ANNOUNCEMENTS
This study comprehensively evaluates the interplay between climatic factors and agricultural biodiversity across the diverse districts of Uttarakhand, India. Utilizing a combination of statistical analyses, including correlation matrices, linear and lasso regression models, and an assessment of feature importance, the research investigates how maximum and minimum temperatures (Tmax and Tmin) and precipitation influence the Shannon Diversity Index (SDI) and Shannon Evenness Index (SEI). Results from the study illustrate significant spatial variability in the effects of these climatic variables on crop diversity. Notably, the lasso regression model highlights specific districts where climate variables have pronounced impacts, facilitating the identification of targeted agricultural interventions. This study underscores the necessity for district-specific agricultural policies that accommodate local climatic conditions and agricultural practices to enhance crop diversity and sustainability. The findings advocate for the integration of climate-adaptive strategies in agricultural planning and management, aiming to bolster ecological resilience and improve agricultural outcomes across Uttarakhand.
Keywords: Agricultural Biodiversity, Climate Change, Crop Diversity, Shannon Index, Regression Analysis.
