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The highly endangered giant panda (Ailuropoda melanoleuca) is the world's most widely recognised conservation icon. Population dynamics models can get on track to a healthy population for giant pandas, and assess its development over time. This paper proposes a new way to study population dynamics of giant pandas in captivity by means of membrane computing, a bio-inspired computational paradigm based on processing multisets of objects within a cell structure, following a series of evolution rules. This framework is used to model the intrinsically stochastic real-life evolution processes of giant pandas, based on pedigree data. This is the first attempt to collect and analyse so complete source, and to investigate population dynamics of giant pandas based on them. Pedigree data consisting of the number of giant panda individuals per age are provided by Chengdu Research Base of Giant Panda Breeding of China. A special simulator has been developed to assist in the design and formal verification of the mathematical model presented. Particularly, the model feasibility, effectiveness, soundness and robustness have been validated by the simulator, which also enables decision-making based on the simulation results of conducted virtual experiments. [ABSTRACT FROM AUTHOR]

Even though the giant panda's extinction status is downgraded from endangered to vulnerable, but the animals still face an uphill battle for survival. Moreover, the number of giant pandas is also rare. With the increase of captive individuals, wild release has become an inevitable task that human face. It is important to evaluate at least how much giant pandas are remained for being released to the wild. Several methods have been presented in the literature to assess minimum viable population (MVP) of giant pandas. However, each of these methods is designed only based on population sizes. In this paper, a membrane computing model based on behavioral biology is proposed to evaluate the MVP of the species. An application of the proposed data processing to binary tree whose nodes are composed of population sizes is also proposed. An binary tree is generated by integrating the following three techniques: (a) a random technique to generate the vast majority of populations; (b) a modified binary search method to obtain an order population size sequence; (c) a modified inorder traversal to generate an order binary tree and a parent tree. This is the first attempt to apply membrane computing model to assess the MVP of giant pandas. The effectiveness of the presented general PDP system is verified by means of the numbers or amounts of subpopulations. Besides, we also provide the population distribution of the obtained MVP. [ABSTRACT FROM AUTHOR]

Knowledge of energy expenditure informs conservation managers for long term plans for endangered species health and habitat suitability. We measured field metabolic rate (FMR) of free-roaming giant pandas in large enclosures in a nature reserve using the doubly labeled water method. Giant pandas in zoo like enclosures had a similar FMR (14,182 kJ/day) to giant pandas in larger field enclosures (13,280 kJ/day). In winter, giant pandas raised their metabolic rates when living at − 2.4 °C (36,108 kJ/day) indicating that they were below their thermal neutral zone. The lower critical temperature for thermoregulation was about 8.0 °C and the upper critical temperature was about 28 °C. Giant panda FMRs were somewhat lower than active metabolic rates of sloth bears, lower than FMRs of grizzly bears and polar bears and 69 and 81% of predicted values based on a regression of FMR versus body mass of mammals. That is probably due to their lower levels of activity since other bears actively forage for food over a larger home range and pandas often sit in a patch of bamboo and eat bamboo for hours at a time. The low metabolic rates of giant pandas in summer, their inability to acquire fat stores to hibernate in winter, and their ability to raise their metabolic rate to thermoregulate in winter are energetic adaptations related to eating a diet composed almost exclusively of bamboo. Differences in FMR of giant pandas between our study and previous studies (one similar and one lower) appear to be due to differences in activity of the giant pandas in those studies. [ABSTRACT FROM AUTHOR]

Giant pandas (Ailuropoda melanoleuca) were historically hunted using dogs and are currently threatened by free-roaming dogs and their associated diseases. To better understand the spatial magnitude of this threat, we used a GIS approach to investigate edge effects of dogs on giant panda habitat. We first examined two nature reserves with contrasting free-roaming dog populations: Liziping, with many dogs (~0.44/km2), and Daxiangling, with few dogs (~0.14/km2). Spatial analysis indicated that giant pandas at Liziping (but not Daxiangling) showed a shift in habitat use away from populated areas consistent with a risk response to the foray distance of free-roaming dogs (10.9 km path-distance). Most giant panda locations (86%) from the 2014 census in Liziping were clustered around remote "dog-free zones." Expanding this analysis across the entire giant panda range revealed that 40% of panda habitat is within the foray distance of dogs. Our assessment will inform dog control programs including monitoring, education, veterinary care, and other measures. We recommend that reserves designated for the release of translocated pandas receive priority consideration for dog control efforts. Only by understanding and managing complex interactions between humans, domestic animals, and wild animals can we sustain natural systems in a world increasingly dominated by humans. [ABSTRACT FROM AUTHOR]

The red-crowned crane is one of the rarest crane species, and its population is decreasing due to loss of habitat, poisoning, and infections. Using a viral metagenomics approach, we analyzed the virome of feces from wild and captive red-crowned cranes, which were pooled separately. Vertebrate viruses belonging to the families Picornaviridae, Parvoviridae, Circoviridae, and Caliciviridae were detected. Among the members of the family Picornaviridae, we found three that appear to represent new genera. Six nearly complete genomes from members of the family Parvoviridae were also obtained, including four new members of the proposed genus "Chapparvovirus", and two members of the genus Aveparvovirus. Six small circular DNA genomes were also characterized. One nearly complete genome showing a low level of sequence identity to caliciviruses was also characterized. Numerous viruses believed to infect insects, plants, and crustaceans were also identified, which were probably derived from the diet of red-crowned cranes. This study increases our understanding of the enteric virome of red-crowned cranes and provides a baseline for comparison to those of other birds or following disease outbreaks. [ABSTRACT FROM AUTHOR]

Understanding the spatial genetic structure of populations can provide insight into the ecological or evolutionary processes of the species, and enable wise conservation decisions. We examined the spatial genetic structure of a giant panda ( Ailuropoda melanoleuca) population in a heterogeneous mountainous landscape using noninvasive genetic sampling and 12 microsatellite loci. Nonrandom genetic structure was detected through spatial autocorrelation analysis, demonstrating a significantly positive autocorrelation over closer distances. Additional spatial analyses showed significantly positive genetic correlation among spatially-proximate males, and no correlation among females and among male-female pairs. These findings suggest a female-biased dispersal pattern and cryptic family grouping among giant pandas on a large mountain-range scale. The spatial extent of genetic structure occurred within 12.5 km, measured by a least-cost path distance model integrating information of habitat quality and habitat preferences of this species. Using the bearing analysis of PASSAGE, we found that directional genetic autocorrelations were in agreement with habitat structure, and habitat heterogeneity may affect the direction of giant panda dispersal. The characterization of spatial genetic structure can provide potentially valuable information for the conservation and management of giant pandas and their habitat. [ABSTRACT FROM AUTHOR]

nthropogenic habitat loss and fragmentation have been implicated in the endangerment and extinction of many species. Here we assess genetic variation and demographic history in the southernmost population of giant pandas ( Ailuropoda melanoleuca) that continues to be threatened by habitat degradation and fragmentation, using noninvasive genetic sampling, mitochondrial control region sequence and 12 microsatellite loci. Compared to other giant panda populations, this population has medium-level genetic diversity based on the measure of both mitochondrial and nuclear markers. Mitochondrial DNA-based demographic analyses revealed that no historical population expansion or contraction has occurred, indicating a relatively stable population size. However, a Bayesian-coalescent method based on the observed allele distribution and allele frequencies of microsatellite clearly did detect, quantify and date a recent decrease in population size. Overall, the results indicate that a population contraction in the order of 95-96% has taken place over the last 910-999 years and is most likely due to anthropogenic habitat loss. These findings highlight the need for a greater focus on habitat protection and restoration for the long-term survival of this giant panda population. [ABSTRACT FROM AUTHOR]

Few studies have focused on the mountain ranges scale effects of roads on wildlife. This lack of data could lead to an underestimation of the negative impact of roads on animal populations. We analyzed a dataset that included 74.4% of the giant panda population and covered 78.7% of the global giant panda habitat to estimate road-effect zones for major roads, and to investigate how these major roads influenced the distribution of giant pandas on a mountain range spatial scale. We found that the density of giant panda signs was significantly decreased by proximity to major roads. The effect zone reached 5,000 m from national roads and 1,500 m from provincial roads. Structural equation model analysis revealed that the strongest negative impact of major roads on giant pandas was via the reduction of nearby forest cover. The results should provide a better understanding of the impact of anthropogenic infrastructure and regional economic development on wildlife, thus providing a basis for conservation policy decisions. We suggest that the environmental impact assessment of proposed roadways or further researches on road ecological effects should expand to a larger scale and consider the possible habitat degradation caused by road access. [ABSTRACT FROM AUTHOR]

Habitat fragmentation can reduce population viability, especially for area-sensitive species. The Minimum Area Requirements (MAR) of a population is the area required for the population's long-term persistence. In this study, the response of occupancy probability of giant pandas against habitat patch size was studied in five of the six mountain ranges inhabited by giant panda, which cover over 78% of the global distribution of giant panda habitat. The probability of giant panda occurrence was positively associated with habitat patch area, and the observed increase in occupancy probability with patch size was higher than that due to passive sampling alone. These results suggest that the giant panda is an area-sensitive species. The MAR for giant panda was estimated to be 114.7 km2 based on analysis of its occupancy probability. Giant panda habitats appear more fragmented in the three southern mountain ranges, while they are large and more continuous in the other two. Establishing corridors among habitat patches can mitigate habitat fragmentation, but expanding habitat patch sizes is necessary in mountain ranges where fragmentation is most intensive. [ABSTRACT FROM AUTHOR]