fallen leaves in winter [59,60,61]. In the forests within the winter home range, and the broadleaf forests, coniferous forests, and mixed forests within the summer–autumn home range, all samples were edible except for the woody stems or branches with a basal diameter greater than 4 mm [58,62]. In the meadows within the winter and summer–autumn home ranges, all samples were edible [63]. In the agricultural fields, the soybean pods and beans were edible, as were the corn kernels and rice (Oryza sativa) ears [64]. After distinguishing the edible plant samples, we packed them separately into paper bags and air-dried them.

2.7. Measurement and Calculation of the Quantity of Available Forage

The air-dried edible samples were oven-dried (60 °C for 72 h) [55] and weighed to the nearest 0.01 g. The total weight of all edible samples from the same sampling plot represented the edible biomass of that sampling plot, serving as the quantity of available forage for the sampling plot.

2.8. Measurement and Calculation of the Quality of Available Forage

Usually, the quality of available forage is expressed as the energy and protein content [65]. Metabolizable energy originates in the digestible carbohydrates of the plant cell (pectin, hemicellulose, and cellulose) and other plant cell contents (soluble sugar and starch), while proteins are available mainly within the cell content [55,66]. However, lignin is the indigestible part of the cell wall and reduces the overall digestibility of the cell wall [66,67]. We pooled edible samples by landscape type and by forage category, ground them to a powder, and performed the chemical analyses described below.
We measured the fiber fractions: NDF (neutral detergent fiber), ADF (acid detergent fiber), and ADL (acid detergent lignin), with corrections for the ash fraction, using the sequential method of Van Soest [68]. The measurements were conducted using the ANKOM 2000i fiber analyzer (Beijing ANKOM Technology Co., Ltd., Beijing, China) [69]. Then, we calculated the relative content (as a percentage) of fibrous components as follows: hemicellulose = NDF-ADF, cellulose = ADF-ADL, and lignin = ADL. The relative content of the non-fibrous components was calculated as 100% minus the relative content of the fibrous components (non-fibrous = 100-NDF) [70]. We also measured the relative content (as a percentage) of carbon and nitrogen [71] using an elemental analyzer (Elementar Analysensysteme GmbH, Langenselbold, Germany).
Finally, we multiplied the relative content of the fibrous and non-fibrous components, carbon, and nitrogen by the respective quantity of available forage to obtain the absolute content of the fibrous and non-fibrous components, carbon, and nitrogen (g/m2).

2.9. Data Analysis

The calculations and analyses were performed using SPSS 20.0 software. We conducted a one-way analysis of variance (ANOVA) to compare the factors of available forage quantity, available forage quality, vegetation coverage, and visibility among home ranges, landscape types, and forage categories.

3. Results and Analysis

3.1. Available Forage

3.1.1. Quantity of Available Forage

Within the winter home range, among the four types of landscape, the meadows had the highest quantity of available forage and it was significantly different from the other three types (p < 0.05). The forests ranked next, in which the standing withered plants accounted for 35% and litterfall accounted for 65% of the available forage, with horsetails accounting for 10% and other plants accounting for 90% of the available forage quantity. The soybean fields were ranked after the forests. The cornfields had the lowest quantity of available forage. There was no significant difference among the forests, the soybean fields, and the cornfields (p > 0.05) (Table 1).
Within the summer–autumn home range, among the seven types of landscape, the cornfields had the highest quantity of available forage and it was significantly different from the other six types (p < 0.05). Next were the rice fields and the meadows, which exhibited significant differences from the other types (p < 0.05) except for the coniferous forests. The coniferous forests, which were ranked after them, did not exhibit significant differences from other types (p > 0.05) except for the cornfields. The soybean fields, the broadleaf forests, and the mixed forests had the lowest quantity of available forage, and these three types exhibited significant differences from the cornfields, the rice fields, and the meadows (p < 0.05). Herbaceous plants provided over 90% of the available forage and woody plants provided less than 10% of the available forage in the broadleaf forests, the mixed forests, the coniferous forests, and the meadows (Table 2). In comparison with the winter home range, there was a significant difference in the quantity of available forage within the summer–autumn home range (p < 0.05). The quantity of available forage within the summer–autumn home range was 2.6 times greater than that within the winter home range, with 388.40 g/m2 compared with 147.00 g/m2.

3.1.2. Quality of Available Forage

Within the winter home range, the relative content of fibrous components ranged from 8.10% to 67.39%. Among them, hemicellulose, cellulose, and lignin were highest in the meadows and lowest in the cornfields. The relative content of non-fibrous components ranged from 32.61% to 91.90%, being highest in the cornfields and lowest in the meadows. The relative content of nitrogen ranged from 0.73% to 3.63%, being highest in the soybean fields and lowest in the meadows. The relative content of carbon ranged from 38.45% to 45.25%, being highest in the soybean fields and lowest in the forests. There were significant differences in the relative content of the components of available forage among different landscape types (p < 0.05) (Table 3). In the forests, the relative content of fibrous components, nitrogen, and carbon in the standing withered plants was higher than that in the litterfall, while the relative content of non-fibrous components was lower than that in the litterfall. Meanwhile, the relative content of fibrous components, nitrogen, and carbon in other plant species was higher than that in horsetails, while the relative content of non-fibrous components was lower than that in horsetails.
Within the winter home range, the absolute content of hemicellulose, cellulose, and lignin in the fibrous components was highest in the meadows and lowest in the cornfields. The absolute content of non-fibrous components was highest in the meadows, followed by the forests, then the cornfields, and the soybean fields. The absolute content of nitrogen was highest in the meadows, followed by the soybean fields, then the forests, and lowest in the cornfields. The absolute content of carbon was highest in the meadows, which was significantly higher than in the other three types (p < 0.05). Meadows were followed by the forests, then the soybean fields, and finally the cornfields. There were significant differences in the absolute content of the components of available forage among different landscape types (p < 0.05) (Table 4). In the forests, the absolute content of fibrous components, non-fibrous components, nitrogen, and carbon in the litterfall was significantly higher than that in the standing withered plants (p < 0.05). Meanwhile, the absolute content of fibrous components, non-fibrous components, nitrogen, and carbon in other plant species was significantly higher than that in horsetails (p < 0.05).
Within the summer–autumn home range, the relative content of fibrous components ranged from 8.05% to 60.40%. Among them, hemicellulose was highest in the coniferous forests, cellulose was highest in the soybean fields, and lignin was highest in the broadleaf forests. All three were lowest in the cornfields. The relative content of non-fibrous components ranged from 39.60% to 91.95%, with the highest found in the cornfields and the lowest in the broadleaf forests. The relative content of nitrogen (1.32%–3.76%) and carbon (40.95%–45.76%) was highest in the soybean fields and lowest in the cornfields. There were significant differences in the relative content of the components of available forage among different landscape types (p < 0.05) (Table 5).
Compared with the winter home range (Table 3 and Table 5), there were significant differences in the relative content of hemicellulose, cellulose, lignin, and carbon within the summer–autumn home range (p < 0.05). Within the summer–autumn home range, the relative content of lignin, hemicellulose, nitrogen, and carbon was higher compared with the winter home range, with increases of 208%, 32%, 17%, and 6%, respectively. On the other hand, the relative content of cellulose and non-fibrous components was lower compared with the winter home range, with a decrease of 51% in cellulose and a decrease of only 7% in non-fibrous components.
Within the summer–autumn home range, the absolute content of hemicellulose, cellulose, and lignin in the fibrous components was highest in meadows, while the absolute content of hemicellulose was lowest in the soybean fields, the absolute content of cellulose was lowest in the cornfields, and the absolute content of lignin was lowest in the soybean fields. Non-fibrous components, nitrogen, and carbon had the highest absolute content in the cornfields, which was significantly higher than that in other types (p < 0.05). However, the absolute content of non-fibrous components was lowest in mixed forests, the absolute content of nitrogen was lowest in broadleaf forests, and the absolute content of carbon was lowest in the mixed forests. There were significant differences in the absolute content of the components of available forage among different landscape types (p < 0.05) (Table 6).
Compared with the winter home range (Table 4 and Table 6), there were significant differences in the absolute content of hemicellulose, lignin, non-fibrous components, nitrogen, and carbon within the summer–autumn home range (p < 0.05). Within the summer–autumn home range, the absolute content of hemicellulose, lignin, non-fibrous components, nitrogen, and carbon was higher than in the winter home range, with increases of 210%, 481%, 195%, 246%, and 181%, respectively. On the other hand, the absolute content of cellulose was lower than in the winter home range, with a decrease of 1%.

3.2. Conditions for Avoiding Predation

3.2.1. Conditions of Concealment

According to Figure 2a, within the winter home range, the vegetation coverage of different landscape types decreased with increasing height. The meadows had the highest vegetation coverage, and the plant composition was mainly dominated by Deyeuxia angustifolia, which grows to a height of 120–160 cm. During winter, the plants were in a withered and standing state. They provided conditions of concealment for the Siberian roe deer at four height layers. The forests ranked second. Among the four height layers, the vegetation coverage was highest in the 0–20 cm layer. The reason for this is that when assessing vegetation coverage in the forests, the coverage of litterfall was also included. The litterfall’s thickness was 5–15 cm, which could provide limited conditions of concealment for the Siberian roe deer. The cornfields ranked third and the soybean fields had the lowest vegetation coverage. The vegetation coverage in both of them was mainly formed by the plants remaining after mechanical harvesting, which were too scattered to provide effective conditions of concealment for the Siberian roe deer.
According to Figure 2b, within the summer–autumn home range, the rankings for vegetation coverage were as follows: meadows > rice fields > coniferous forests > cornfields > soybean fields > mixed forests > broadleaf forests. In the broadleaf forests, the vegetation coverage decreased with increasing height. In the agricultural fields, the vegetation coverage increased with increasing height. The vegetation coverage at 120–200 cm height was 0% for soybean fields and rice fields. The reason for this was that the height of soybeans and rice plants was below 120 cm, which meant they could only provide conditions of concealment for the Siberian roe deer within the 0–120 cm height range. In the meadows and coniferous forests, the vegetation coverage was highest at 20–50 cm. In the mixed forests, the vegetation coverage was lowest at 50–120 cm height.
The average vegetation coverage was 28% and 40%, respectively, within the winter home range and the summer–autumn home range. The average vegetation coverage within the summer–autumn home range was significantly higher than that within the winter home range (p < 0.05). Meanwhile, the vegetation coverage of each landscape type was also significantly higher within the summer–autumn home range compared with the winter home range (p < 0.05). Specifically, soybean fields and cornfields showed a much greater increase during the planting season compared with winter, with increases of 517% and 121%, respectively, while meadows showed a 24% increase.

3.2.2. Conditions of Escape

According to Figure 3a, within the winter home range, the soybean fields had the greatest visibility, followed by the cornfields and the meadows, and there were no significant differences among the three types (p > 0.05). The forests had the least visibility and showed significant differences from the other three types (p < 0.05). According to Figure 3b, within the summer–autumn home range, the rice fields and the soybean fields had the greatest visibility and differed significantly from the coniferous forests, the cornfields, the broadleaf forests, and the mixed forests (p < 0.05). The meadows came next and differed significantly from the broadleaf forests and the mixed forests (p < 0.05). The coniferous forests and the cornfields followed, and these two types differed significantly from the rice fields and the soybean fields (p < 0.05). The broadleaf forests and the mixed forests had the least visibility. There were significant differences in the visibility between these two types and the rice fields, the soybean fields, and the meadows (p < 0.05).
The average visibility was 171 m and 57 m, respectively, within the winter home range and the summer–autumn home range. The average visibility within the winter home range was significantly greater than that within the summer–autumn home range (p < 0.05). Meanwhile, the visibility of each landscape type was also significantly greater within the winter home range compared within the summer–autumn home range (p < 0.05). Specifically, the cornfields showed the greatest increase of 522%, followed by the meadows with an increase of 288%, and the soybean fields with an increase of 272%.

4. Discussion

4.1. Quantity of Available Forage

Our study indicated that the available forage within the winter home range was less than half of that within the summer–autumn home range. Generally, in northeastern China, the quantity of available forage during the winter season is significantly lower compared with the growing season because plants wither and leaves fall [72,73]. The winter plants include standing withered and litterfall, with the latter serving as an important source of forage for cervids [74]. Our study revealed that litterfall accounted for 65% of the total available forage of forests within the winter home range. If litterfall is overlooked, the calculated quantity of available forage may be lower than the actual amount, providing biased information for further modeling the spatial distribution of forage by remote sensing [75].
Our study indicated that open habitats (including agricultural fields and meadows) provided a greater amount of available forage compared with closed habitats within both the winter and summer–autumn home ranges. Several studies support our results, which reveal that open habitats have high light availability, leading to the higher productivity of the layer of shrubs and herbaceous vegetation [76]. Agricultural fields were one type of open habitats in our study area, providing fresh high-quality available forage (e.g., soybeans and corn crops) for the Siberian roe deer during the growing season. In winter, the few crop plants left after mechanical harvesting can also be utilized as available forage by the Siberian roe deer [52,77]. However, there are studies that contradict our results. For example, Li Bibo reported that open habitats (only agricultural fields) provided a lower amount of dry matter for cervids compared with closed habitats in the Qinglongtai Forest Farm during winter [78]. Over a decade ago, only a very small number of herbaceous plants, primarily dominated by wild sesame, were left after manual harvesting in the Qinglongtai Forest Farm, which barely provided forage for cervids [78]. The difference in available forage could be attributed to the different agricultural harvesting methods used in two study areas; the Qinglongtai Forest Farm employed manual harvesting with almost no crop residue, while the Tieli Forestry Bureau employed mechanical harvesting, resulting in a minor amount of crop residue. This indicated that agricultural management plays a crucial role in determining the quantity of available forage provided by agricultural fields during winter. As another type of open habitats, meadows were dominated by Deyeuxia angustifolia alongside perennial herbaceous plants such as Carex schmidtii and Filipendula palmata. The grass community in the meadows was dense, with a canopy cover of over 90% and an average height of approximately 120–160 cm. By contrast, the closed habitats, such as the forests, had a layer of shrubs and herbaceous vegetation with a canopy cover of about 50% and an average height of approximately 80–120 cm [79]. Additionally, many thicker woody stems and branches in the closed habitats were inedible. Therefore, closed habitats provided less biomass and less edible biomass than open habitats. Our results are supported by other studies; for example, Wang Le et al. reported that in the forest landscapes of the eastern part of the Northeast Tiger and Leopard National Park, the biomass of the understory vegetation in open habitats (gaps, edges, and riparian areas) was significantly higher than that in closed habitats (closed forests) [80].
It is clear that available forage is vital for the sustainability of the Siberian roe deer population. Our study shows that winter forage is scarce, but litterfall in forests contributes significantly to their diet during this season. Open habitats, including agricultural fields, provide substantial forage, especially during the growing season. However, the quantity of available forage depends on agricultural management practices. To ensure the deer population’s future survival, it is crucial to conserve natural habitats with litterfall and manage open habitats effectively, considering agricultural practices in the region.

4.2. Quality of Available Forage

Our study indicated that the litterfall in the forests within the winter home range had a high content of non-fibrous components and a low lignin content. Roe deer are known to prefer high-protein and low-fiber forage [64], so the litterfall is an important forage source in winter for this species.
Our study indicated that the quality of available forage within the winter home range was lower than that within the summer–autumn home range, which is consistent with the fact that the nutritional quality of forage in the harsh winter is lower than that in other seasons [81,82]. There are some studies that support our results [83,84]. For example, by measuring both the forage provided by the surrounding landscapes and the rumen contents of Mongolian gazelle, Li Junsheng et al. found that the content of crude protein was lowest in winter, while the content of detergent fiber and lignin were the highest in winter in the Xingqin area of Hulunbeir Grassland of northeastern China [85]. Our study indicated that there were significant differences in the relative content of fibrous components, non-fibrous components, carbon, and nitrogen among different landscape types, which were due to the varying composition of vegetation in different landscapes. The forests and meadows primarily consisted of herbaceous plants and woody plants, and had a higher content of fibrous components than agricultural fields, which mainly consisted of crops and had higher levels of non-fibrous components, carbon, and nitrogen. Wild ungulates select forage with a suitable ratio of nutrients (e.g., protein) and non-nutrients (e.g., lignin) [75,81], and ungulates’ preference for a particular plant species may be related to the trade-off between them [86].
The results of our research indicate that forage quality declines as the seasons transition from summer–autumn to winter, highlighting the seasonal impact on forage quality. It is worth noting that the influence of global warming is expected to have a substantial impact not only on the ecosystem as a whole but also specifically on the Siberian roe deer. As temperatures continue to rise, altering vegetation growth patterns and forage availability, the challenges faced by Siberian roe deer in obtaining high-quality winter forage are likely to intensify, potentially affecting their overall health and survival.

4.3. Conditions for Avoiding Predation

In our study, we implemented a clear and consistent system to define the conditions for avoiding predation, specifically focusing on the conditions of concealment and escape from the preys’ perspective, which was more reasonable. This approach was adopted to avoid any potential confusion arising from variations in the terminology and definitions used in previous studies. For instance, in Chinese studies, different terms such as “hiding cover”, “shelter class”, and “hidden level” have been used to refer to the visibility from the surroundings to the center [77,87,88]. Similarly, terms such as “sheltering class”, “sheltering”, and “concealment” have been used to describe the visibility from the center to the surroundings [89,90,91]. Meanwhile, some studies have used the visibility from the center to the surroundings to represent conditions of escape, but directionality is not specified in the term “visibility”, which may cause confusion [52]. Therefore, the establishment of the system of definition used in our study could unify the different indicators and facilitate comparisons among different studies.
Our study revealed the environmental conditions provided within the home ranges of the Siberian roe deer, with lower vegetation coverage and greater visibility favoring escape in the winter home range, and higher vegetation coverage and less visibility favoring concealment in the summer–autumn home range. Camp et al. considered that concealment and visibility represent opposing properties of cover [42]. In other words, cover that shields a prey from a predator’s detection also reduces the prey’s visibility, diminishing its ability to detect predator early and escape capture [42]. However, our research revealed that concealment and visibility are not necessarily negatively correlated. On the one hand, animals could choose locations with both greater concealment and greater visibility. The location offers excellent concealment, preventing predators from detecting preys, while also providing good visibility for preys to detect predators. Like a ‘fortress’, when an animal is inside the ‘fortress’, the predator could not perceive it, but it can easily spot the predator. For instance, meadows within the winter home range could provide roe deer with both greater concealment and greater visibility. On the other hand, there were habitats with less concealment and less visibility, such as the broadleaf forests within the summer–autumn home range.
Our study revealed the available forage and the conditions for avoiding predation in various landscape types. In situations where no single habitat can provide all the necessary resources simultaneously, in order to obtain enough resources to satisfy their requirements [92], animals are likely to allocate their time across different habitat types [37]. For example, Mysterud and Ostbye (1995) considered that roe deer prefer to rest below heavy canopy cover, whereas they feed in areas with little or no canopy cover [93]. According to our results, probably due to the fact that agricultural fields could provide greater quantity and quality of forage compared to the forests, Siberian roe deer are willing to take the increasing risk of predations to forage in open agricultural fields. When they rest, they would choose locations in the forests with greater concealment but less forage. Therefore, this combination of habitat types can simultaneously meet the survival needs of Siberian roe deer in terms of both available forage and the conditions for avoiding predation [94,95].

5. Conclusions

Our study quantified available forage and the conditions for avoiding predation provided within the home ranges of Siberian roe deer. In terms of the quantity of available forage provided by the home ranges, the amount of available forage in northern regions is significantly lower during winter compared with summer–autumn because plants wither and leaves fall. Litterfall plays a crucial role as an important source of forage for the Siberian roe deer during winter. The disparity in the quantity of available forage between open habitats and closed habitats in both seasons can be attributed not only to natural conditions but also factors such as agricultural management practices and the composition of the vegetation in the landscape. In terms of the quality of available forage provided by the home ranges, the nutritional quality of available forage was lower in winter compared with that in summer–autumn. The nutritional quality of litterfall during winter is particularly significant. In terms of the conditions for avoiding predation provided by the home ranges, a lower vegetation coverage and greater visibility in winter may be more favorable for the escape strategy of the roe deer, while a higher vegetation coverage and less visibility in summer–autumn may be more favorable for the hiding strategy of the roe deer.

Author Contributions

Conceptualization, Y.L. (Yueyuan Li), Y.L. (Yuehui Li) and Y.H.; Methodology, Y.L. (Yueyuan Li), Y.L. (Yuehui Li) and Y.H.; Formal analysis, Y.L. (Yueyuan Li), Y.L. (Yue Li) and J.G.; Investigation, Y.L. (Yue Li), J.G., X.S. and H.G.; Writing—original draft, Y.L. (Yueyuan Li); Writing—review & editing, Y.L. (Yueyuan Li), Y.L. (Yuehui Li) and Y.H.; Project administration, Y.L. (Yuehui Li); Funding acquisition, Y.L. (Yuehui Li). All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China, grant numbers: 41871197, 41271201, 42271108.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Sampling transect design within the winter and summer–autumn home ranges of the Siberian roe deer (Capreolus pygargus) in the Lesser Xing’an Mountains.
Figure 1. Sampling transect design within the winter and summer–autumn home ranges of the Siberian roe deer (Capreolus pygargus) in the Lesser Xing’an Mountains.
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Figure 2. Vegetation coverage at four height layers in different landscape types within the winter and summer–autumn home ranges of the Siberian roe deer in the Lesser Xing’an Mountains. (a) The samples in different landscape types within the winter home range were from forests (n = 79), meadows (n = 18), soybean fields (n = 36), and cornfields (n = 18). (b) The samples in different landscape types within the summer–autumn home range were from broadleaf forests (n = 70), coniferous forests (n = 56), mixed forests (n = 7), meadows (n = 71), soybean fields (n = 5), cornfields (n = 4), and rice fields (n = 3). Statistical differences are denoted by lowercase letters, with a significance level of 0.05. Different lowercase letters in the same height layer denote significant differences in vegetation coverage among landscape types (p < 0.05).
Figure 2. Vegetation coverage at four height layers in different landscape types within the winter and summer–autumn home ranges of the Siberian roe deer in the Lesser Xing’an Mountains. (a) The samples in different landscape types within the winter home range were from forests (n = 79), meadows (n = 18), soybean fields (n = 36), and cornfields (n = 18). (b) The samples in different landscape types within the summer–autumn home range were from broadleaf forests (n = 70), coniferous forests (n = 56), mixed forests (n = 7), meadows (n = 71), soybean fields (n = 5), cornfields (n = 4), and rice fields (n = 3). Statistical differences are denoted by lowercase letters, with a significance level of 0.05. Different lowercase letters in the same height layer denote significant differences in vegetation coverage among landscape types (p < 0.05).
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Figure 3. Visibility in different landscape types within the winter and summer–autumn home ranges of the Siberian roe deer in the Lesser Xing’an Mountains. (a) The samples in different landscape types within the winter home range were from forests (n = 79), meadows (n = 18), soybean fields (n = 36), and cornfields (n = 18). (b) The samples in different landscape types within the summer–autumn home range were from broadleaf forests (n = 70), coniferous forests (n = 56), mixed forests (n = 7), meadows (n = 71), soybean fields (n = 5), cornfields (n = 4), and rice fields (n = 3). Statistical differences are denoted by lowercase letters, with a significance level of 0.05. Different lowercase letters denote significant differences in visibility among landscape types (p < 0.05).
Figure 3. Visibility in different landscape types within the winter and summer–autumn home ranges of the Siberian roe deer in the Lesser Xing’an Mountains. (a) The samples in different landscape types within the winter home range were from forests (n = 79), meadows (n = 18), soybean fields (n = 36), and cornfields (n = 18). (b) The samples in different landscape types within the summer–autumn home range were from broadleaf forests (n = 70), coniferous forests (n = 56), mixed forests (n = 7), meadows (n = 71), soybean fields (n = 5), cornfields (n = 4), and rice fields (n = 3). Statistical differences are denoted by lowercase letters, with a significance level of 0.05. Different lowercase letters denote significant differences in visibility among landscape types (p < 0.05).
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Table 1. Edible biomass (g/m2) and standard deviations (SD) within the winter home range of the Siberian roe deer (Capreolus pygargus) in the Lesser Xing’an Mountains.
Table 1. Edible biomass (g/m2) and standard deviations (SD) within the winter home range of the Siberian roe deer (Capreolus pygargus) in the Lesser Xing’an Mountains.
Forage CategoryMeadows
(n = 18)		Forests
(n = 80)		Soybean Fields
(n = 36)		Cornfields
(n = 17)
HorsetailsOther PlantsSoybeansSoybean Pods
Standing withered416.40 ± 209.279.84 ± 27.5738.19 ± 46.82———
Litterfall—4.04 ± 11.5186.98 ± 53.3331.26 ± 36.3140.89 ± 85.8457.64 ± 233.31
Total416.40 ± 209.27 a139.06 ± 65.26 b72.16 ± 97.39 b57.64 ± 233.31 b
Statistical differences are denoted by lowercase letters, with a significance level of 0.05. Different lowercase letters in the same row denote significant differences in edible biomass among landscape types (p < 0.05).
Table 2. Edible biomass (g/m2) and standard deviations (SD) within the summer–autumn home range of the Siberian roe deer in the Lesser Xing’an Mountains.
Table 2. Edible biomass (g/m2) and standard deviations (SD) within the summer–autumn home range of the Siberian roe deer in the Lesser Xing’an Mountains.
Forage CategoryCornfields
(n = 12)		Rice Fields
(n = 3)		Meadows
(n = 64)		Coniferous Forests
(n = 62)		Soybean Fields
(n = 5)		Broadleaf Forests
(n = 69)		Mixed Forests
(n = 7)
Woody——6.24 ± 22.0116.38 ± 40.12—15.28 ± 28.976.24 ± 8.93
Herbaceous——549.43 ± 172.27346.81 ± 233.34—149.36 ± 108.88144.46 ± 61.44
Crops1081.08 ± 526.76593.83 ± 65.75——198.05 ± 20.55——
Total1081.08 ± 526.76 a593.83 ± 65.75 b555.67 ± 176.15 b363.19 ± 223.89 bc198.05 ± 20.55 c164.64 ± 108.94 c150.70 ± 63.04 c
Statistical differences are denoted by lowercase letters, with a significance level of 0.05. Different lowercase letters in the same row denote significant differences in edible biomass among landscape types (p < 0.05).
Table 3. Relative content of the components of available forage (as a percentage) and standard deviations (SD) within the winter home range of the Siberian roe deer in the Lesser Xing’an Mountains.
Table 3. Relative content of the components of available forage (as a percentage) and standard deviations (SD) within the winter home range of the Siberian roe deer in the Lesser Xing’an Mountains.
Landscape TypeForage CategoryHemicelluloseCelluloseLigninNon-Fibrous ComponentsNitrogenCarbon
ForestsStanding horsetails9.93 ± 0.2430.40 ± 0.461.05 ± 0.0558.62 ± 0.721.36 ± 0.0135.88 ± 0.12
Standing other plants16.21 ± 0.8524.51 ± 1.0813.17 ± 1.1246.11 ± 2.141.53 ± 0.0341.50 ± 0.06
Fallen horsetails9.62 ± 0.4031.72 ± 0.971.20 ± 0.2257.46 ± 1.341.22 ± 0.0135.14 ± 0.07
Fallen other plants15.32 ± 0.7923.67 ± 2.9912.81 ± 3.2748.20 ± 1.701.44 ± 0.1641.27 ± 0.38
Subtotal12.77 ± 3.08 b27.58 ± 3.91 ab7.06 ± 6.18 ab52.60 ± 5.73 b1.39 ± 0.14 b38.45 ± 2.96 b
MeadowsHerbaceous plants20.98 ± 0.26 a34.76 ± 0.70 a11.65 ± 2.28 a32.61 ± 1.80 c0.73 ± 0.03 b43.67 ± 0.04 a
Soybean fieldsSoybeans5.84 ± 0.947.08 ± 0.090.31 ± 0.1786.77 ± 1.006.00 ± 0.0348.99 ± 0.07
Soybean pods17.06 ± 0.6934.38 ± 0.6110.12 ± 0.5738.44 ± 1.611.26 ± 0.0541.51 ± 0.03
Subtotal11.45 ± 5.67 b20.73 ± 13.66 b5.21 ± 4.92 ab62.61 ± 24.20 b3.63 ± 2.37 a45.25 ± 3.74 a
CornfieldsCorn5.07 ± 0.75 c2.93 ± 0.29 c0.10 ± 0.03 b91.90 ± 1.05 a1.41 ± 0.01 b41.90 ± 0.08 ab
Total12.50 ± 5.3923.68 ± 11.546.30 ± 5.9057.51 ± 20.181.87 ± 1.5841.23 ± 4.07
Statistical differences are denoted by lowercase letters, with a significance level of 0.05. Different lowercase letters in the same column denote significant differences in the components of available forage among landscape types (p < 0.05).
Table 4. Absolute content of the components of available forage (g/m2) and standard deviations (SD) within the winter home range of the Siberian roe deer in the Lesser Xing’an Mountains.
Table 4. Absolute content of the components of available forage (g/m2) and standard deviations (SD) within the winter home range of the Siberian roe deer in the Lesser Xing’an Mountains.
Landscape TypeForage CategoryHemicelluloseCelluloseLigninNon-Fibrous ComponentsNitrogenCarbon
ForestsStanding horsetails0.98 ± 2.742.99 ± 8.380.10 ± 0.295.77 ± 16.160.13 ± 0.373.53 ± 9.89
Standing other plants6.19 ± 7.599.36 ± 11.475.03 ± 6.1717.61 ± 21.590.58 ± 0.7215.85 ± 19.43
Fallen horsetails0.39 ± 1.111.28 ± 3.650.05 ± 0.142.32 ± 6.610.05 ± 0.141.42 ± 4.04
Fallen other plants13.33 ± 8.1720.59 ± 12.6211.14 ± 6.8341.93 ± 25.711.25 ± 0.7735.90 ± 22.01
Subtotal17.76 ± 8.33 b38.35 ± 18.00 b9.82 ± 4.61 b73.15 ± 34.33 b1.93 ± 0.91 ab53.47 ± 25.09 b
MeadowsHerbaceous plants87.36 ± 43.90 a144.74 ± 72.74 a48.51 ± 24.38 a135.79 ± 68.24 a3.04 ± 1.53 a181.84 ± 91.39 a
Soybean fieldsSoybeans1.83 ± 2.122.21 ± 2.570.10 ± 0.1127.13 ± 31.511.88 ± 2.1815.32 ± 17.79
Soybean pods6.98 ± 14.6514.06 ± 29.514.14 ± 8.6915.72 ± 33.000.52 ± 1.0816.97 ± 35.63
Subtotal8.26 ± 11.15 bc14.96 ± 20.19 c3.76 ± 5.07 bc45.18 ± 60.98 b2.62 ± 3.54 a32.65 ± 44.07 b
CornfieldsCorn2.92 ± 11.83 c1.69 ± 6.84 c0.06 ± 0.23 c52.97 ± 214.41 b0.81 ± 3.29 b24.15 ± 97.76 b
Total22.12 ± 30.1341.33 ± 50.0311.89 ± 16.7271.67 ± 87.312.10 ± 2.2760.51 ± 69.86
Statistical differences are denoted by lowercase letters, with a significance level of 0.05. Different lowercase letters in the same column denote significant differences in the components of available forage among landscape types (p < 0.05).
Table 5. Relative content of the components of available forage (as a percentage) and standard deviations (SD) within the summer–autumn home range of the Siberian roe deer in the Lesser Xing’an Mountains.
Table 5. Relative content of the components of available forage (as a percentage) and standard deviations (SD) within the summer–autumn home range of the Siberian roe deer in the Lesser Xing’an Mountains.
Landscape TypeForage CategoryHemicelluloseCelluloseLigninNon-Fibrous ComponentsNitrogenCarbon
Broadleaf forestsWoody21.34 ± 0.919.60 ± 1.9223.53 ± 2.3645.53 ± 0.572.18 ± 0.0243.64 ± 0.03
Herbaceous19.18 ± 3.025.36 ± 2.8945.02 ± 6.2833.67 ± 5.222.07 ± 0.0344.24 ± 0.01
Subtotal20.26 ± 2.48 a7.91 ± 3.14 ab34.28 ± 11.75 a39.60 ± 6.99 d2.13 ± 0.06 c43.94 ± 0.30 bc
Coniferous forestsWoody21.36 ± 0.838.33 ± 0.5925.67 ± 1.0544.64 ± 1.572.69 ± 0.0144.71 ± 0.07
Herbaceous22.62 ± 0.8618.72 ± 2.6718.13 ± 2.7740.53 ± 2.041.82 ± 0.0143.11 ± 0.04
Subtotal21.99 ± 1.05 a13.52 ± 5.55 a21.90 ± 4.31 bc42.59 ± 2.75 cd2.26 ± 0.43 c43.91 ± 0.80 bc
Mixed forestsWoody20.67 ± 2.874.92 ± 2.4828.32 ± 2.5546.09 ± 3.943.03 ± 0.0444.52 ± 0.05
Herbaceous16.71 ± 0.9521.55 ± 2.0224.71 ± 4.1337.02 ± 2.112.32 ± 0.0141.53 ± 0.08
Subtotal18.69 ± 2.91 a13.24 ± 8.62 a26.52 ± 3.88 ab41.55 ± 5.53 cd2.67 ± 0.36 b43.03 ± 1.50 c
MeadowsWoody11.45 ± 0.617.57 ± 0.9716.50 ± 1.4664.48 ± 1.231.85 ± 0.0245.84 ± 0.01
Herbaceous27.04 ± 0.1417.92 ± 3.1814.93 ± 4.5940.12 ± 1.301.54 ± 0.0143.47 ± 0.07
Subtotal19.25 ± 7.81 a12.74 ± 5.68 a15.72 ± 3.50 cd52.30 ± 12.25 c1.69 ± 0.15 d44.66 ± 1.18 ab
Soybean fieldsCrops8.35 ± 1.13 b15.34 ± 1.07 a5.42 ± 0.75 e70.88 ± 2.21 b3.76 ± 0.03 a45.76 ± 0.03 a
CornfieldsCrops4.75 ± 0.13 b0.86 ± 0.15 b2.89 ± 0.65 e91.95 ± 0.11 a1.32 ± 0.01 d40.95 ± 0.07 d
Rice fieldsCrops8.24 ± 1.73 b11.40 ± 0.52 a8.11 ± 0.87 de72.26 ± 2.13 b1.43 ± 0.00 d41.59 ± 0.30 d
Total16.52 ± 7.0311.56 ± 6.3919.38 ± 11.8753.38 ± 17.912.18 ± 0.7043.58 ± 1.59
Statistical differences are denoted by lowercase letters, with a significance level of 0.05. Different lowercase letters in the same column denote significant differences in the components of available forage among landscape types (p < 0.05).
Table 6. Absolute content of the components of available forage (g/m2) and standard deviations (SD) within the summer–autumn home range of the Siberian roe deer in the Lesser Xing’an Mountains.
Table 6. Absolute content of the components of available forage (g/m2) and standard deviations (SD) within the summer–autumn home range of the Siberian roe deer in the Lesser Xing’an Mountains.
Landscape TypeForage CategoryHemicelluloseCelluloseLigninNon-Fibrous ComponentsNitrogenCarbon
Broadleaf forestsWoody3.26 ± 6.181.47 ± 2.783.59 ± 6.826.96 ± 13.190.33 ± 0.636.67 ± 12.64
Herbaceous28.65 ± 20.888.01 ± 5.8467.24 ± 49.0250.29 ± 36.663.09 ± 2.2566.08 ± 48.17
Subtotal33.36 ± 22.07 bc13.02 ± 8.62 c56.44 ± 37.35 ab65.20 ± 43.14 d3.51 ± 2.32 b72.34 ± 47.87 c
Coniferous forestsWoody3.50 ± 8.571.36 ± 3.344.20 ± 10.307.31 ± 17.910.44 ± 1.087.32 ± 17.94
Herbaceous78.45 ± 52.7864.92 ± 43.6862.88 ± 42.30140.56 ± 94.576.31 ± 4.25149.51 ± 100.59
Subtotal79.87 ± 49.23 ab49.10 ± 30.27 ab79.54 ± 49.03 a154.68 ± 95.35 cd8.21 ± 5.06 ab159.48 ± 98.31 bc
Mixed forestsWoody1.29 ± 1.850.31 ± 0.441.77 ± 2.532.88 ± 4.110.19 ± 0.272.78 ± 3.97
Herbaceous24.14 ± 10.2731.13 ± 13.2435.70 ± 15.1853.48 ± 22.753.35 ± 1.4359.99 ± 25.52
Subtotal28.17 ± 11.78 bc19.95 ± 8.35 bc39.96 ± 16.72 ab62.61 ± 26.19 d4.02 ± 1.68 b64.85 ± 27.13 c
MeadowsWoody0.71 ± 2.520.47 ± 1.671.03 ± 3.634.02 ± 14.200.12 ± 0.412.86 ± 10.09
Herbaceous148.57 ± 46.5898.46 ± 30.8782.03 ± 25.72220.43 ± 69.128.46 ± 2.65238.84 ± 74.89
Subtotal106.97 ± 33.91 a70.79 ± 22.44 a87.35 ± 27.69 a290.62 ± 92.12 bc9.39 ± 2.98 ab248.16 ± 78.67 b
Soybean fieldsCrops16.54 ± 1.72 c30.38 ± 3.15 bc10.73 ± 1.11 b140.37 ± 14.56 cd7.45 ± 0.77 b90.63 ± 9.40 c
CornfieldsCrops51.35 ± 25.02 abc9.30 ± 4.53 c31.24 ± 15.22 ab994.05 ± 484.36 a14.27 ± 6.95 a442.70 ± 215.71 a
Rice fieldsCrops48.93 ± 5.42 bc67.70 ± 7.50 a48.16 ± 5.33 ab429.10 ± 47.51 b8.49 ± 0.94 ab249.11 ± 27.58 b
Total68.53 ± 46.6040.83 ± 32.0869.14 ± 41.15211.25 ± 248.287.26 ± 4.79169.95 ± 130.26
Statistical differences are denoted by lowercase letters, with a significance level of 0.05. Different lowercase letters in the same column denote significant differences in the components of available forage among landscape types (p < 0.05).
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Li, Y.; Li, Y.; Hu, Y.; Li, Y.; Guo, J.; Shao, X.; Gao, H. Available Forage and the Conditions for Avoiding Predation of the Siberian Roe Deer (Capreolus pygargus) in the Lesser Xing’an Mountains. Forests 2023, 14, 2072. https://doi.org/10.3390/f14102072

AMA Style

Li Y, Li Y, Hu Y, Li Y, Guo J, Shao X, Gao H. Available Forage and the Conditions for Avoiding Predation of the Siberian Roe Deer (Capreolus pygargus) in the Lesser Xing’an Mountains. Forests. 2023; 14(10):2072. https://doi.org/10.3390/f14102072

Chicago/Turabian Style

Li, Yueyuan, Yuehui Li, Yuanman Hu, Yue Li, Jia Guo, Xuefeng Shao, and Huifang Gao. 2023. "Available Forage and the Conditions for Avoiding Predation of the Siberian Roe Deer (Capreolus pygargus) in the Lesser Xing’an Mountains" Forests 14, no. 10: 2072. https://doi.org/10.3390/f14102072

APA Style

Li, Y., Li, Y., Hu, Y., Li, Y., Guo, J., Shao, X., & Gao, H. (2023). Available Forage and the Conditions for Avoiding Predation of the Siberian Roe Deer (Capreolus pygargus) in the Lesser Xing’an Mountains. Forests, 14(10), 2072. https://doi.org/10.3390/f14102072

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