Data and code for: Leveraging long-term data to improve biodiversity monitoring with species distribution models

This dataset contains 10 years (2010–2019) of bird occurrence records and associated environmental predictors from the H.J. Andrews Experimental Forest (Oregon, USA). Bird distributions were monitored during the breeding season at 184 sites, resulting in presence–absence data for 37 species. These observations are paired with fine-scale environmental data, including hourly under-canopy temperature records from 184 microclimate sensors and LiDAR-derived vegetation structure metrics at 25-m resolution. The dataset also includes derived predictor variables (e.g., growing degree days, canopy cover) and R code used for model calibration, validation, and spatial prediction.

The data were assembled to support the development and evaluation of dynamic species distribution models (SDMs) that account for interannual variability and microclimatic heterogeneity. However, the resources have reuse potential for biodiversity monitoring, ecological forecasting, habitat management, and methodological studies of spatial and temporal model transferability.

Bird and microclimate data were collected as part of long-term monitoring programs at the H.J. Andrews Experimental Forest and do not involve animal capture or manipulation. All species are free-ranging and no additional ethical approvals were required.