Giant Panda Population Research Articles

Captivity increased the abundance of high-risk antibiotic resistance genes in the giant panda gut microbiome

Captivity is a key strategy for protecting endangered species, but research has primarily focused on artificial breeding and reintroduction to bolster wild populations, often overlooking the environmental and health risks associated with antibiotic resistance genes (ARGs). Here, we conducted a comprehensive analysis of the microbiome and ARG profiles in the gut of wild giant pandas across five representative populations, as well as one captive population, utilizing 16S rRNA gene sequencing and High-Throughput Quantitative PCR. Our findings revealed that both geographic location and captivity significantly influenced the gut microbial community and ARG composition in the gut of giant pandas. Additionally, we identified core microbiomes with essential ecological functions, particularly those related to food utilization, were identified in the giant panda gut across different regions. The gut ARGs in giant pandas exhibited a broad range of subtypes, with multidrug resistance genes being the most prevalent. Notably, the captive population harbored the highest abundance of high-risk ARGs, especially those conferring tetracycline resistance. High-risk multidrug ARGs (e.g., tolC, mepA, and mdtA) were found to be strongly correlated with the potential pathogens, such as Escherichia_Shigellina and Pseudomonas. Furthermore, bamboo-associated ARGs and mobile genetic elements (MGEs) contributed significantly to the ARG abundance in the giant panda gut, indicating that diet plays a crucial role in shaping gut resistome. Collectively, our study provides a detailed mapping of giant panda gut microbiomes and ARG distribution, offering valuable insights for conservation efforts and advancing our understanding of ARG dynamics in giant panda populations.

Habitat status and feasibility of constructing corridors for a vulnerable population of giant pandas

Habitat corridors provide connectivity to decrease the negative effects of fragmentation. However, numerous current studies on habitat corridors remain in the design stage, and there is a lack of research addressing the challenges and feasibility of actual construction. Therefore, fine-scale analyses of habitat corridors are needed to provide deeper insights. We proposed a fine-scale habitat corridor design using the giant panda (Ailuropoda melanoleuca) population in the Mabian Dafengding National Nature Reserve as a case study. The research combined field quadrats, camera traps, and remote sensing data to complete analyses using the species distribution model, landscape pattern index, circuit theory model, and least-cost path (LCP) model. The results show that 53 km2 of suitable habitat for giant pandas exists in the reserve, and anthropogenic disturbance and bamboo cover were key environmental factors affecting giant pandas’ habitat suitability. Fragmentation has caused suitable habitat isolation, and the core habitat is non-contiguously scattered between the north and south. In the design of ten habitat corridors, two primary corridors connect the core habitat from north to south. The proposed primary corridors, roughly 1.4 km wide, are limited by natural impediments such as rivers, food resources, and anthropogenic disturbance. Our research used the latest methods and data to design the habitat corridor and reveals many difficulties for actual construction, despite employing approaches such as the LCP. Our findings enhance the understanding of habitat corridor feasibility and support the development of giant panda conservation efforts.

Quantifying the potential health risk of surface waters in the Qinling giant panda habitat

The giant panda (Ailuropoda melanoleuca) is recognized worldwide as an icon for wildlife conservation. The Qinling subspecies (Ailuropoda melanoleuca qinlingensis) inhabiting the Qinling Mountains is more endangered. Previous studies have indicated that Qinling pandas are potentially at risk from environmental pollutants, which they are exposed to via food and drinking water. However, there is little information about the surface water quality in the Qinling Mountains, and it is unknown whether drinking water is an important pollutant source for pandas. Water samples were collected from five different nature reserves in Qinling, each of which is home to a population of pandas. The samples were analyzed for five essential metals of copper (Cu), zinc (Zn), manganese (Mn), chromium (Cr), and nickel (Ni) and four non-essential metals of lead (Pb), cadmium (Cd), arsenic (As), and mercury (Hg). The concentrations of all heavy metals (HMs) were higher in buffer zones than in the core areas and were highest in Foping and Niuweihe nature reserves. The concentrations of mercury exceeded the water quality standard in the core zone of three reserves, suggesting that NWH (Niuweihe), THS (Tianhuashan), and PHL (Pingheliang) giant panda populations were at risk from mercury toxicity. The accumulation of other elements over time could also pose a serious risk to pandas. Three main sources of pollution were identified: coal combustion, waste incineration, and fertilizer use; traffic-related activities; and metal mining. Environmental pollution is compromising the efforts to conserve the giant panda, and measures need to be put in place to control pollution sources.

Large-scale genome sequencing of giant pandas improves the understanding of population structure and future conservation initiatives

The extinction risk of the giant panda has been demoted from "endangered" to "vulnerable" on the International Union for Conservation of Nature Red List, but its habitat is more fragmented than ever before, resulting in 33 isolated giant panda populations according to the fourth national survey released by the Chinese government. Further comprehensive investigations of the genetic background and in-depth assessments of the conservation status of wild populations are still necessary and urgently needed. Here, we sequenced the genomes of 612 giant pandas with an average depth of ~26× and generated a high-resolution map of genomic variation with more than 20 million variants covering wild individuals from six mountain ranges and captive representatives in China. We identified distinct genetic clusters within the Minshan population by performing a fine-grained genetic structure. The estimation of inbreeding and genetic load associated with historical population dynamics suggested that future conservation efforts should pay special attention to the Qinling and Liangshan populations. Releasing captive individuals with a genetic background similar to the recipient population appears to be an advantageous genetic rescue strategy for recovering the wild giant panda populations, as this approach introduces fewer deleterious mutations into the wild population than mating with differentiated lineages. These findings emphasize the superiority of large-scale population genomics to provide precise guidelines for future conservation of the giant panda.

Enhancing the Viability of a Small Giant Panda Population Through Individual Introduction From a Larger Conspecific Group: A Scientific Simulation Study.

Currently, nearly 70% of giant panda populations are facing survival challenges. The introduction of wild individuals can bring vitality to them. To explore this possibility, we hypothetically introduced giant pandas from Tangjiahe and Wanglang into Liziping and Daxiangling Nature Reserves. We collected feces from these areas and analyzed the genetic diversity and population viability before and after introduction using nine microsatellite loci. The results showed the genetic level and viability of the large populations were better than the small populations. We investigated the effects of time intervals (2a, 5a, and 10a; year: a) and gender combinations (female: F; male: M) on the rejuvenation of small populations. Finally, five introduction plans (1F/2a, 2F/5a, 1F1M/5a, 3F/10a, and 2F1M/10a) were obtained to make Liziping meet the long-term survival standard after 100 years, and six plans (1F/2a, 2F/5a, 1F1M/5a, 4F/10a, 3F1M/10a, and 2F2M/10a) were obtained in Daxiangling. The more females were introduced, the greater the impact on the large populations. After introducing individuals, the number of alleles and expected heterozygosity of the Liziping population are at least 6.667 and 0.688, and for the Daxiangling population, they are 7.111 and 0.734, respectively. Our study provides theoretical support for the translocation of giant pandas, a reference for the restoration of other endangered species worldwide.

Habitat connectivity drives panda recovery

Globally, the majority of habitat loss is irreversible, and most species will never recover their former ranges. We have learned a great deal about what leads to population decline and extinction, but less about recovery. The recently downlisted giant panda provides a unique opportunity to understand the mechanisms of species recovery. In our study, we estimate giant panda suitable habitats, population density, and gene flow across landscapes to fully investigate the direct and indirect ecological mechanisms underlying bold conservation strategies. We found that the Giant Panda National Survey has modestly but systematically underestimated population size. China's effort to mitigate anthropogenic disturbances was associated with increased panda population density through improving habitat quality and reducing habitat fragmentation. Enhanced landscape connectivity reduced inbreeding via gene flow but indirectly increased inbreeding temporarily due to high local panda density. Although the panda's recovery has been geographically uneven, we provide evidence for improving connectivity and gene flow resulting from conservation efforts. If these processes can be sustained and improved, the panda's path to recovery will be less encumbered by loss of genetic diversity, fostering hope that the present rate of recovery will not be stalled. Findings from this study will not only help guide future giant panda conservation management but also provide a model for how a more mechanistic examination of the genetic processes underlying species recovery can foster the development of more effective strategies for endangered species recovery.

Facilitating giant panda crossings of national highway in Wolong area of Giant Panda National Park amid human activities.

As human activities continue to expand, wildlife persistence faces escalating threats from roads. In Wolong area of Giant Panda National Park, the local giant pandas (Ailuropoda melanoleuca) are divided into two population groups along the National Highway G350 (NHG). Therefore, selecting suitable areas to help those giant pandas communicate across the NHG is necessary. In this research, we evaluated the presence of human activities and simulated their absence to analyze how they affect the giant panda's habitat in Wolong. Subsequently, based on the kernel density estimation (KDE) for giant pandas and the main human distribution locations, we selected suitable areas for the population link between the two road sections on the NHG. We simulated the absence of human activities on the two road sections to compare changes in the habitat suitability index (HSI) and connectivity value (CV) relative to their presence. We aimed to carefully select the area for future giant panda corridor plans and simulate whether eliminating human activities will significantly improve the HSI and CV of the area. Our results show that: (1) Human activities presence has led to subtle changes in the landscape pattern of suitable habitats and a decrease in Wolong by 78.76 km2 compared to their absence. (2) Human activities presence significantly reduced HSI and CV in the 1000 m buffer along the NHG compared to their absence. (3) The HSI and CV of the 1000 m buffer in the simulated absence of human activities for the two road sections were significantly higher than their presence. This research identified the optimal road section for crossing the NHG to link giant panda population groups and habitats in Wolong. These insights are significant for formulating conservation decisions and corridor plans and for promoting wildlife conservation in reserves amid high levels of human activity.

Suitable habitat evaluation and ecological security pattern optimization for the ecological restoration of Giant Panda habitat based on nonstationary factors and MCR model

Enhancing the regional connectivity, coordination, and integrity of Giant Panda National Park can protect giant pandas. The construction and optimization of the ecological security pattern in giant panda habitat can effectively promote the information exchange among giant panda populations of Giant Panda National Park in Ya'an area. Based on climate change, geographic location, human activities, and other factors, the Maxent model was used to evaluate the non-stability of giant panda habitat suitability, and the minimum cumulative resistance (MCR) model was used to construct the ecological security pattern. Based on the gravity model and relevant image verification analysis, we proposed an optimal solution to the ecological problem of giant panda corridor groups. From our research, good habitat suitability of giant pandas was detected, with a high degree of local fragmentation. The areas of the most suitable habitat, the more suitable habitat, and the generally suitability were 1970.12 km2, 2346.51 km2, and 1902.37 km2, respectively. Suitable habitat was located between 2100 m and 3400 m in elevation, with a less than 30° slope. The average temperature of the coldest season in the suitable area was around - 2 ∼ 2 °C, the precipitation of the wettest month was between 140 ∼ 160 mm, and the mean diurnal range was between 9 ∼ 14 °C. Valuation results for nonstationary factors beyond these ranges will not fall within the Habitat Suitability Zone. In total, 13 ecological sources, 13 ecological corridors, 6 ecological barrier points, and 4 ecological pinch points were identified and divided into 4 ecological corridor groups to locate and repair ecological problems, achieving the purpose of building and optimizing ecological security patterns. The integrated technical frame work proposed in this work, which combined the suitability evaluation, ecological safety pattern construction and ecological restoration, considered the nonstationary variations in factors and the actual species ranges. It also emphasized the importance of the relationship between the species’ suitability and the ecological security pattern. The results of this work have important implications for examining the habitat modifications, gene exchange between giant panda populations, and habitat conservation of giant pandas.

Species identification and spatial diversity patterns of the Giant Panda National Park (GPNP) in Ya’an, Sichuan, China

National parks play a crucial role in global biodiversity preservation, with China’s Giant Panda National Park (GPNP) serving as a key stronghold for protecting unique flora and fauna endemic to diverse mountainous regions. This study focused on unraveling the dynamics of diversity within local giant panda populations and their sympatric species in the Ya’an section of the GPNP. Five specific local population patches (LPPs) were selected as subjects, utilizing data from the 4th National Giant Panda Survey. Through identification, classification, and analysis of observed species within each LPP, α and β diversity patterns were revealed, leading to actionable recommendations. A comprehensive record of 34 species spanning 5 orders and 16 families was documented. Notably, 8 species were under the first-class of the National Key Protected Wildlife List in China, and the IUCN Red List has identified 3 species – Rhinopithecus roxellana, Moschus berezovskii, and Ailurus styani – as endangered, showing its high biodiversity and conservation significance. While α-diversity assessment highlighted the DaxianglingA2 (DXLA2) with the highest Shannon-Wiener and Simpson’s indices, the QionglaishanA3 (QLSA3) exhibited greater species richness. However, these differences lacked statistical significance (P > 0.05). The Jaccard similarity coefficient indicated a stronger turnover process compared to nestedness. The dominance of turnover in total β-diversity accentuated the importance of encompassing all five LPPs in conservation strategies. The study underscored the imperative of conservation management for each LPP, with a focus on enhancing habitat connectivity between disparate small LPPs to prevent species extinction by fostering species exchange and gene flow. This pioneering research shed light on spatial utilization patterns and diversity drivers for local giant panda populations and their sympatric species within the GPNP. It provides valuable references to appraise conservation strategy effectiveness and offers scientific backing to optimize biodiversity conservation and management within national parks and protected areas.

The Potential of Co-Evolution and Interactions of Gut Bacteria-Phages in Bamboo-Eating Pandas: Insights from Dietary Preference-Based Metagenomic Analysis.

Bacteria and phages are two of the most abundant biological entities in the gut microbiome, and diet and host phylogeny are two of the most critical factors influencing the gut microbiome. A stable gut bacterial community plays a pivotal role in the host's physiological development and immune health. A phage is a virus that directly infects bacteria, and phages' close associations and interactions with bacteria are essential for maintaining the stability of the gut bacterial community and the entire microbial ecosystem. Here, we utilized 99 published metagenomic datasets from 38 mammalian species to investigate the relationship (diversity and composition) and potential interactions between gut bacterial and phage communities and the impact of diet and phylogeny on these communities. Our results highlight the co-evolutionary potential of bacterial-phage interactions within the mammalian gut. We observed a higher alpha diversity in gut bacteria than in phages and identified positive correlations between bacterial and phage compositions. Furthermore, our study revealed the significant influence of diet and phylogeny on mammalian gut bacterial and phage communities. We discovered that the impact of dietary factors on these communities was more pronounced than that of phylogenetic factors at the order level. In contrast, phylogenetic characteristics had a more substantial influence at the family level. The similar omnivorous dietary preference and closer phylogenetic relationship (family Ursidae) may contribute to the similarity of gut bacterial and phage communities between captive giant panda populations (GPCD and GPYA) and omnivorous animals (OC; including Sun bear, brown bear, and Asian black bear). This study employed co-occurrence microbial network analysis to reveal the potential interaction patterns between bacteria and phages. Compared to other mammalian groups (carnivores, herbivores, and omnivores), the gut bacterial and phage communities of bamboo-eating species (giant pandas and red pandas) exhibited a higher level of interaction. Additionally, keystone species and modular analysis showed the potential role of phages in driving and maintaining the interaction patterns between bacteria and phages in captive giant pandas. In sum, gaining a comprehensive understanding of the interaction between the gut microbiota and phages in mammals is of great significance, which is of great value in promoting healthy and sustainable mammals and may provide valuable insights into the conservation of wildlife populations, especially endangered animal species.

Antimicrobial resistance, serogroups, virulence gene profiles and MLST of Escherichia coli from giant panda.

Escherichia coli is a major bacterial pathogen which causes diarrhea in the giant panda. This study investigated the biological characteristics of 100 E. coli strains isolated from fecal samples collected from 100 captive giant pandas of different age groups and sexes. A standard Kirby-Bauer disk diffusion antimicrobial susceptibility test was performed with the isolates and we then further evaluated the antibiotic resistance genes (ARGs) by high-throughput quantitative PCR. Additionally, we then analyzed O serogroups through a slide agglutination test, virulence genes and the multi-locus sequence typing (MLST) by PCR. Antimicrobial susceptibility testing demonstrated that the 100 E. coli strains were mainly resistant to ENR (68%), AM (56%), IPM (55%), AMX (54%) and CA (52%), but were susceptible to MEM and FOX. The resistance to TZP, AK, FEP, CAZ, AMS, AZM, AT and IPM was significantly related to age (p < 0.05); the resistance rate of E. coli isolated from female giant pandas to N was significantly higher than in males (p < 0.05). Forty-five different types of ARGs were found, which included a total of 2,258 ARGs, in the 100 E. coli isolates. The top 10 of detection rate of ARGs were: acrA-04, acrA-05, aacC, blaCTX-M-04, ampC-04, blaSHV-01, blaTEM, sul2, blaOXY, tetA-02. ARGs aac (6')I1, blaCTX-M-03, tetD-02, blaSHV-02 and blaOXY were significantly related to age (p < 0.05), blaSHV-02, blaNDM and ampC-04 were related to sex (p < 0.05). Twelve different O serogroups from 32 E. coli isolates were distinguished, including O4, O8, O9, O15, O18, O20, O55, O88, O112, O157, O158, and O167. The most prevalent O serotype was O20, but O28, O45, O101, O149, and O152 were not detected. Fourteen different types of virulence genes were detected in the 100 E. coli isolates, of which papA (99%) were highly detected, while hlyA, elt and estA were not detected. MLST showed that 41 STs, which had one CCs and six groups with SLVs, in the 100 E. coli strains were identified, the main type was ST37. Our results advocate the need of strict biosecurity and surveillance programs in order to prevent the spread of pathogenic bacteria in the captive giant panda population.

A Survey of the Wild Giant Panda Population and Habitat Reflects an Urgent In Situ Conservation Need: A Case of Meigu Dafengding National Nature Reserve

An important tool for conserving species and their habitats and achieving sustainable development is the establishment of national parks. The population ecology of the species to be conserved, including their population size and suitable habitat, needs to be assessed prior to integrating protected areas into national parks. The Liangshan Mountains are currently the southernmost habitat of giant pandas and lie outside the newly established Giant Panda National Park (GPNP). The population is threatened with extinction due to severe isolation and human disturbance. However, there has been a ten-year gap in the census of giant pandas in this critical area. This means that conservation managers are unable to keep up to date with population and habitat dynamics. The Meigu Dafengding National Nature Reserve is the core area of the giant panda population in Liangshan and the link for gene exchange. The focus of this study is to assess the spatial distribution pattern of suitable habitat, habitat fragmentation and the habitat selection characteristics of giant pandas in the Meigu Dafengding Nature Reserve in Liangshan in order to lay the foundation for the future inclusion of Liangshan into the national park. A total of 151 giant panda fecal samples were collected in 2023. Using the distance–bamboo stem fragments method, this indicated that nearly 28 to 29 giant pandas exist within the reserve. Based on MaxEnt and FRAGSTATS, the giant panda population is concentrated in Wahei–Yiziyakou. They tend to choose gentle slopes of 10–30°, at altitudes between 2500 m and 3500 m, with average annual temperatures between 8.5 °C and 10 °C. They also select the areas close to roads and settlements for their frequent activities. Unsuitable habitat is widespread and surrounds low-, medium- and high-suitability habitats with poor habitat connectivity. In situ conservation measures are urgently needed due to the restricted distribution of populations and poor habitat suitability. This lays the foundation for the future inclusion of Liangshan into the national park, providing greater protection for the giant panda and other species in the region, and for other national parks to integrate all habitats into a single management unit. This will address conservation gaps and overlapping management, and promote the conservation of rare or endangered species.

Effects of Age and Season on Blood Parameters of Captive Giant Pandas: A Pilot Study.

The giant panda, Ailuropoda melanoleuca, serves as a flagship species for biodiversity conservation, embodying the intersection of ecological, evolutionary, and anthropogenic forces shaping the natural world. Hematological parameters serve as crucial indicators for assessing the physiological status of animals. However, our understanding of blood parameters and hemorheology in captive giant pandas under non-anesthetic conditions is limited. In this study, from September 2018 to August 2020, we collected blood samples from captive giant pandas under non-anesthetic conditions. Twelve captive giant pandas, ranging in age from 2 to 28 years, were divided into three groups based on their age, and the variations in basic blood parameters and hemorheological parameters across four seasons were analyzed. This provided baseline data for future blood sample comparisons in non-anesthetized captive giant pandas. Additionally, we observed seasonal changes in hematological morphology, hemorheology, and serum enzymes. Moreover, seasonality had a regulatory effect on hemorheological parameters and negatively impacted blood viscosity. Age influenced changes in serum enzymes, serum protein content, and serum metabolites, indicating differences in overall metabolic processes among giant pandas of different age groups. Whether factors such as season and climate contribute to environmental stress in captive giant pandas requires further investigation. The findings of this study may help to protect the stability of the giant panda population better and provide a reference for the medical care of captive giant pandas.

The distribution variation of pathogens and virulence factors in different geographical populations of giant pandas.

Intestinal diseases caused by opportunistic pathogens seriously threaten the health and survival of giant pandas. However, our understanding of gut pathogens in different populations of giant pandas, especially in the wild populations, is still limited. Here, we conducted a study based on 52 giant panda metagenomes to investigate the composition and distribution of gut pathogens and virulence factors (VFs) in five geographic populations (captive: GPCD and GPYA; wild: GPQIN, GPQIO, and GPXXL). The results of the beta-diversity analyzes revealed a close relationship and high similarity in pathogen and VF compositions within the two captive groups. Among all groups, Proteobacteria, Firmicutes, and Bacteroidetes emerged as the top three abundant phyla. By using the linear discriminant analysis effect size method, we identified pathogenic bacteria unique to different populations, such as Klebsiella in GPCD, Salmonella in GPYA, Hafnia in GPQIO, Pedobacter in GPXXL, and Lactococcus in GPQIN. In addition, we identified 12 VFs that play a role in the intestinal diseases of giant pandas, including flagella, CsrA, enterobactin, type IV pili, alginate, AcrAB, capsule, T6SS, urease, type 1 fimbriae, polar flagella, allantoin utilization, and ClpP. These VFs influence pathogen motility, adhesion, iron uptake, acid resistance, and protein regulation, thereby contributing to pathogen infection and pathogenicity. Notably, we also found a difference in virulence of Pseudomonas aeruginosa between GPQIN and non-GPQIN wild populations, in which the relative abundance of VFs (0.42%) of P. aeruginosa was the lowest in GPQIN and the highest in non-GPQIN wild populations (GPXXL: 23.55% and GPQIO: 10.47%). In addition to enhancing our understanding of gut pathogens and VFs in different geographic populations of giant pandas, the results of this study provide a specific theoretical basis and data support for the development of effective conservation measures for giant pandas.

Species coexistence and niche interaction between sympatric giant panda and Chinese red panda: A spatiotemporal approach.

The giant panda (Ailuropoda melanoleuca) and the Chinese red panda (Ailurus styani) are distributed in the same region in the mountain forest ecosystem on the eastern edge of the Qinghai Tibet Plateau and share the same food sources. In order to understand how sympatric giant pandas and Chinese red pandas maintain interspecific relationships to achieve stable coexistence, we used species distribution models and diurnal activity rhythms to analyze the spatial and temporal niche characteristics of giant pandas and Chinese red pandas in the Daxiangling Mountain system based on 187 camera traps data. The results show that: (1) In the Daxiangling Mountains, the total area of suitable habitats for giant pandas and Chinese red pandas is 717.61 km2 and 730.00 km2, respectively, accounting for 17.78% and 18.25%, respectively, of the study area. (2) The top five environmental factors contributing to the model of giant panda and Chinese red panda are precipitation seasonality, temperature seasonality, distance to the road, and elevation and vegetation type. (3) The total overlapping area of suitable habitats for giant pandas and Chinese red pandas is 342.23 km2, of which the overlapping area of highly suitable habitats is 98.91 km2. The overlapping index of suitable habitats is 0.472, and the overlapping index of highly suitable habitats is 0.348, which indicates that the two achieve spatial niches are separated to achieve stable coexistence. (4) The overlapping index of the daily activity rhythm of giant panda and Chinese red panda is 0.87, which is significantly different (p < .05). The existence of Chinese red panda will significantly affect the daily activity rhythm of giant panda (p < .001). This research can provide scientific reference for the researches about population and habitat protection of giant pandas and Chinese red pandas, so as to understand the driving mechanism of resource allocation and population dynamics of sympatric species.

Feeding habits and foraging patch selection strategy of the giant panda in the Meigu Dafengding National Nature Reserve, Sichuan Province, China.

Despite retaining a digestive system with carnivorous characteristics, the giant panda has now specialized to eat bamboo. Therefore, research on its feeding habits and foraging strategies has always been an important field in the study of giant panda population ecology. Located in the core distribution area of the giant panda population in the Liangshan mountains, the Meigu Dafengding Nature Reserve acts as the link between the major panda reserves in the Liangshan mountains and the key corridor zone connecting the giant panda populations in the east and west. This study was performed in 2017 and aimed to determine the feeding habits of giant pandas in this region, the heterogeneity of food resources in different seasons, and the selection strategy for foraging patches. To achieve this, we used the line transect method to investigate the giant panda population, collected fresh feces, analyzed the nutritional composition of bamboo samples, and set up a sampling grid of foraging patches in different seasonal distribution areas. It was found that wild giant pandas in the region spend most of the year at lower elevations(1939-3296m) foraging for Yushania maculata and Yushania ailuropodina, and only move to higher elevations(2844-3770m) in summer for Bashania fangiana. Their preferred foraging patches(n = 65) had certain topographical features, such as gentle slopes(< 25°) and closer proximity to water sources(< 500m), and the nutritional quality of bamboo resources in foraging patches was significantly better than in those they avoided or rarely used. The food habits and foraging patch selection strategies of giant pandas in the Liangshan and Qinling mountains are relatively similar, and the results of this study can help provide a scientific basis for the conservation and management of wild giant panda habitats in different mountain regions.

Large-scale genetic surveys for main extant population of wild giant panda (Ailuropoda melanoleuca) reveals an urgent need of human management.

There are only six isolated living giant panda populations, and a comprehensive understanding of their genetic health status is crucial for the conservation of this vulnerable species. Liangshan Mountains is one of the main distribution areas of living giant pandas and is outside the newly established Giant panda national park. In this study, 971 giant panda fecal samples were collected in the heartland of Liangshan Mountains (Mabian Dafengding Nature Reserve: MB; Meigu Dafengding Nature Reserve: MG; and Heizhugou Nature Reserve: HZG). Microsatellite markers and mitochondrial D-loop sequences were used to estimate population size and genetic diversity. We identified 92 individuals (MB: 27, MG: 22, HZG: 43) from the three reserves. Our results showed that: (1) genetic diversity of three giant panda populations was moderate; (2) several loci deviated significantly from the Hardy-Weinberg equilibrium and almost all these deviated loci showed significant heterozygote deficiencies and inbreeding; (3) three giant panda populations have substantial genetic differentiation with the most differentiation between MB and the two other populations; and (4) a large amount of giant panda feces outside the three reserves were found, implying the existence of protection gap. These results indicated that under stochastic events, the giant panda populations in Liangshan Mountains are at risk of genetic decline or extinction and urgent need of human management. This study revealed that high attention should be paid to the protection of these giant panda populations outside the Giant panda national park, to ensure their survival in their distribution areas.

The putative maintaining mechanism of gut bacterial ecosystem in giant pandas and its potential application in conservation.

Animals living in captivity and the wild show differences in the internal structure of their gut microbiomes. Here, we performed a meta-analysis of the microbial data of about 494 fecal samples obtained from giant pandas (captive and wild giant pandas). Our results show that the modular structures and topological features of the captive giant panda gut microbiome differ from those of the wild populations. The co-occurrence network of wild giant pandas also contained more nodes and edges, indicating a higher complexity and stability compared to that of captive giant pandas. Keystone species analysis revealed the differences between geographically different wild populations, indicating the potential effect of geography on the internal modular structure. When combining all the giant panda samples for module analysis, we found that the abundant taxa (e.g., belonged to Flavobacterium, Herbaspirillum, and Escherichia-Shigella) usually acted as module hubs to stabilize the modular structure, while the rare taxa usually acted as connectors of different modules. We conclude that abundant and rare taxa play different roles in the gut bacterial ecosystem. The conservation of some key bacterial species is essential for promoting the development of the gut microbiome in pandas. The living environment of the giant pandas can influence the internal structure, topological features, and strength of interrelationships in the gut microbiome. This study provides new insights into the conservation and management of giant panda populations.

Dynamic threats of nighttime light-represented human activities to giant pandas and their habitat

Human activities are one of the main factors threatening the long-term survival of wild giant pandas. Long-term and large-scale human activities can be quickly assessed by night light remote sensing data, which has been more and more widely used. In this paper, we analyzed the spatial patterns of nighttime light intensity and their dynamic changes from 2000 to 2020 in the entire giant panda distribution area using long-term nighttime light remote sensing data, and evaluated the dynamic threats of nighttime light-represented human activities to giant panda populations by proximity of light source and its intensity. We also assessed the relationships between the nighttime light dynamics and the trends of habitat fragmentation. Results showed that the intensity and range of the nighttime light around panda habitat had increased significantly from 2000 to 2020. The nighttime light intensity inside the natural reserves is significantly lower than outside, and it becomes more obvious over time. The intensity and range of nighttime light inside the natural reserves first increased and then decreased during the two decades, indicating that the protection inside the natural reserves effectively reversed the rapid increase in human activities in the previous decade. From 2000 to 2020, nighttime light sources became closer to local panda populations. In particular, they approached the pandas in the first decade, and stayed away in the second decade. This is mainly reflected in the weakened threats of nighttime light-represented human activities on the core large populations of the Qinling, Minshan and Qionglai Mountains from 2010 to 2020, but the threats on the peripheral populations continued to strengthen, where nighttime light became not only closer but also more intensified. The increase in nighttime light intensity and range were also significantly positively correlated with the increase in habitat fragmentation, especially during 2000–2010. Our study reveals the dynamic changes of nighttime light-represented human activities’ threats to wild giant panda and its habitat, gives advices for effectively protecting giant pandas and their habitats from human activities, and has implications for the assessment of human activities’ threats to other species in the world.

Giant panda age recognition based on a facial image deep learning system.

The conservation of the giant panda (Ailuropoda melanoleuca), as an iconic vulnerable species, has received great attention in the past few decades. As an important part of the giant panda population survey, the age distribution of giant pandas can not only provide useful instruction but also verify the effectiveness of conservation measures. The current methods for determining the age groups of giant pandas are mainly based on the size and length of giant panda feces and the bite value of intact bamboo in the feces, or in the case of a skeleton, through the wear of molars and the growth line of teeth. These methods have certain flaws that limit their applications. In this study, we developed a deep learning method to study age group classification based on facial images of captive giant pandas and achieved an accuracy of 85.99% on EfficientNet. The experimental results show that the faces of giant pandas contain some age information, which mainly concentrated between the eyes of giant pandas. In addition, the results also indicate that it is feasible to identify the age groups of giant pandas through the analysis of facial images.