Data and code for: Leveraging long-term data to improve biodiversity monitoring with species distribution models
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This dataset contains 10 years (2010â2019) 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 presenceâabsence 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 st..., , , ## **Overview**
When using this dataset, please cite the associated article:
Anselmetto N, Garbarino M, Weldy MJ, Bell D, Daly C, Epps CW, Ferrari N, Kim H, LaManna JA, Lesmeister D, Penaluna BE, Schulze M, Sutton M, Tosa MI, & Betts MG. (2025). *Leveraging long-term data to improve biodiversity monitoring with species distribution models*. Journal of Applied Ecology.
This repository contains data and R code associated with the manuscript.
The dataset provides a .csv dataframe with bird occurrence data (3 focal species) across 182 sampling locations for 10 years and associated microclimate and vegetation predictors, and R code to reproduce model calibration, validation, and spatial predictions.
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## **Folder Structure**
```
data_and_code.zip/open_data/
âââ open_data.Rproj # R Project file
âââ .Rhistory # R session history
âââ README.txt # Short internal readme
â
âââ data/
â âââ data_raw/
â âââ df/
â â âââ birds_mic...,
创建时间:
2025-09-13



