Keywords
BGR
yo‘l tarmoqlari
GIS
OpenStreetMap
fazoviy tahlil.
How to Cite
Abstract
Mazkur tadqiqotda Molguzar botanik-geografik rayonida yo‘l tarmoqlari va floristik yig‘ma ma’lumotlarning fazoviy taqsimlanishi o‘rtasidagi bog‘liqlik GIS asosidagi fazoviy tahlil usullari hamda OpenStreetMap yo‘l tarmog‘i ma‘lumotlari yordamida baholandi. Tadqiqotda 3260 ta gerbariy namunasining geografik koordinatalari tahlil qilinib, har bir yig‘ma nuqtasidan eng yaqin avtomobil yo‘ligacha bo‘lgan masofa hisoblandi. Natijalarga ko‘ra, namunalarning yo‘lgacha bo‘lgan median masofasi 0,16 km ni tashkil etdi. Gerbariy namunalarining 74,4 % avtomobil yo‘llaridan 500 m gacha, 85,5 % esa 1 km gacha bo‘lgan hududlarda yig‘ilgan, 5 km dan uzoq hududlarda to‘plangan namunalar ulushi esa atigi 0,3 % ni tashkil etdi. Olingan natijalar floristik yig‘ma ma’lumotlarning fazoviy taqsimlanishi yo‘l tarmoqlari bilan chambarchas bog‘liqligini ko‘rsatdi hamda kam o‘rganilgan hududlarni aniqlash va kelgusidagi floristik tadqiqotlarni rejalashtirish uchun muhim ilmiy asos yaratadi.References
1. Azimova, D. E. (2018). Molguzar tizmasi florasi (PhD dissertation, 03.00.05 – Botanika). Tashkent, Uzbekistan.
2. Beck, J., Böller, M., Erhardt, A., & Schwanghart, W. (2014). Spatial bias in the GBIF database and its effect on modeling species' geographic distributions. Ecological Informatics, 19, 10–15. https://doi.org/10.1016/j.ecoinf.2013.11.002
3. Bowler, D. E., Callaghan, C. T., Bhandari, N., Dänhardt, J., Fink, D., Hochachka, W. M., Johnston, A., Kennedy, C. M., Kelling, S., Robinson, O. J., Winter, M., & Amano, T. (2022). Towards an ecology of biodiversity data. Nature Ecology & Evolution, 6(5), 451–460. https://doi.org/10.1038/s41559-022-01708-6
4. Canhos, V. P., Souza, S., Giovanni, R., & Canhos, D. A. L. (2004). Global biodiversity informatics: Setting the scene for a "new world" of ecological modeling. Biodiversity Informatics, 1, 1–13.
5. He, J., Yang, W., You, Q., Hu, Q., Cong, M., Tian, C., & Ma, K. (2025). Impacts of road networks on the geography of floristic collections in China. Plant Diversity. https://doi.org/10.1016/j.pld.2025.02.001
6. Kadmon, R., Farber, O., & Danin, A. (2004). Effect of roadside bias on the accuracy of predictive maps produced by bioclimatic models. Ecological Applications, 14(2), 401–413. https://doi.org/10.1890/02-5364
7. Karimov, B., Mamadaliev, S., Kurbanova, D., Yusupov, Z., & Tojibaev, K. S. (2026). Accessibility bias and the road-map effect in biodiversity data across Central Asia and Afghanistan. Journal of Asia-Pacific Biodiversity. Advance online publication. https://doi.org/10.1016/j.japb.2026.02.007
8. Meyer, C., Weigelt, P., & Kreft, H. (2016). Multidimensional biases, gaps and uncertainties in global plant occurrence information. Ecology Letters, 19(8), 992–1006. https://doi.org/10.1111/ele.12624
9. Nualart, N., Ibáñez, N., Soriano, I., & López-Pujol, J. (2017). Assessing the relevance of herbarium collections as tools for conservation biology. The Botanical Review, 83(4), 303–325. https://doi.org/10.1007/s12229-017-9188-z
10. Oliveira, U., Brescovit, A. D., Souza, C. M., Jr., Cancello, E. M., Carvalho, C. J. B., Silva, T. S. F., Silva, D. P., Brandão, R. A., & Santos, A. J. (2016). The strong influence of collection bias on biodiversity knowledge shortfalls of Brazilian terrestrial biodiversity. Diversity and Distributions, 22(12), 1232–1244. https://doi.org/10.1111/ddi.12489
11. Zizka, A., Silvestro, D., Andermann, T., Azevedo, J., Duarte Ritter, C., Edler, D., Farooq, H., Herdean, A., Ariza, M., Scharn, R., Svantesson, S., Wengström, N., Zizka, V., & Antonelli, A. (2021). CoordinateCleaner: Standardized cleaning of occurrence records from biological collection databases. Methods in Ecology and Evolution, 12(4), 744–751. https://doi.org/10.1111/2041-210X.13660