Urban Arthropod Abundance Modeling

Built linear regression models in Python and scikit-learn to test how temperature, air quality, season, and year relate to fly and spider abundance in field data collected around Pelham Parkway in the Bronx. Standardized continuous predictors and one-hot encoded seasonal categories, then exported per-taxon coefficients and predictions to CSV so results stayed reproducible. Wrote the visualization layer in Matplotlib and pandas to produce the figures I presented in a scientific poster at the NYCSRM Consortium Student Research Symposium, held at the American Museum of Natural History. Reported adjusted R-squared alongside R-squared, which showed the models explained little variance at this sample size and that the coefficients were not reliable enough to draw conclusions from.