A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

A new species of Galearis (Orchidinae: Orchidaceae) from Sichuan,China

A new species, Galearis huanglongensis Q.W.Meng & Y.B.Luo, is described and illustrated. It is similar to Galearis cyclochila (Franch. & Sav.) Soó and Galearis diantha (Schltr.) P.F.Hunt, but differs in having a short spur, two elliptical lateral stigma lobes and distinctly separated bursicles. This new species is known only from the type locality, the Huanglong Valley, Songpan County, western Sichuan, China, growing amongst mosses under alpine shrubs at an elevation of about 3000 m. Based on two years of observations of its population size, the species was categorized as critically endangered CR (B1a, B2a) according to the World Conservation Union (IUCN) Red List Categories and Criteria, Version 3.1. The micromorphology of pollinia and seeds was observed by scanning electron microscopy and compared with that of G. cyclochila and G. diantha. The results supported G. huanglongensis Q.W.Meng & Y.B.Luo as a new species. © 2008 The Linnean Society of London, Botanical Journal of the Linnean Society, 2008, 158 , 689–695.     

Spatial and temporal factors associated with nest survival of Gray Flycatchers in managed ponderosa pine forests

Gray Flycatchers (Empidonax wrightii) breed in a variety of habitats in the arid and semi‐arid regions of the western United States, but little is known about their breeding biology, especially in the northern portion of their range where they nest in ponderosa pine (Pinus ponderosa) forests. From May to July 2014 and 2015, we conducted surveys for singing male Gray Flycatchers along the eastern slope of the Cascade Range in Washington, U.S.A, monitored flycatcher nests, and quantified nest‐site vegetation. We used a logistic‐exposure model fit within a Bayesian framework to model the daily survival probability of flycatcher nests. During the 2 yr of our study, we monitored 141 nests, with 93% in ponderosa pines. Mean clutch size was 3.6 eggs and the mean number of young fledged per nest was 3.2. Predation accounted for 90% of failed nests. We found a positive association between daily nest survival and both nest height and distance of nest substrates from the nearest tree. Flycatchers that locate their nests higher above the ground and further from adjacent trees may be choosing the safest alternative because higher nests may be less exposed to terrestrial predators and nests in trees that are farther from other trees may be less exposed to arboreal predators such as jays (Corvidae) that may forage in patches with connected canopies. Nests in trees farther from other trees may also allow earlier detection of approaching predators and thus aid in nest defense.     

Glycogen debranching enzyme: purification, antibody characterization, and immunoblot analyses of type III glycogen storage disease.

Type III glycogen storage disease is caused by a deficiency of glycogen debranching-enzyme activity. Many patients with this disease have both liver and muscle involvement, whereas others have only liver involvement without clinical or laboratory evidence of myopathy. To improve our understanding of the molecular basis of the disease, debranching enzyme was purified 238-fold from porcine skeletal muscle. In sodium dodecyl sulfate-polyacrylamide gel electrophoresis the purified enzyme gave a single band with a relative molecular weight of 160,000 that migrated to the same position as purified rabbit-muscle debranching enzyme. Antiserum against porcine debranching enzyme was prepared in rabbit. The antiserum reacted against porcine debranching enzyme with a single precipitin line and demonstrated a reaction having complete identity to those of both the enzyme present in crude muscle and the enzyme present in liver extracts. Incubation of antiserum with purified porcine debranching enzyme inhibited almost all enzyme activity, whereas such treatment with preimmune serum had little effect. The antiserum also inhibited debranching-enzyme activity in crude liver extracts from both pigs and humans to the same extent as was observed in muscle. Immunoblot analysis probed with anti-porcine-muscle debranching-enzyme antiserum showed that the antiserum can detect debranching enzyme in both human muscle and human liver. The bands detected in human samples by the antiserum were the same size as the one detected in porcine muscle. Five patients with Type III and six patients with other types of glycogen storage disease were subjected to immunoblot analysis. Although anti-porcine antiserum detected specific bands in all liver and muscle samples from patients with other types of glycogen storage disease (Types I, II, and IX), the antiserum detected no cross-reactive material in any of the liver or muscle samples from patients with Type III glycogen storage disease. These data indicate (1) immunochemical similarity of debranching enzyme in liver and muscle and (2) that deficiency of debranching-enzyme activity in Type III glycogen storage disease is due to absence of debrancher protein in the patients that we studied.