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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM48462
Volume:
9 |
5 |
May 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Climate change is transforming immensely to the ecosystem, which is forcing the species to adapt or migrate to ensure their survival. This research investigates the effects of climate change on the population of birds, with extremely reliant on the pine forests of Scottish crossbills (Luxia Scotica). A machine learning-based species distribution model was developed to predict the suitability of future habitat under various climatic landscapes by integrating historical climate data from the records of the UK Met Office and species phenomenon from GBIF. The model enlists algorithms like random forest and nerve network to examine temperature, rainfall and snowfall patterns. The findings reveal a decrease in Scottish crossbill houses, and highlighting the immediacy of specific conservation is important. It displays the importance of future modeling in conserving biodiversity and the actionable information that can be provided to policy makers and scientists.
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Publication Date
5/21/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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