Impact of Climate change on Scottish Crossbill using Machine learning.

Impact of Climate change on Scottish Crossbill using Machine learning.

1Mr. Prathamesh Patil, 2Miss. Aditi Mirajkar, 3Mr. Pankaj Ghuge, 4Mr. Krunal Sonavane,

5Miss. Nikita Gite, 6Miss. Shreya Desai, 7Prof. Meghana Bandiwadekar.

1Student,2Student,3Student,4Student,5Student,6Student,7Asst. Professor

 Department of Computer Science and Engineering,

D.Y.Patil College Of Engineering and Technology,Kolhapur,India.

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Abstract:  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.

Keywords – Machine learning, Scottish crossbills, Species distribution models, Prediction, Climate Change, habitat suitability, protection, biodiversity, future modeling.