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The Spatial and Typological Structure and Organization of Summer Bird Assemblages in Kyrgyzstan
— The results of multivariate analyses of the data obtained during the summer period in Kyrgyzstan, Central Asia are presented. The total length of the survey routes was about 1700 km. A comparison with a similar study carried out earlier using half of the initial data makes it possible to assess th...
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Published in: | Biology bulletin of the Russian Academy of Sciences 2022-12, Vol.49 (9), p.1398-1405 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | —
The results of multivariate analyses of the data obtained during the summer period in Kyrgyzstan, Central Asia are presented. The total length of the survey routes was about 1700 km. A comparison with a similar study carried out earlier using half of the initial data makes it possible to assess the representativeness of the collected material and to clarify the perception of the spatial heterogeneity of bird assemblages in Kyrgyzstan. The main environmental factors that determine the variations in bird assemblages are the type of vegetation, afforestation, and provincial differences in topography and climate. These account for 38% of the similarity matrix variance of bird assemblages. Structural graphs and hierarchical classifications constructed from both data sets demonstrate high-degrees of coincidence. The differences come to a slightly higher estimate of the strength of the relationship between the variability of bird assemblages and terrain elevations in the first variant of calculation using a smaller amount of data, versus the degree of afforestation in the second, complete, variant. The information content of both classifications, as estimated by the total value of the explained variance of the similarity matrix of the analyzed assemblages, differs insignificantly. The expert division of the territory using bird assemblages is shown to be less informative than the results of cluster analyses. |
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ISSN: | 1062-3590 1608-3059 |
DOI: | 10.1134/S1062359022090291 |