The Structure of Potential Amur Tiger (Panthera tigris altaica) Habitats and Evaluation of Its Prey in Taipingou National Reserve (China) Based on Remote Sensing Data

2020 ◽  
Vol 56 (9) ◽  
pp. 1107-1126
Author(s):  
Shibing Zhu ◽  
Yi Qu ◽  
Yingzhu Liu ◽  
D. V. Dobrynin ◽  
O. V. Sukhova ◽  
...  
Author(s):  
Shibing Zhu ◽  
Yi Qu ◽  
Yingzhu Liu ◽  
D. V. Dobrynin ◽  
O. V. Sukhova ◽  
...  

Today the population of the Amur tiger (Panthera tigris altaica) in the Russian Far East is being restored, young individuals are spread within the historical range, including the territory of China. Here the assessment of the territories suitability that exists at Northeastern China as the habitat of the Amur tiger and its food supply (three species of ungulates – wild boar, red deer and roe deer) are shown. Basically a specially protected area is chosen – the Taipingou National Park, located on the border of the Public Republic of China and Russia. The modeling of habitat suitability for ungulates was carried out on the basis of remote sensing data (Earth remote sensing) by using two different approaches – expert geo-information assessment of the territory and discriminant analysis modeling. The modeling of the suitability of ungulate habitats without the variability of plant communities based on discriminant analysis and showed a small difference between the model results for wild boar and roe deer. Nevertheless, the connection with the morphometric characteristics of the relief is more important for the wild boar than for the roe deer, and for the roe deer there is a variability of vegetation types more important. The results of the analysis that included the type of biotopes, showed that the wild boar prefers the central and northern parts of the Taipingou National Park, while the roe deer is the western part of the park; red deer is more common in the southern part of the park.


2002 ◽  
Vol 8 (1) ◽  
pp. 15-22
Author(s):  
V.N. Astapenko ◽  
◽  
Ye.I. Bushuev ◽  
V.P. Zubko ◽  
V.I. Ivanov ◽  
...  

2011 ◽  
Vol 17 (6) ◽  
pp. 30-44
Author(s):  
Yu.V. Kostyuchenko ◽  
◽  
M.V. Yushchenko ◽  
I.M. Kopachevskyi ◽  
S. Levynsky ◽  
...  

2017 ◽  
Vol 6 (1) ◽  
pp. 2246-2252 ◽  
Author(s):  
Ajay Roy ◽  
◽  
Anjali Jivani ◽  
Bhuvan Parekh ◽  
◽  
...  

Author(s):  
Rupali Dhal ◽  
D. P. Satapathy

The dynamic aspects of the reservoir which are water spread, suspended sediment distribution and concentration requires regular and periodical mapping and monitoring. Sedimentation in a reservoir affects the capacity of the reservoir by affecting both life and dead storages. The life of a reservoir depends on the rate of siltation. The various aspects and behavior of the reservoir sedimentation, like the process of sedimentation in the reservoir, sources of sediments, measures to check the sediment and limitations of space technology have been discussed in this report. Multi satellite remote sensing data provide information on elevation contours in the form of water spread area. Any reduction in reservoir water spread area at a specified elevation corresponding to the date of satellite data is an indication of sediment deposition. Thus the quality of sediment load that is settled down over a period of time can be determined by evaluating the change in the aerial spread of the reservoir at various elevations. Salandi reservoir project work was completed in 1982 and the same is taken as the year of first impounding. The original gross and live storages capacities were 565 MCM& 556.50 MCM respectively. In SRS CWC (2009), they found that live storage capacity of the Salandi reservoir is 518.61 MCM witnessing a loss of 37.89 MCM (i.e. 6.81%) in a period of 27 years.The data obtained through satellite enables us to study the aspects on various scales and at different stages. This report comprises of the use of satellite to obtain data for the years 2009-2013 through remote sensing in the sedimentation study of Salandi reservoir. After analysis of the satellite data in the present study(2017), it is found that live capacity of the reservoir of the Salandi reservoir in 2017 is 524.19MCM witnessing a loss of 32.31 MCM (i.e. 5.80%)in a period of 35 years. This accounts for live capacity loss of 0.16 % per annum since 1982. The trap efficiencies of this reservoir evaluated by using Brown’s, Brune’s and Gill’s methods are 94.03%, 98.01and 99.94% respectively. Thus, the average trap efficiency of the Salandi Reservoir is obtained as 97.32%.


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