Network approach to studying spatial ecology of apex predators and ungulates of southeastern Sikhote-Alin range (Primorsky Krai)

DOI: 10.35595/2414-9179-2023-1-29-668-681

View or download the article (Rus)

About the Authors

Vladimir N. Bocharnikov

Pacific Geographical Institute FEB RAS,
7, Radio str., Vladivostok, 690041, Russia,
E-mail: vbocharnikov@mail.ru

Andrey I. Trufanov

Irkutsk National Research Technical University,
83, Lermontova str., Irkutsk, 664074, Russia,
E-mail: troufan@gmail.com

Lyudmila G. Emelyanova

Lomonosov Moscow State University, Faculty of Geography,
1, Leninskie Gory, Moscow, 119991, Russia,
E-mail: biosever@yandex.ru

Abstract

Network analysis has proven to be an effective tool for understanding patterns and predicting consequences in the study of complex systems on a local, regional and global scale. In the south of the Russian Far East exists one of the highest levels of biodiversity in Russia. This paper presents mainly theoretical study, its results includes maps and of spatial structure distribution schemes in the winter of the Amur tiger and the main objects of its food interest—ungulates. The research model area situated within the mountain-forest territory of Southeastern Sikhote-Alin Mountains (Primorsky Krai). This region is home to species of worldwide conservation significance, including the Amur tiger (Panthera tigris altaica). The results of the study show the interpenetration of places of human activity and infrastructure into the main habitats of large animals in winter. The factors threatening the existence of large predators can be divided into three types: anthropogenic (related to the presence of man and his economic activity); technogenic (caused by implemented technological systems, for example, transport and fuel and energy infrastructure); natural (natural disasters, as well as relief and landscape conditions that prevent the existence of living organisms of wildlife). The work presents: 1) network models and geoinformation mapping of the winter distribution of the Amur tiger, which is the result of using the proximity threshold as a key variable parameter of the network model; 2) maps of the distribution of ungulates have been compiled by recalculating the total number of animals by their population density in hunting grounds; 3) network models of the human-occupied space (roads, settlements) of the model territory have been prepared and distribution of hunting enterprises. The applied synergy of geoinformation modeling and network analysis provides effective analytical tools for research in the spatial ecology of animals.

Keywords

spatial ecology, apex predators, population threats, geoinformation modeling, network analysis

References

  1. Bergsten A., Zetterberg A. To model the landscape as a network: A practitioner’s perspective. Landscape and Urban Planning, 2013. V. 119. P. 35–43. DOI: 10.1016/j.landurbplan.2013.06.009.
  2. Besson M., Delmas E., Poisot T., Gravel D. Complex ecological networks. Encyclopedia of Ecology, 2019. P. 536–545. DOI: 10.1016/b978-0-12-409548-9.10564-0.
  3. Carter N.H., Viña A., Hull V., McConnell W.J., Axinn W., Ghimire D., Liu J. Coupled human and natural systems approach to wildlife research and conservation. Ecology and Society, 2014. V. 19. No. 3. Art. 43. DOI: 10.5751/ES-06881-190343.
  4. Fenu G., Pau P.L. Topological and conceptual complex network models for environmental planning. Procedia Computer Science, 2016. V. 83. P. 123–130. DOI: 10.1016/j.procs.2016.04.107.
  5. Gawecka K.A., Bascompte J. Habitat restoration in spatially explicit metacommunity models. Journal of Animal Ecology, 2021. V. 90. Iss. 5. P. 1239–1251. DOI: 10.1111/1365-2656.13450.
  6. Gray C., Baird D.J., Baumgartner S., Jacob U., Jenkins G.B., O’Gorman E.J., Lu X., Ma A., Pocock M.J., Schuwirth N., Thompson M., Woodward G. FORUM: Ecological networks: The missing links in biomonitoring science. Journal of Applied Ecology, 2014. V. 51. Iss. 5. P. 1444–1449. DOI: 10.1111/1365-2664.12300.
  7. Kerley L.L., Borisenko M.M. Amur tiger survivability and movement between Lazovsky Reserve and Zov Tigra (Call of the Tiger) National Park. XII Far Eastern conference on conservation, 2017. P. 87–89 (in Russian).
  8. Maguire D.Y., James P.M.A., Buddle C.M., Bennett E.M. Landscape connectivity and insect herbivory: A framework for understanding tradeoffs among ecosystem services. Global Ecology and Conservation, 2015. V. 31. P. 73–84. DOI: 10.1016/j.gecco.2015.05.006.
  9. Pikunov D.G., Seredkin I.V., Solkin V.A. Amur tiger (history of study, range dynamics, abundance, ecology and conservation strategy). Vladivostok: Dal’nauka, 2010. 104 p. (in Russian).
  10. Salkina G.P., Poddubnaya N.Ya. Trace records of the tiger in the Lazovsky Reserve. Monitoring of the state of natural complexes and long-term research in specially protected natural territories, 2019. No. 3. P. 88–95 (in Russian).
  11. Shi F., Liu S., An Y., Sun Y., Zhao S., Liu Y., Li M. Spatio-temporal dynamics of landscape connectivity and ecological network construction in Long Yangxia Basin at the Upper Yellow River. Land, 2020. V. 9. No. 8. Art. 265. DOI: 10.3390/land9080265.
  12. Sochava V.B. Introduction to the doctrine of geosystems. Novosibirsk: Nauka, 1978. 317 p. (in Russian).
  13. Taylor P.D., Fahrig L., Henein K., Merriam G. Connectivity is a vital element of landscape structure. Oikos, 1993. V. 68. P. 571–573. DOI: 10.2307/3544927.
  14. Tiang D.C.F., Morris A., Bell M., Gibbins C., Azhar B., Lechner A. Ecological connectivity in fragmented agricultural landscapes and the importance of scattered trees and small patches. Ecological Processes, 2021. V. 10. Art. 20. DOI: 10.1186/s13717-021-00284-7.

For citation: Bocharnikov V.N., Trufanov A.I., Emelyanova L.G. Network approach to studying spatial ecology of apex predators and ungulates of southeastern Sikhote-Alin range (Primorsky Krai). InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: MSU, Faculty of Geography, 2023. V. 29. Part 1. P. 668–681. DOI: 10.35595/2414-9179-2023-1-29-668-681 (in Russian)