The giant panda is an example of a species that has faced extensive historical habitat fragmentation and anthropogenic disturbance, and is assumed to be isolated in numerous subpopulations with limited gene flow between them. To investigate the population size, health and connectivity of pandas in a key habitat area, we noninvasively collected a total of 539 fresh wild giant panda fecal samples for DNA extraction within Wolong Nature Reserve, Sichuan, China. Seven validated tetra-microsatellite markers were used to analyze each sample, and a total of 142 unique genotypes were identified. Non-spatial and spatial capture-recapture models estimated the population size of the reserve at 164 and 137 individuals (95% confidence intervals 153-175 and 115-163), respectively. Relatively high levels of genetic variation and low levels of inbreeding were estimated, indicating adequate genetic diversity. Surprisingly, no significant genetic boundaries were found within the population despite the national road G350 that bisects the reserve, which is also bordered with patches of development and agricultural land. We attribute this to high rates of migration, with 4 giant panda road-crossing events confirmed within a year based on repeated captures of individuals. This likely means that giant panda populations within mountain ranges are better connected than previously thought. Increased development and tourism traffic in the area and throughout the current panda distribution poses a threat of increasing population isolation, however. Maintaining and restoring adequate habitat corridors for dispersal is thus a vital step for preserving the levels of gene flow seen in our analysis and the continued conservation of the giant panda meta-population in both Wolong and throughout their current range.

The national surveys on giant panda (Ailuropoda melanoleuca) population and habitat quality have shown a high-density population of this species in the Qinling Mountains, China. We investigated five adjacent nature reserves (NR), i.e., the key distribution area of giant pandas in the Qinling Mountains, to model and identify the potential dispersal routes for giant pandas. We hypothesized that giant pandas will spread to neighboring areas when the population of the species keeps increasing. Habitat suitability was firstly evaluated based on environmental and disturbance factors. We then identified source and sink patches for giant pandas’ dispersal. Further, Minimum Cumulative Resistance (MCR) model was applied to calculate cost of movement. Finally, the Current Theory was adopted to model linkages between source and sink patches to explore potential dispersal routes of giant pandas. Our results showed that (1) the three large source patches and eight potential sink patches were identified; (2) the 14 potential corridors were predicted for giant pandas dispersing from source patches to the neighboring areas; (3) through the predicted corridors, the giant pandas in the source patches could disperse to the west, the south and the east sink patches. Our research revealed possible directional patterns for giant pandas’ dispersal in their key distribution area of the Qinling Mountains, and can provide the strong recommendations in policy and conservation strategies for improving giant panda habitat management in those identified sink patches and also potential dispersal corridors.

How high is the brand awareness of Panda Express in the United States?When it comes to restaurant chain customers, brand awareness of Panda Express is at 87% in the United States. The survey was conducted using the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name.How popular is Panda Express in the United States?In total, 30% of U.S. restaurant chain customers say they like Panda Express. What is the usage share of Panda Express in the United States?All in all, 23% of restaurant chain customers in the United States use Panda Express. How loyal are the customers of Panda Express?Around 19% of restaurant chain customers in the United States say they are likely to use Panda Express again. What's the buzz around Panda Express in the United States?In October 2024, about 11% of U.S. restaurant chain customers had heard about Panda Express in the media, on social media, or in advertising over the past three months. If you want to compare brands, do deep-dives by survey items of your choice, filter by total online population or users of a certain brand, or drill down on your very own hand-tailored target groups, our Consumer Insights Brand KPI survey has you covered.

The taxonomy in woody bamboo faces a lot of difficulties due to its long blooming intervals and complicated morphological variation. Whether the current taxonomy would reflect the genuine species divergence within woody bamboo is an intriguing question. Fargesia spathacea complex comprises fifteen closely related species with sympatric distribution in China. Their classification has long been controversy because of only a handful of vegetative traits available, thus providing a good opportunity to explore the evolutionary relationship and genetic differentiation in woody bamboo. Here we presented a study with 750 individuals from 39 representative populations in Fargesia spathacea complex using 14 SSR markers. We found varying degrees of genetic diversity across populations of the Fargesia spathacea complex (He=0.07-0.81) and largely negative F values at the population level, implying an excess of heterozygotes in the populations. Phylogenetic analyses revealed that all populations were divided into two major groups (cluster A and B), with the majority of fifteen species representing distinct genetic lineages. Based on the population genetic analysis along with morphological evidence, we confirmed the identity of three species (F. decurvata, F. spathacea and F. murielae) and suggested invalidation of four other species (scabrida, F. robusta, F. denudata and F. nitida). The delimitation of the rest eight species was yet to be explored. The ecological factor and spatial autocorrelation analysis supported that altitude difference might account for the distinct genetic divergence between two major groups.

Recently, an increasing number of microsatellites or Simple Sequence Repeats (SSRs) have been found and characterized from transcriptome. Such SSRs can be employed as putative functional markers to easily tag corresponding genes, which play an important role in biomedical studies and genetic analysis. However, the transcriptome-derived SSRs for giant panda (Ailuropoda melanoleuca) are not yet available. In the present work, we identified and characterized 20 tetranucleotide microsatellite loci from a transcript database generated from the blood of giant panda. Furthermore, we assigned their predicted transcriptome locations: 16 loci were assigned to untranslated regions (UTRs) and 4 loci were assigned to coding regions (CDSs). Gene identities of 14 transcripts contained corresponding microsatellites were determined, which provide useful information to study the potential contribution of SSRs to gene regulation in giant panda. The polymorphic information content (PIC) values ranged from 0.293 to 0.789 with an average of 0.603 for the 16 UTRs-derived SSRs. Interestingly, four CDS-derived microsatellites developed in our study were also polymorphic, and the instability of these four CDS-derived SSRs was further validated by re-genotyping and sequencing. The genes contained these four CDS-derived SSRs were embedded with various types of repeat motifs. The interaction of all the length-changing SSRs might provide a way against coding region frameshift caused by microsatellite instability. We hope these newly gene-associated biomarkers would pave the way for genetic and biomedical studies for giant panda in the future. In sum, this set of transcriptome-derived markers complements the genetic resources available for giant panda.

This layer shows the overall 2016 Environmental Democracy Index for 70 countries around the world. The map also shows the total population of each country for reference.The Environmental Democracy Index is an average of three overall pillars: transparency, participation, and justice. These pillars are made up of 23 guidelines adopted by the United Nations Environment Programme (UNEP), which are arithmetic averages of 75 legal indicators. As described on the Background and Methodology page, the Environmental Democracy Index rides on the following:"Environmental democracy is rooted in the idea that meaningful public participation is critical to ensure that land and natural resource decisions adequately and equitably address citizens’ interests. At its core, environmental democracy involves three mutually reinforcing rights:the right to freely access information on environmental quality and problemsthe right to participate meaningfully in decision-makingthe right to seek enforcement of environmental laws or compensation for harm.Protecting these rights, especially for the most marginalized and vulnerable, is the first step to promoting equity and fairness in sustainable development. Without essential rights, information exchange between governments and the public is stifled and decisions that harm communities and the environment cannot be challenged or remedied. Establishing a strong legal foundation is the starting point for recognizing, protecting and enforcing environmental democracy. "The population estimate comes from the Esri 2016 World Population Estimate.

This layer shows the change in employment in agriculture, which are originally provided as a percentage of total employment in different countries. (modeled ILO estimate)Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The agriculture sector consists of activities in agriculture, hunting, forestry and fishing, in accordance with division 1 (ISIC 2) or categories A-B (ISIC 3) or category A (ISIC 4).Data is from the World Bank and was acquired on 4/19/2018.