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.

     

Phosphoproteins in dictyostelium discoideum

The phosphoproteins of Dictyostelium discoideum were compared at different stages of development by polyacrylamide gel electrophoresis. Certain phosphoproteins of vegetative amoebae were conserved while others appeared and disappeared during development. Four major phosphoproteins with apparent subunit molecular weights of 50,000, 47,000, 38,000, and 34,000 disappeared precociously in response to exogenous cAMP. Two membranal phosphoproteins, with apparent subunit molecular weights of 80,000 and 81,000, appeared precociously in response to added cAMP. One of these phosphoproteins, molecular weight of 80,000, has been identified tentatively as the “contact site A” glycoprotein. Another membranal protein, with apparent subunit molecular weight of 42,000, unaffected in its appearance by cAMP, has been identified tentatively as phosphoactin.     

Putative candidate genes for blood pressure control in the SHR.BN-RNO8 congenic substrains

The SHR-Lx congenic strain carrying a differential segment of chromosome 8 of BN and PD origin was recently shown to exhibit a significant decrease in blood pressure as compared to the SHR strain. There were two positional candidate genes for blood pressure control mapped to the differential segment: the rat kidney epithelial potassium channel gene (Kcnj1) and brain dopamine receptor 2 gene (Drd2). Bot these genes were separated into SHR.BN-RNO8 congenic substrains. In this communication, we are presenting the assignment of two further putative candidate genes, which might be involved in blood pressure control to the BN/PD differential segment of the SHR-Lx congenic strain. These are: the gene coding for smooth muscle cell specific protein 22 (Sm22) defined by the D8Mcw1 marker and neuronal nicotinic acetylcholine receptor gene cluster, defined by the D8Bord1 marker. Moreover, the glutamate receptor gene Grik4 which also maps to the differential segment of the SHR-Lx should be taken into account. The genetic separation of all these putative candidate genes of blood pressure control is being performed by recombinations and subsequent selection using (SHR×SHR-Lx) intercross population.     

Climatic forcing and larval dispersal capabilities shape the replenishment of fishes and their habitat‐forming biota on a tropical coral reef

Fluctuations in marine populations often relate to the supply of recruits by oceanic currents. Variation in these currents is typically driven by large‐scale changes in climate, in particular ENSO (El Nino Southern Oscillation). The dependence on large‐scale climatic changes may, however, be modified by early life history traits of marine taxa. Based on eight years of annual surveys, along 150 km of coastline, we examined how ENSO influenced abundance of juvenile fish, coral spat, and canopy‐forming macroalgae. We then investigated what traits make populations of some fish families more reliant on the ENSO relationship than others. Abundance of juvenile fish and coral recruits was generally positively correlated with the Southern Oscillation Index (SOI), higher densities recorded during La Niña years, when the ENSO‐influenced Leeuwin Current is stronger and sea surface temperature higher. The relationship is typically positive and stronger among fish families with shorter pelagic larval durations and stronger swimming abilities. The relationship is also stronger at sites on the coral back reef, although the strongest of all relationships were among the lethrinids (r = .9), siganids (r = .9), and mullids (r = .8), which recruit to macroalgal meadows in the lagoon. ENSO effects on habitat seem to moderate SOI–juvenile abundance relationship. Macroalgal canopies are higher during La Niña years, providing more favorable habitat for juvenile fish and strengthening the SOI effect on juvenile abundance. Conversely, loss of coral following a La Niña‐related heat wave may have compromised postsettlement survival of coral dependent species, weakening the influence of SOI on their abundance. This assessment of ENSO effects on tropical fish and habitat‐forming biota and how it is mediated by functional ecology improves our ability to predict and manage changes in the replenishment of marine populations.