Comparative Analysis and Molecular Characterization of a Gene BANF1 Encoded a DNA-Binding Protein During Mitosis from the Giant Panda and Black Bear

Barrier to autointegration factor 1 (BANF1) is a DNA-binding protein found in the nucleus and cytoplasm of eukaryotic cells that functions to establish nuclear architecture during mitosis. The cDNA and the genomic sequence of BANF1 were cloned from the Giant Panda (Ailuropoda melanoleuca) and Black Bear (Ursus thibetanus mupinensis) using RT-PCR technology and Touchdown-PCR, respectively. The cDNA of the BANF1 cloned from Giant Panda and Black Bear is 297 bp in size, containing an open reading frame of 270 bp encoding 89 amino acids. The length of the genomic sequence from Giant Panda is 521 bp, from Black Bear is 536 bp, which were found both to possess 2 exons. Alignment analysis indicated that the nucleotide sequence and the deduced amino acid sequence are highly conserved to some mammalian species studied. Topology prediction showed there is one Protein kinase C phosphorylation site, one Casein kinase II phosphorylation site, one Tyrosine kinase phosphorylation site, one N-myristoylation site, and one Amidation site in the BANF1 protein of the Giant Panda, and there is one Protein kinase C phosphorylation site, one Tyrosine kinase phosphorylation site, one N-myristoylation site, and one Amidation site in the BANF1 protein of the Black Bear. The BANF1 gene can be readily expressed in E. coli. Results showed that the protein BANF1 fusion with the N-terminally His-tagged form gave rise to the accumulation of an expected 14 kD polypeptide that formed inclusion bodies. The expression products obtained could be used to purify the proteins and study their function further.     

Nucleotide Sequences of an Important Functional Gene hnRNPA2/B1 from Ailuropoda melanoleuca and Ursus thibetanus mupinensis and Its Potential Value in Phylogenetic Study

The cDNA fragments of hnRNPA2/B1 were cloned from the giant panda and black bear using RT-PCR method, which were, respectively, 1029bp and 1026bp in length encoding 343 and 341 amino acids. Analysis indicated the cDNA cloned from the giant panda encoded variant B1 while the cDNA cloned from black bear encoded variant A2.

Analyzing the hnRNPA2B1 peptide of the giant panda and black bear, 76 glycine residues and 86 glycine residues were, respectively, found, and moreover, most glycine are concentrated in the latter halves of the hnRNPA2B1 peptides. Functional sites prediction also showed many N-myristoylation sites existed in the glycine-rich domain, which is probably related to the role of telomere maintenance.

From base bias and substitution analysis, we can conclude that the ORF of hnRNPA2/B1 biased G while hated C, and transition of the third site did not achieve the level of saturation.

Orthology analysis indicated that both the nucleotide sequence and the deduced amino acid sequence showed high identity to other 26 hnRNPA2/B1 sequences from mammals and nonmammals reported. These sequences were used to construct phylogenetic trees employing the NJ method with 1000 bootstrap, and the obtained tree demonstrated similar topology with the classical systematics, which suggested the potential value of hnRNPA2/B1 in phylogenetic analysis.

This report will be the first step to the study function of hnRNPA2/B1 in the giant panda and black bear, and will provide a scientific basis to disease surveillance, captive breeding, and conservation of the endangered species.     

Spatiotemporal Distribution of Black Bear-Human Conflicts in Colorado,USA

Abstract: Management and conservation of large carnivores increasingly includes conflicts with humans. Consequently, a greater understanding of spatiotemporal trends of conflicts is needed to efficiently allocate resources and apply targeted management. Therefore, we examined spatial and temporal distribution of American black bear (Ursus americanus; hereafter, bear)-human conflicts in Colorado, USA, related to 3 conflict types (agriculture operations, human development, and road kills). We used the Getis-Ord G_i* spatial clustering statistic to describe location and assess magnitude of bear-human conflicts in Colorado during 1986–2003 and investigated temporal trends of bear-human conflicts by type. Bear-human conflicts showed distinct spatial clustering by type, and areas of high clustering overlapped conflict types. Clustering for agriculture operations conflicts had the largest overall G_i* value and overlapped counties with high sheep production. Both human development and road-kill conflict clusters were high in areas of high-quality oak (Quercus spp.)—shrub habitat in the central and southern portions of Colorado's Front Range region and near the city of Durango in southwestern Colorado. Bear-human conflicts varied by year and type but overall increased during the 18 years. Summed across years, most conflicts were related to agriculture (32%), followed by road kills (27%) and human development (24%). The greatest proportion of agriculture operations-related conflicts (76%), human development-related conflicts (36%), and road kills (47%) occurred in 1988, 1999, and 2003, respectively. Considering that bear-human conflicts in Colorado increased over time and will likely continue to increase, we suggest wildlife managers improve data collection by obtaining detailed location data, categorizing conflict types uniformly, and applying conflict regulations consistently to strengthen inference of similar analyses. We also suggest that managers target efforts to mitigate damage by focusing on areas with high clustering of conflicts.     

Comparing clustered sampling designs for spatially explicit estimation of population density

Spatially explicit capture–recapture methods do not assume that animals have equal access to sampling devices (e.g., detectors), which allows for gaps in the sampling extent and nonuniform (e.g., clustered) sampling designs. However, the performance (i.e., relative root mean squared error [RRMSE], confidence interval coverage, relative bias and relative standard error) of clustered detector arrays has not been thoroughly evaluated. I used simulations to evaluate the performance of various detector and cluster spacings, cluster configurations (i.e., number of detectors arranged in a square grid), sampling extents and number of sampling occasions for estimating population density, the relationship between detection rate and distance to a detector from the animal's center of activity (σ) and base detection rates, using American black bears (Ursus americanus) as a case study. My simulations indicated that a wide range of detector configurations can provide reliable estimates if spacing between detectors in clusters is ≥1σ and ≤3σ. A number of cluster configurations and occasion lengths produced estimates that were unbiased, resulted in good spatial coverage, and were relatively precise. Moreover, increasing the duration of sampling, establishing large study areas, increasing detection rates and spacing clusters so that cross-cluster sampling of individuals can occur could help ameliorate deficiencies in the detector layout. These results have application for a wide array of species and sampling methods (e.g., DNA sampling, camera trapping, mark-resight and search-encounter) and suggest that clustered sampling can significantly reduce the effort necessary to provide reliable estimates of population density across large spatial extents that previously would have been infeasible with nonclustered sampling designs.     

人熊冲突缓解措施研究进展——以三江源国家公园为例

人与熊科动物之间的冲突已成为亚洲、欧洲和美洲地区的一个普遍问题,科学有效的人熊冲突管控措施有助于人熊共存机制的建立。目前,全球范围内肇事熊科动物涉及7种,分别为棕熊、亚洲黑熊、美洲黑熊、北极熊、马来熊、懒熊和眼镜熊。肇事类型主要包括伤人、捕食牲畜、入侵房屋、损害庄稼、袭击蜂箱以及翻食垃圾。引发人熊冲突的原因与人类活动范围扩大、熊科动物种群数量上升、熊科动物生境质量下降、熊科动物自然食源周期性短缺、人类食物来源易获得性以及公众对肇事熊的容忍度下降有关。国际上已有的人熊冲突缓解措施包括物理措施、生物措施、化学措施以及政策导向性措施,然而,多数措施的制定仅停留在措施本身的技术层面上,缺乏对地方实际情况和冲突驱动因素的分析。西藏棕熊属于棕熊的一种稀有亚种,生活在靠近人类的中亚高海拔地区。在中国三江源国家公园地区,人类与西藏棕熊的冲突引起了人们的关注,为协助制订有效的保育目标、解决区内人熊冲突问题,提出以下缓解建议:(1)缓解措施的制定需因地而异,综合考虑地方实际情况,如地理环境、法律法规、民俗文化以及宗教信仰等;(2)冲突类型多样,防熊措施需持续更新与完善;(3)加强人类社会发展与熊科动物生存之间的关系研究,探索人们生产生活方式的改变与熊科动物行为变化之间的关系;(4)加强棕熊生态学方面的研究,从棕熊生境质量、种群动态、自然食源以及生态系统完整性等方面去深入挖掘人熊冲突的驱动因素,进而从根本上制定缓解措施,促进三江源国家公园地区人熊共存。     

Modeling optimal responses and fitness consequences in a changing Arctic

Animals must balance a series of costs and benefits while trying to maximize their fitness. For example, an individual may need to choose how much energy to allocate to reproduction versus growth, or how much time to spend on vigilance versus foraging. Their decisions depend on complex interactions between environmental conditions, behavioral plasticity, reproductive biology, and energetic demands. As animals respond to novel environmental conditions caused by climate change, the optimal decisions may shift. Stochastic dynamic programming provides a flexible modeling framework with which to explore these trade‐offs, but this method has not yet been used to study possible changes in optimal trade‐offs caused by climate change. We created a stochastic dynamic programming model capturing trade‐off decisions required by an individual adult female polar bear (Ursus maritimus) as well as the fitness consequences of her decisions. We predicted optimal foraging decisions throughout her lifetime as well as the energetic thresholds below which it is optimal for her to abandon a reproductive attempt. To explore the effects of climate change, we shortened the spring feeding period by up to 3 weeks, which led to predictions of riskier foraging behavior and higher reproductive thresholds. The resulting changes in fitness may be interpreted as a best‐case scenario, where bears adapt instantaneously and optimally to new environmental conditions. If the spring feeding period was reduced by 1 week, her expected fitness declined by 15%, and if reduced by 3 weeks, expected fitness declined by 68%. This demonstrates an effective way to explore a species' optimal response to a changing landscape of costs and benefits and highlights the fact that small annual effects can result in large cumulative changes in expected lifetime fitness.     

Estimating the energy expenditure of free‐ranging polar bears using tri‐axial accelerometers: A validation with doubly labeled water

Measures of energy expenditure can be used to inform animal conservation and management, but methods for measuring the energy expenditure of free‐ranging animals have a variety of limitations. Advancements in biologging technologies have enabled the use of dynamic body acceleration derived from accelerometers as a proxy for energy expenditure. Although dynamic body acceleration has been shown to strongly correlate with oxygen consumption in captive animals, it has been validated in only a few studies on free‐ranging animals. Here, we use relationships between oxygen consumption and overall dynamic body acceleration in resting and walking polar bears Ursus maritimus and published values for the costs of swimming in polar bears to estimate the total energy expenditure of 6 free‐ranging polar bears that were primarily using the sea ice of the Beaufort Sea. Energetic models based on accelerometry were compared to models of energy expenditure on the same individuals derived from doubly labeled water methods. Accelerometer‐based estimates of energy expenditure on average predicted total energy expenditure to be 30% less than estimates derived from doubly labeled water. Nevertheless, accelerometer‐based measures of energy expenditure strongly correlated (r² = 0.70) with measures derived from doubly labeled water. Our findings highlight the strengths and limitations in dynamic body acceleration as a measure of total energy expenditure while also further supporting its use as a proxy for instantaneous, detailed energy expenditure in free‐ranging animals.     

Accounting for phenology in the analysis of animal movement

The analysis of animal tracking data provides important scientific understanding and discovery in ecology. Observations of animal trajectories using telemetry devices provide researchers with information about the way animals interact with their environment and each other. For many species, specific geographical features in the landscape can have a strong effect on behavior. Such features may correspond to a single point (eg, dens or kill sites), or to higher dimensional subspaces (eg, rivers or lakes). Features may be relatively static in time (eg, coastlines or home‐range centers), or may be dynamic (eg, sea ice extent or areas of high‐quality forage for herbivores). We introduce a novel model for animal movement that incorporates active selection for dynamic features in a landscape. Our approach is motivated by the study of polar bear (Ursus maritimus) movement. During the sea ice melt season, polar bears spend much of their time on sea ice above shallow, biologically productive water where they hunt seals. The changing distribution and characteristics of sea ice throughout the year mean that the location of valuable habitat is constantly shifting. We develop a model for the movement of polar bears that accounts for the effect of this important landscape feature. We introduce a two‐stage procedure for approximate Bayesian inference that allows us to analyze over 300 000 observed locations of 186 polar bears from 2012 to 2016. We use our model to estimate a spatial boundary of interest to wildlife managers that separates two subpopulations of polar bears from the Beaufort and Chukchi seas.