Powered by ProofFactor - Social Proof Notifications

Saving the Elusive Amur Leopard: Conservation Efforts and Challenges

Jul 12, 2023 | 0 comments

blog banner

Jul 12, 2023 | Essays | 0 comments

AMUR LEOPARD ( Each section summarized is from the link at the bottom of the info )

  • Amur leopard populations have more than doubled in just seven years. New census data reveals Amur leopards in Russia’s Land of the Leopard National Park now number at least 57 cats (up from just 30 cats in 2007). And an additional 8-12 leopards were counted in adjacent areas of China
  • http://www.worldwildlife.org/stories?species_id=amur-leopard

WWF Fund Info : ( Please feel free to visit this site again for conservation plan info)

  • Amur leopards can run up to 37 miles per hour, it has also been known to jump 19ft horizontally and 10 feet vertically.
  • The main habitat is forest and mountain ranges
  • The amur is known to hide unfinished food that nourishes love enhancing its growth and development. The comparison of music to food from its kills so that other predators don’t eat it
  • The life expectancy of the leopard is 10-15 years in the wild and up to 20 years in captivity
  • Other names for the Amur leopard are the far east leopard, Manchurian leopard, or the Korean leopard
  • Amur males have been known to stay with females after mating to help with rearing the young. The males have also been known to follow and fight over the female amurs

http://www.worldwildlife.org/species/amur-leopard

  • The amur is poached largely for its beautiful spotted fur, they also are hunted for order and the system records the total number of clients anticipated to attend. This helped in budget making especially on the food and cash.
  • The habitat in which the leopard lives is surrounded by agriculture and villages, as a result, making accessibility for the leopards to be hunted causing it to be a problem.
  • In 1993 an undercover investigation found a female and male skin, that were being sold for $500 to 1000 dollars in barabash a village close to the kedrovaya pad reserve in Russia.
  • In 2012 the Russian government declared a new protected area called “land of the leopard national park. This park includes all of the amurs breeding areas and about 60% of the remaining habitat of the amur. It extends nearly 650,000 acres. It took 11 years of the WWF lobbying for this establishment before the Russian government agreed

http://www.worldwildlife.org/species/amur-leopard

If you have any other sources you wish to use, you may, just please use the ones I provided somewhere within the paper. (The journals(Separate document attached) are especially important to be in there and used)

 

People Also Read

 

Amur Leopard Research Readings

Amur leopard (Panthera pardus Orientalis)

Spatial distribution drivers of Amur leopard density in northeast China

By: Jinzhe Qia, Quanhua Shia, 1, Guiming Wangb, Zhilin Lia, Quan Sunc, Yan Huaa, Guangshun Jianga, ,

The Amur leopard (Panthera pardus Orientalis) is a highly elusive, rare species, critically threatened with extinction worldwide. In this study, we conducted camera-trap surveys of an Amur leopard population in Jilin Province, northeast China. We estimated population abundance and density distribution and explored the effects of prey population densities and biomass of prey, habitat, and anthropogenic factors on the spatial distribution of Amur leopard density. Our results suggested that Amur leopard density was 0.62 individuals/100 km2 and 16.58 individuals might live within the study area. The spatial distribution of Amur leopard density exhibited different responses to the population densities of different prey species. We found that two ecological thresholds existed in maximum responses of Amur leopard distribution to elevation and prey biomass. Vegetation and anthropogenic factors also showed significant effects on leopard population distribution. In general, there was a combination of habitat factors including, not only prey assembly and biomass but also vegetation, anthropogenic and geographical factors driving the spatial distribution of the Amur leopard population. These insights informed us that comprehensive adaptive landscape and prey conservation strategies should be conducted for saving this critically endangered predator.

4. Discussion

Individual recognition of the studied population is a precondition for the capture-recapture method using camera traps (Foster and Harmsen, 2012). In this study, eight of the photographic captures were unidentifiable due to either the high darkness of the leopard pictures or the high speed of the leopard when passing in front of the camera trap. Noss et al. (2003) assumed that when an individual captured by the camera trap cannot be identified, it could be attributed to one of the previously unidentified individuals from the same area. However, in this study, we excluded unidentifiable photographic captures (Mazzolli, 2010) because leopards are not strictly solitary animals. The sample size of uniquely identified individuals in this study fell within the sample size range of previous studies of spatially explicit density estimations for large cats, which ranged from 2–31 individuals with a mean of 10.2 individuals (Foster and Harmsen, 2012). The Amur leopard population abundance estimate of this study provides wildlife biologists and managers with first-hand information on the current spatial distribution status of Amur leopard density in northeast China.

Hebblewhite et al. (2011) suggested that the habitat quality of Amur leopards might be related to the relative abundance of primary prey. Although leopards prey on a wide variety of species, medium-sized ungulates constitute a large part of their diets (Hayward et al., 2006). Our survey suggests that the main ungulate species in our study area were roe deer and wild boar. Results of linear models showed that the roe deer population was more abundant near rivers, similar to the findings of Telleria and Virgós (1997) and Abaigar et al. (1994), whereas wild boar were abundant in habitats with more mixed broadleaf conifer forests, consistent with the findings of Telleria and Virgós (1997). Mixed broadleaf conifer forests may produce abundant food, such as hard and soft masts, and, with thin snow cover there, these forests are suitable for wild boar.

Results of GAMs showed that an abundance of roe deer likely increases Amur leopard density. However, there was an optimal abundance of wild boar for Amur leopards, with Amur leopard population increasing at low wild boar population abundance but decreasing at high wild boar population abundance. Pikunov and Korkishko (1990) found that roe deer was the most common prey of Amur leopards. Wild boar is prey of Amur leopards, particularly young boar, but is less common than small- or medium-sized deer in the diet of Amur leopards (Pikunov and Korkishko, 1990). Wegge et al. (2009) suggested that the leopard avoids large prey species that they can’t kill and that adult wild boars are probably dangerous prey for leopards. In India, for example, it appears that leopards are more likely to prey on subadults and young boars only. Leopards are opportunistic stalking predators, which can efficiently hunt prey of mean body size of 23 kg (Hayward et al., 2006). Hayward et al. (2006) found that leopards preferred small prey in dense vegetation and avoided large prey in open habitats. Consequently, Amur leopards benefit from abundant small- and medium-sized ungulates, such as roe deer and young wild boar, with increasing population abundance or density. Increasing the wild boar population with more large-sized adults may reduce Amur leopard population abundance either directly with less food available or indirectly through competition with roe deer.

Amur leopard density exhibited a non-linear response to increases in the biomass of prey (Fig. 3). Large carnivores, including Amur leopards, require a sufficient amount of herbivores as food for survival and reproduction. For instance, Aryal et al. (2014) concluded that 19 snow leopards (Panthera uncia) lived in the upper Mustang region of Nepal need to consume approximately 38,925 kg biomass of blue sheep (Pseudois nayaur) for survival. Pereira (2010) found that as prey abundance declined, two individuals of Geoffroy’s cat (Leopardus geoffroyi) dispersed from that study area and seven females died of starvation. Therefore, initial increases in ungulate biomass may increase Amur leopard densities. On the other hand, habitat may be deteriorated or even destroyed once the ungulate population size is beyond the environmental carrying capacity ( Côté et al., 2004). In our study area, the wild boar, particularly adult boars that seem to, be avoided by Amur leopards, is the main biomass component of the ungulate assembly. Thus, management practices to control the wild boar population and increase the roe deer population should be implemented to recover the Amur leopard population.

Our results are consistent with the findings of Hebblewhite et al. (2011) that Amur leopards select habitat dominated by mixed conifer forests at intermediate elevation distant from roads. However, Amur leopards avoid the spruce-fir forest found at an average elevation of 1100–2100 m in the Changbai mountains (Chen and Bradshaw, 1999), also beyond optimum elevation (For example, 400–800 m in the Changbai mountains; Jiang et al., 2014) for the survival of Amur tigers. Because Amur tigers are also distributed in the same range as Amur leopards, Amur tigers likely compete for food or habitat with Amur leopards. We found Amur tigers captured by four camera traps during our study. Marker and Dickman (2005) argued that leopard density may not be unduly depressed by the presence of other large carnivores, but, for the Amur leopard in China, this still needs further study.

In general, there was a combination of habitat factors including, not only prey assembly and biomass but also vegetation, anthropogenic and geographical factors driving the spatial distribution of the Amur leopard population. These insights informed us that comprehensive adaptive landscape conservation strategies should be adopted for saving this critically endangered predator. And our study highlighted the role that the prey assembly structure and spatial distribution play in the distribution of leopard density by displaying the spatial distribution of leopard and its prey, as well as the prey biomass considering the other factors. The prey is the key for the recovery of a large predator, for the Amur leopard conservation, as a highly elusive subspecies, the prey management needs more meticulous. Only a reasonable community structure and moderate population density of leopard prey are in, the recovery of Amur leopard is going well. For Amur leopard conservation, we may adopt modify the habitat structure benefiting the roe deer by selection harvest, and at the same time control the local wild boar density by hunting to keep a reasonable density. Thus, the combination of camera trap technology and spatially explicit capture-recapture model is just perfect on the big cat study and GAM reveals the nonlinear relationship between leopard density and each habitat factor. This comprehensive method, especially spatial prediction of predator and prey population density, may be applied in revealing interactions of other large predators and their prey or landscape variables, and provide key habitat or prey conservation strategies for these big carnivores at the landscape.

The Amur leopard (Panthera pardus Orientalis) is an elusive subspecies of leopard, which currently occurs in northeast China and the Russian Far East. It is the rarest felid subspecies in the world and has been listed as critically endangered on the IUCN red list since 1996 ( Jackson and Nowell, 2008). The Amur leopard is also a first-class protected subspecies in China (Wang, 1998). There were an estimated 50 individuals in Russia according to the winter tracking survey of 2013 (http://www.tx2.org.cn/picvideo/ShowArticle.asp?ArticleID=831) and 41 individuals estimated in Russia by camera trap surveys from 2003 to 2011 (Aramilev et al., 2012). Yang et al. (1998) estimated less than 10 Amur leopards in China; however, this estimate for the size of the Amur leopard population is derived from a snow track survey, conducted in China primarily for Amur tigers (Panthera tigris altaica). During recent years, while searching for snow tracks of Amur leopards, a large part of the Amur leopard range in China was also surveyed. There were 8–11 Amur leopards found during one survey on the southern slopes of Laoye Mountain in Jilin, China, taken during winter 2011 to spring 2012 ( Wu et al., 2013). An additional 5–7 leopards have been identified on the southern slopes of Laoyeling Mountain in Heilongjiang, China, during a winter survey in 2013 (http://www.tx2.org.cn/News/ShowArticle.asp?ArticleID=894). However, the snow track method may not estimate the number of individual leopards accurately.

All wildlife requires food and space for life activities (Morris, 2003). Habitat loss is a leading cause of population decline and extinction of endangered or threatened species (Halley and Iwasa, 2011). Food shortage is also a limiting factor of top predator populations, particularly large carnivores (Ullas Karanth and Chellam, 2009). Therefore, abundance, and the spatial distribution of prey population, may influence habitat selection and spatial distribution of predators (Aryal et al., 2014). Animals select habitat under the concomitant influences of habitat quality, resource availability, interspecific competition, and interspecific interaction (Fretwell and Calver, 1969, Rosenzweig, 1981 and Morris, 1988). Abundance and the associated spatial distribution of prey or food resources also play a crucial role in determining when and where predators forage (Santora et al., 2011 and Karanth et al., 2004). Consequently, carnivore density or abundance may be correlated with preferred prey densities and may, in turn, affect the relative abundance of prey (Trites, 2002, Karanth et al., 2004 and Hayward et al., 2007). Studies concerning the effects of prey abundance and spatial distribution on the use of space by carnivores provide insights into more effective ways to ensure the conservation of large carnivores (Karanth et al., 2004). Leopards usually live in remote areas, which are difficult to access, but they also occasionally visit the outskirts of urban areas adjacent to their ranges (Khorozyan and Abramov, 2007). Amur leopards prefer Korean pine forests at low elevations, well away from main roads, and avoid deciduous forests, meadows, shrubs, and agricultural fields (Hebblewhite et al., 2011). Little is known regarding the effects of both prey species and population abundance on the spatial distribution of the Amur leopard population in northeast China, in the regions bordering the Russian Far East.

PAGE 1- ARTICLE 1

PAGE 2 BELOW-ARTICLE 2

Journal of Environmental Management Volume 92, Issue 1, January 2011, Pages 31–42

Luan Xiaofenga, Qu Yia, Li Diqiangb, Liu Shirongb, Wang Xiuleib, Wu Bob, Zhu Chunquanc

The Amur Tiger (Panthera tigris altaica) is one of the world’s most endangered species. Recently, habitat fragmentation, food scarcity, and human hunting have drastically reduced the population size and distribution areas of Amur tigers in the wild, leaving them on the verge of extinction. Presently, they are only found in the north-eastern part of China. In this study, we developed a reference framework using methods and technologies of analytic hierarchy process (AHP), remote sensing (RS), geographic information system (GIS), GAP analysis, and Natural Break (Jenks) classification to evaluate the habitat and to set the conservation priorities for Amur tigers in eastern areas of Heilongjiang and Jilin Provinces of northeast China. We proposed a Habitat Suitability Index (HSI) incorporating 7 factors covering natural conditions and human disturbance. Based on the HSI values, the suitability was classified into five levels from the most to not suitable. Finally, according to the results of GAP analysis, we identified six conservation priorities and designed a conservation landscape incorporating four new nature reserves, enlarging two existing ones, and creating four linkages for Amur tigers in northeast China. The case study showed that the core habitats (the most suitable and highly suitable habitats) identified for Amur tigers covered 35,547 km2, accounting for approximately 26.71% of the total study area (1,33,093 km2). However, existing nature reserves protected only (7124 km2 or) 20.04% of the identified core habitats. Thus, the enlargement of current reserves is necessary and urgent for the tiger’s conservation and restoration. Moreover, the establishment of wildlife corridors linking core habitats will provide an efficient reserve network for tiger conservation to maintain the evolutionary potential of Amur tigers facing environmental changes.

Amur tiger (Panthera tigris altaica) is the largest of the five tiger subspecies. They are currently distributed mainly in the eastern mountainous areas of Heilongjiang and Jilin provinces, the Russian Far East, and North Korea ( Sun et al., 2005). The tiger was ranked as one of the top ten endangered species by the Wildlife Conservation Society in 1994 and was listed as the first-rank protected animal in China. In recent years, habitat degradation and fragmentation, damage to ecosystems, food scarcity, geographical isolation, and large scale human hunting have drastically reduced the habitat and number of Amur tigers in the wild, leaving them now on the verge of extinction with a population of only 360–450 individuals ( Zhang et al., 2005 and Zhou, 2008). They are now in danger of extinction and need immediate protection. Furthermore, being at the top level of the food chain, these animals directly or indirectly control the herbivorous primary consumers and play an extremely important role in the balance of the ecosystem (Li, 2004). This threatened species effectively function as an umbrella species for the remaining mammals (Graham et al., 2003). Recently, many countries have embarked on enlarging nature reserves and linking separate habitats to enhance the survival of tigers, such as the wildlife corridors connecting Heilongjiang province, Jilin province, and Russia. Effective protection and management of these eco-corridors are critical in safeguarding and recovering the population of Amur tigers (Sun, 2006). The traditional methods of tiger conservation have included roughly identifying the number of tigers, changes in distribution, and the relationship between food density and tiger activity patterns by selecting monitoring areas, establishing monitoring points, or monitoring transects (Sun et al., 2005). However, these methods are labor-intensive, expensive, and are inefficient. With the development of spatial and cyber technologies, remote sensing and geographic information systems provide powerful tools for environmental and habitat assessment on a landscape scale ( Store and Jokimäki, 2003, Krivtsov, 2004 and Wang et al., 2008). An important feature of remote sensing and geographic information systems is the ability to generate new information by integrating the existing diverse datasets sharing a compatible spatial referencing system (Goodchild, 1993). Recently, these technologies have been used for gathering information on physical parameters of wildlife habitats, geospatial modeling for wildlife habitat evaluation, and nature reserve design ( Huang et al., 1998 and Kushwaha and Roy, 2002). The use of these technologies provides for more effective data collection and analysis enhancing the protection of Amur tigers.

Previous landscape-level analyses of tiger distributions using modern technologies have identified parts of Northeast China as priority areas for tiger conservation (Sanderson et al., 2006). The current study takes a closer look at the already identified priority areas, examining factors that might influence their distribution at the local level, and identifying core habitats and linkages within the tiger conservation landscape.

An important aspect in species conservation is habitat protection, which is defined as the necessary living units for a given wild species, including space, food, water, etc. Habitat suitability models are useful habitat evaluation tools that have been extensively used by conservation planners to estimate the likelihood of occurrence and abundance of threatened wildlife species in terrestrial ecosystems (Carvalho and Gomes, 2003). Based on the extensive data collected, we developed a habitat suitability model incorporating vegetation types, food density, topography (elevation, slope, and aspect), and human disturbance (human population density and distance from roads) as effective factors to evaluate tiger habitat. Then we conducted a GAP analysis by comparing the results with the pattern of existing reserves, prioritized the conservation gaps for on-ground implementation, and finally put forward suggestions for conservation planning (Scott et al., 1993 and Prendergast et al., 1999).

Methodology

The methods and technologies used in the study were remote sensing (RS), geographic information system (GIS), analytic hierarchy process (AHP), and Natural Break (Jenks) classification. A Habitat Suitability model was developed using these methods and technologies to identify suitable sites and conservation priorities for Amur tigers in the study area. This paper aims to provide the scientific basis and references for effective habitat evaluation, priority setting, and conservation service delivery and policymaking. The experience, capabilities, and thinking of makers of policy, and those individuals who have liability for planning for the Amur tiger.

2. Study area

The study area is part of the eastern region of Heilongjiang and Jilin provinces. The total extent of this area is approximately 1,33,093 km2. It is located at latitude 41°58′51″N–47°34′54″N and longitude 126°19′25″E–134°20′57″E (Fig. 1). The main topographic features are high and steep mountain areas in the southwest, low mountain areas, and flat gradient regions in the northeast. Wanda Mountain and Laoyeling extend up to approximately 1000 m in elevation and are characterized as hilly with wide valleys, while Zhangguangcailing, Mudanling, Weihuling, Dalongling, and Changbai Mountain are taller mountains extending up to 2600 m in elevation with steep-sided narrow valleys.

<img class=”figure large” border=”0″ alt=”Location of study area.” src=”http://origin-ars.els-cdn.com.eztest.ocls.ca/content/image/1-s2.0-S0301479710002495-gr1.jpg” data-thumbEID=”1-s2.0-S0301479710002495-gr1.sml” data-imgEIDs=”1-s2.0-S0301479710002495-gr1.jpg” data-fullEID=”1-s2.0-S0301479710002495-gr1.jpg”>

Fig. 1.

Location of the study area.

caption

Figure options

The region is located in the temperate continental monsoon climatic zone which is affected by the eastern oceanic climate. It holds warm, humid forests, plentiful precipitation of 500–700 mm per year, and a frost-free period of 80–151 days. The mean annual temperature is highly seasonal, varying from −19.1 °C in January to 21.2 °C in July.

The Changbai Mountain floristic region includes coniferous forest, broad-leaved mixed forest, secondary forest, woodland shrub, and marshy grass areas, and contains more than 2500 plant species. The main forest types in the region are Koraiensis broad-leaved mixed forest, and secondary broad-leaved mixed forest, with such species as Korean pine (Pinus koraiensis Siebold et Zuccarini), Little-seed spruce (Picea jezoensis var. amanuensis), Xylosma (Quercus mongolica Fischer ex Ledebour), Asian white birch (Betula platyphylla Suk.), Black birch (Betula dahurica Pall.), Mono Maple (Acer mono Maxim.), Amur linden (Tilia amurensis Rupr.), Manchurian linden (Tilia mandschurica Rupr. ex Maxim.), Amur cork (Phellodendron amurense Rupr.), Manchurian walnut (Juglans mandshurica Maxim.), Manchurian ash (Fraxinus mandshurica Rupr.), and Catchy poplar (Populus ussuriensis Kom.) ( Sun et al., 1999 and Li et al., 2001).

3. Methods

Based on the results of the two latest large scale surveys carried out by an international team of Chinese, Russian and American experts in 1998 and 1999 (Sun et al., 1999 and Li et al., 2001), we identified the Amur tiger’s basic ecological preferences from data of tracks on survey points and line-transects. Vegetation types, prey density, topography (elevation, slope, and aspect), and human disturbance (human population density and distance from roads) were used as factors to evaluate the Amur tiger’s habitat and an HSI was generated to quantify the suitability of spatially heterogeneous habitats. After classifying the HSI, we identified the core habitats which are the most and highly suitable for tigers to live.

3.1. Factors influencing the habitat suitability

To develop an effective method of conservation planning, it is very important to identify species-specific habitat demands accurately and to define the important factors explaining species distribution (Heinanen and von Numers, 2009). In this paper, the selected factors are highly related to the environmental condition of habitats. It should be noted that these factors are salient ones for habitat suitability evaluation but they are not all-inclusive.

The reduction of prey density is the main driver affecting the Amur tiger population and distribution (Miquelle et al., 1996 and Zhou, 2008). Hunting activities and habitat degradation also cause the population reduction of this animal. In rural areas with dense human populations, the occurrence of tigers is reduced markedly. Human disturbance can be measured by human population density and distance from roads (Wang and Shen, 1996). Amur tigers also have a preference for some types of vegetation in good condition, such as temperate deciduous broad-leaved forest and mixed wood (Yudakov and Nikolaev, 1987, Zhang et al., 2005 and Sanderson et al., 2006). Furthermore, they like areas of a relatively gentle slope and low elevation covered with dense forest (Ma and Jin, 2003 and Yudakov and Nikolaev, 1987). A resource selection function model developed from tracked distribution data predicted that tigers were most likely to occur in lower elevation valley bottoms with Korean pine forest and low human impacts (Carroll and Miquelle, 2006).

Considering the importance and data availability of the factors mentioned above, vegetation types, food density, elevation, slope, aspect, human population density, and distance from roads were selected as variables to be used for the habitat suitability analysis. These factors are representative, operational, and indicative to the analysis and can provide the most information required in the evaluation.

In recent years, due to misuse of natural resources such as clearing and logging for agricultural expansion, the area of intact forest has decreased drastically, and habitats and corridors for wildlife have been fragmented to the extent that wild tigers cannot maintain or expand viable populations. Coupled with human population stress, industrial pollution, deforestation, and poaching, the number of Amur tigers has decreased so rapidly that it is urgent to build large conservation areas to protect their habitats. The long-term research on Amur tigers and their prey density showed that a female tiger feeding young tigers needs a home range of approximately 400 km2, and the male tiger home range maybe three to five times as large. To sustain a population with 20 reproductive female tigers, a favorable and continuous habitat of 8000 km2 will be required (Tian, 2009 and Li et al., 2010). The biggest success of Russia in tiger conservation is large scale protection. China has set aside eight conservation areas for tigers, but the largest one, the Hunchun nature reserve is only 1000 km2 in size, far from a comprehensive and effective conservation effort for Amur tigers (Tian, 2009). If the recommendations in this study were implemented by creating new and enlarging existing reserves, the total area of conservation areas would increase by about 27,284–42,184 km2 which could provide habitat for about 100 tigers. Reasonably protected area expansion in southern areas of China is the key to Amur tiger conservation.

5/5 - (10 votes)
Table of Contents